Patent Publication Number: US-11651771-B2

Title: Home appliance and speech recognition server system using artificial intelligence and method for controlling thereof

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application is a continuation of U.S. application Ser. No. 16/523,548, filed on Jul. 26, 2019, which claims the benefit of an earlier filing date and right of priority to Korean Application No. 10-2018-0087782, filed on Jul. 27, 2018, the disclosures of which are incorporated herein by reference in their entirety. 
    
    
     TECHNICAL FIELD 
     A home appliance and a speech recognition server system, in which a plurality of speech recognition home electronics may perform a command intended by a user without conflicting with each other with respect to speech command of the user, and a method for controlling such a home appliance and a speech recognition server system is disclosed herein. 
     BACKGROUND 
     Home appliances used in a predetermined space such as home or offices, and the like perform their own functions and operations. Such home appliances may include washing machines, dryers, air conditioners, robot cleaners, air cleaners, refrigerators, oven ranges, water purifiers, and the like. 
     In order to control an operation of the home appliances, a user may use a button provided on a main body of the home appliances. However, in order to press the button to control the operation of the home appliance, the user needs to move directly to the home appliance. 
     At this time, the user may use a remote control device, for example, a remote controller that may remotely control the operation of the home appliance. However, when the respective home appliances include the respective remote control devices, it is inconvenient to find the remote control device with respect to the desired home appliance among a plurality of remote control devices. 
     In order to solve this inconvenience, recently, home appliances use speech recognition technology capable of controlling the operation based on speech of a user. 
     However, the technology has a limitation that a control target device disposed in a place other than the current position of the user may not be controlled. 
     Further, the technology has a problem that all speech recognition devices may respond to one command, when the plurality of speech recognition devices are arranged in the same place. Therefore, there is a problem that the control operation intended by the user is not performed properly. 
     Further, for the control of the speech recognition, the technology has inconvenience that the user may explicitly utter the name of a particular product, which is previously stored by a manufacturer. 
     Further, in order to control the speech recognition, the technology has an inconvenience that the user may clearly select a particular product so as to be controlled. 
     SUMMARY 
     The present disclosure provides a home appliance and a speech recognition server system that control a control target device disposed in a space different from another space where a speech recognition device that recognizes speech of a user is disposed and a method for controlling such a home appliance and a speech recognition server system. 
     The present disclosure further provides a home appliance and a speech recognition server system that does not allow controlling of the control target device disposed in the same space as a speech recognition device that recognizes speech of a user and a method for controlling such a home appliance and a speech recognition server system. 
     The present disclosure also provides a home appliance and a speech recognition server system capable of controlling a control target device based on a name or a nickname designated by a user and a method for controlling such a home appliance and a speech recognition server system. 
     The present disclosure also provides a home appliance and a speech recognition server system capable of controlling a control target device based on a specialized control command only applied to particular home electronics and a method for controlling such a home appliance and a speech recognition server system. 
     The objects of the present disclosure are not limited to the above-mentioned objects, and the other objects and advantages of the invention, which are not mentioned, may be understood by the following description, and more clearly understood by the implementations of the present disclosure. It will be also readily understood that the objects and the advantages of the present disclosure may be implemented by means defined in the appended claims and a combination thereof. 
     One general aspect of the present disclosure, there is provided a home appliance and a speech recognition server system and a method for controlling such home appliance and speech recognition server system. The home appliance and the speech recognition server system and the method for controlling such home appliance and speech recognition server system determine whether a first group to which a control target belongs is identical to a second group to which a speech recognition device belongs when the control target device is different from the speech recognition device. Then, when the first group is different from the second group, the present disclosure controls the operation of the control target device based on a control command. Accordingly, the user may control the control target device disposed in a space different from another space where the speech recognition device is disposed. 
     Another general aspect of the present disclosure, there is provided a home appliance, a speech recognition server system, and a method for controlling such home appliance and speech recognition server system. The home appliance, the speech recognition server system, and the method for controlling such home appliance and speech recognition server system determine whether the first group to which the control target device belongs is identical to the second group to which the speech recognition product belongs when the control target device is different from the speech recognition device. Then, when the first group is identical to the second group, the present disclosure controls the speech recognition device to ignore the control command of the user. As a result, the present disclosure may prevent the control of the control target device from being repeated two or more times by the plurality of speech recognition devices. 
     Another general aspect of the present disclosure, there is provided a home appliance, a speech recognition server system, and a method for controlling such home appliance and speech recognition server system. The home appliance, the speech recognition server system, and the method for controlling such home appliance and speech recognition server system receives a name or a nickname capable of identifying the home appliance the home appliance includes in advance and stores information on the inputted name or nickname. Then, the present disclosure determines the control target device based on the stored name or nickname. Accordingly, the user may control the control target device with a desired name or nickname. 
     Another general aspect of the present disclosure, there is provided a home appliance and a speech recognition server system and a method for controlling such a home appliance and a speech recognition server system. The home appliance and the speech recognition server system and the method for controlling such a home appliance and a speech recognition server system may determine the control target device based on a specialized control command when a control command inputted from a user is a specialized control command. As a result, the user may control a device without designating the control target device. 
     Another general aspect of the present disclosure, there is provided a home appliance and a speech recognition server system and a method for controlling such a home appliance and a speech recognition server system. The home appliance and the speech recognition server system and the method for controlling such a home appliance and a speech recognition server system may include remotely controlling the control target device disposed in a space different from another space where the speech recognition device that recognizes the speech of the user is disposed. At this time, the speech recognition product may notify the user of the control result of the control target device through speech. As a result, the user may easily control the home appliances disposed in another space and immediately identify the control results. Therefore, a user convenience to use a plurality of home appliances may be improved. 
     Another general aspect of the present disclosure, there is provided a home appliance and a speech recognition server system and a method for controlling such a home appliance and a speech recognition server system. In the home appliance and the speech recognition server system and the method for controlling such a home appliance and a speech recognition server system, the control of the control target device disposed in the space same as the speech recognition device that recognizes the speech of the user may not be allowed. As a result, it is possible to prevent a command conflict or mutual interference between the speech recognition devices from occurring even when a plurality of speech recognition devices is arranged in a space where the user is disposed. Therefore, stability in the operation for the plurality of speech recognition devices may be improved. Further, satisfaction of the user with respect to the use may be improved due to a stable operation. 
     Another general aspect of the present disclosure, in the home appliance, the speech recognition server system, and the method for controlling such home appliance and speech recognition server system, the user may control the control target device based on the pre-designated name or nickname. As a result, the user may control the particular device with a name easy to remember for the user. Therefore, the user convenience with respect to using the speech recognition device may be improved. Further, when the user utters the nickname of the home appliance, affection of the user with respect to the home appliance and satisfaction of the user with respect to using the home appliance may be improved. 
     Another general aspect of the present disclosure, according to the present disclosure, in the home appliance, the speech recognition server system, and the method for controlling such home appliance and speech recognition server system, the user may control the control target device with the specialized control command only applied to the specific home appliances. As a result, as the user does not need to utter the name of the control target device, the length of the control command to control the control target device may be shortened. Therefore, the user may control the control target device with a short length of control command, thereby improving the user convenience. Further, the user may feel that the speech recognition device becomes smarter. Therefore, satisfaction of the user with respect to the device may be improved, and a brand image of the device may also be improved. 
     The effect of the present disclosure is not limited to the above-mentioned effect, and those skilled in the art of the present disclosure can easily understand various effects of the present disclosure based on the disclosure of the present disclosure. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG.  1    shows an operation of a home network system that uses a speech recognition technology. 
         FIG.  2    is a schematic view of a home appliance and a speech recognition server system according to an implementation of the present disclosure. 
         FIG.  3    shows home electronics which includes the home appliance of  FIG.  2   . 
         FIG.  4    is a block diagram of a home appliance according to an implementation of the present disclosure. 
         FIG.  5    shows a speech recognition server system that controls a home appliance according to an implementation of the present disclosure. 
         FIG.  6    is a block diagram of relations between the home appliance and a speech recognition server system of  FIG.  5   . 
         FIG.  7    is a flowchart of a method for controlling speech recognition according to some implementations of the present disclosure. 
         FIG.  8    shows a representative device for each group of a home appliance. 
         FIG.  9    is a flowchart of a method for controlling speech recognition for each case according to an implementation of the present disclosure. 
         FIG.  10    is a flowchart of a method for controlling speech recognition for each case according to another implementation of the present disclosure. 
         FIG.  11    is a schematic view of a method for controlling speech recognition according a first implementation of the present disclosure. 
         FIG.  12    is a schematic view of a method for controlling speech recognition according to a second implementation of the present disclosure. 
         FIG.  13    is a schematic view of a method for controlling speech recognition according to a third implementation of the present disclosure. 
         FIG.  14    is a schematic view of a method for controlling speech recognition according to a fourth implementation of the present disclosure. 
         FIG.  15    shows a speech recognition server system that communicates with a user terminal. 
         FIG.  16    shows an interface that sets a name or a nickname of the specific home electronics. 
         FIG.  17    shows a group change interface of a plurality of home electronics the home appliance includes. 
     
    
    
     DETAILED DESCRIPTION 
     The advantages and features of the present disclosure and a method of achieving them will become apparent with reference to the implementations described in detail below with reference to the accompanying drawings. However, the present disclosure should not be construed as limited to the implementations set forth herein and may be implemented in many different manners. Rather, these implementations are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art. The present disclosure is defined by the scope of the claims. Like reference numerals refer to like elements throughout the specification. 
     Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense commonly understood by the person skilled in the art to which the present disclosure pertains. Also, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise. 
     Further, with respect to implementation of the present disclosure, the present disclosure may be described by subdividing an individual component, the components of the present disclosure may be implemented within a device or a module, or a component of the invention may be implemented by being divided into a plurality of devices or modules. 
     Hereinafter, a home network system using a speech recognition technology will be described. 
       FIG.  1    shows an operation of a home network system using a speech recognition technology. 
     Referring to  FIG.  1   , the home network system  1  includes a plurality of speech recognition units  11 ,  12 ,  13  and  14 , a plurality of control target devices  21 ,  22 ,  23  and  24 , and a controller  30 . At this time, the plurality of speech recognition units  11 ,  12 ,  13 , and  14  and the plurality of control target devices  21 ,  22 ,  23 , and  24  are arranged in different areas from one another, respectively. 
     For example, the first speech recognition unit  11  and the first control target device  21  may be arranged in ‘room  1 ’, the second speech recognition unit  12  and the second control target device  22  may be arranged in ‘room  2 ’. 
     At this time, different identifiers, for example, ID, are provided to the respective speech recognition units  11 ,  12 ,  13 , and  14 . The controller  30  may control an operation of the control target devices  21 ,  22 ,  23 , and  24  based on the ID of the speech recognition units  11 ,  12 ,  13 , and  14  to which a speech command is inputted. 
     For example, if light is installed in two places such as room  1  and the living room, the user may select the place of the control target device that is required to be controlled and utter the instructions, for example, “turn on the light in the room  1 ”, “turn off the light in the room  1 ”, “brighten the light in the living room”, and “darken the light in the living room”. 
     However, the home network system of  FIG.  1    may select a place where a speech command is input based on the IDs of the speech recognition units  11 ,  12 ,  13 , and  14 . Therefore, when a plurality of the same control target devices are installed in the house, the user may control the control target device installed at a current position, even if the current position is not uttered. 
     Hereinafter, according to some implementations of the present disclosure, a home appliance and a speech recognition server system and a method for controlling the home appliance and the speech recognition server system will be described with reference to  FIG.  2    to  FIG.  17   . 
       FIG.  2    is a schematic view of a home appliance and a speech recognition server system according to an implementation of the present disclosure.  FIG.  3    shows home electronics which include the home appliance of  FIG.  2   . 
     Referring to  FIG.  2   , according to an implementation of the present disclosure, a smart home system  10  may include a home appliance  100  and a speech recognition server system  200 . The home appliance  100  may communicate with other electronic devices or network using a communication module or Access Point (AP)  300 . The speech recognition server system  200  may use artificial intelligence and may include a plurality of servers to recognize speech and control home electronics. 
     Specifically, referring to  FIG.  3   , a home appliance  100  may include a washing machine  101 , a dryer  102 , an air conditioner  103 , a robot cleaner  104 , an air purifier  105 , a refrigerator  106 , an oven range  107 , and a water purifier  108 . However, this is merely an example, and the home appliance  100  may include various types of home appliances. 
     At this time, the components of the home appliance  100  may be classified into different groups from one another according to the positions at which the components of the home appliance  100  are arranged in the house. 
     For example, the washing machine  101  and the dryer  102  arranged in the balcony, or veranda/terrace, may be designated as a first group G 1 . The air conditioner  103 , the robot cleaner  104 , and the air cleaner  105  arranged in the living room may be designated as a second group G 2 . Further, the refrigerator  106 , the oven range  107 , and the water purifier  108  arranged in the kitchen may be designated as a third group G 3 . However, this is only one example, and the components of the group and the home appliances in each group may be changed and implemented. 
     At this time, the number of groups and the home appliances included in each group may be preset by the user. Further, the user may change the number of groups and a configuration of the home electronics included in each group using a user terminal. At this time, the user terminal may provide the user with an interface, UX/UI, that may change the number of groups and the configuration of home electronics included in each group. A detailed description thereof will be described later with reference to  FIG.  16   . 
     Each of the home electronics included in the home appliance  100  may include a communication module therein and may communicate with the electronic devices inside/outside of the smart home system  10 . 
     At this time, the smart home system  10  may further include an access point (AP) device. The home appliance  100  may access a wireless network through the AP device  300 . 
     The AP device  300  allocates a wireless channel according to a predetermined communication method to each electronic device included in the home appliance  100 . The predetermined communication method may be a Wi-Fi communication method. With respect to the above, the communication module provided by the home appliance  100  may be a Wi-Fi communication module, but the present disclosure is not limited to the communication method. For example, the home appliance  100  may use an NFC module, a zigbee communication module, and a Bluetoot™ communication module, and the like. 
     The home appliance  100  may be connected to a server included in the speech recognition server system  200 , an external server, or a user terminal through the AP device  300 . As a result, services such as remote monitoring, remote control, and the like of the home appliance  100  may be provided to the user. 
     In other words, the user may identify information on the home appliance  100  in the smart home system  10  or control an operation of the home appliance  100  using the user terminal. 
     According to the implementation of the present disclosure, the home appliance  100  may receive a speech command of the user. Then, the speech recognition server system  200  may analyze the speech command of the user received from the home appliance  100  to determine a control target device and a control command intended by the user. Subsequently, the speech recognition server system  200  may control the determined control target device based on the control command of the user. 
     Hereinafter, each configuration of the home appliance  100  and the speech recognition server system  200  will be described. 
       FIG.  4    is a block diagram of a home appliance according to an implementation of the present disclosure. 
     Referring to  FIG.  4   , according to the implementation of the present disclosure, a home appliance  100  includes a plurality of home electronics. Hereinafter, for example, any one of a plurality of home electronics included in the home appliance  100  will be described. 
     The home appliance  100  includes a speech input  110 , a speech guidance unit  120 , a speech recognition module  130 , a controller  140 , a driver  150 , a communicator  160 , an interface  170 , and a memory  180 . 
     The speech command of the user may be input to the speech input  110 . To this end, the speech input  110  may include one or more microphones (MIC). 
     For example, in order to more accurately receive the speech command of the user, the speech input  110  may include a plurality of MICs. At this time, the plurality of MICs may be spaced apart from one another. 
     The speech input  110  may compare data received from the plurality of MICs therewith and remove the noise therefrom. The speech input  110  may use various noise removing algorithms to remove the noise generated when the speech command of the user is received. Further, the speech input  110  may include the components for processing an audio signal, such as a filter that removes the noise from the audio signal received from each MIC and an amplifier that amplifies the signal outputted by the filter and outputs the amplified signal, and the like. As a result, the speech input  100  may correctly receive the speech command of the user. 
     The speech guidance unit  120  may convert speech data into sound and output the converted sound. The speech guidance unit  120  may include a component, for example, a speaker, and the like, that converts an electric signal into sound. The speech guidance unit  120  may receive the speech data from a text to speech (TTS)  135  described later. 
     The speech recognition module  130  receives the speech command of the user from the speech input  110 . Then, the speech recognition module  130  extracts a keyword included in the speech command received from the speech input  110 . At this time, the extracted keyword may include control target device and a control command. 
     The control target device represents any one of a plurality of home appliances included in the home appliance  100 . For example, the control target device may be any one of a washing machine  101 , a dryer  102 , an air conditioner  103 , a robot cleaner  104 , an air purifier  105 , a refrigerator  106 , and an oven range  107 , and a water purifier  108 . 
     Further, the control command represents the instruction of the user to control the operation of the control target device. At this time, the control command may include a common control command commonly applied to a plurality of devices and a specialized control command only applied to a specific device. 
     For example, “power on” is a common control command. On the other hand, “configure the cold water washing”, and “add the dehydration cycle” are the specialized control commands with respect to the washing machine  101 . 
     Additionally, the user may omit the utterance of the control target device using the specialized control command. In this case, the device which received the specialized control command may determine the control target device based on the specialized control command, and control the target device based on the inputted specialized control command. A detailed description thereof will be described below. 
     The speech recognition module  130  includes an automatic speech recognition (ASR) (hereinafter; ASR)  131 , a natural language processing (NLP) or natural language understanding (hereinafter; NLP)  133 , and a text to speech (TTS) (hereinafter; TTS)  135 . 
     The ASR  131  converts the speech data received from the speech input  110  into text data. The ASR  131  may be variously expressed as a natural language recognition unit or a speech recognition unit, and the like. The ASR  131  may use various techniques and algorithms to convert speech data into text data. The text data converted by the ASR  131  is transmitted to the NLP  133 . 
     The NLP  133  may determine the speech command by analyzing the natural language processing algorithm stored in advance. The NLP  133  may process a natural language, which is a language that a person routinely uses according to a natural language processing algorithm, and may analyze an intention of a user. That is, the NLP  133  performs the natural language processing on the text data received from the ASR  131 , thereby determining a speech command that meets the intention of the user. The NLP  133  may be variously expressed as an intention analysis unit, a natural language processing unit, or a complex sentence recognition unit, and the like. The NLP  133  may use various types of techniques and algorithms to determine the intention of the user. 
     Specifically, the NLP  133  analyzes the text data received from the ASR  131  and extracts a keyword for the speech command. The keyword includes the above-mentioned control command. The keyword may include name of control target-device. 
     At this time, the NLP  133  may determine the control target device to which the specialized control command is applied if the control command is a specialized control command. The information on the specific device to which the specialized control command is applied may be stored in the memory  180  and the stored information may be used. 
     Next, the NLP  133  determines whether the device that receives the speech of the user is identical to the control target device. Then, when the device is different from the control target device, the NLP  133  determines whether a first group to which the device belongs is identical to a second group to which the control target device belongs. When the first group is different from the second group, the NLP  133  transmits a control signal to control the operation of the control target device to the controller  140 . The description thereof will be described below in detail with reference to  FIGS.  7  to  9   . 
     On the other hand, a determination with respect to comparing the device with the control target device may be performed by the controller  140  instead of the NLP  133 . 
     The TTS  135  converts the text into speech data. The TTS  135  may be variously expressed as a speech synthesizer or a speech converter, and the like. The TTS  135  may use various techniques and algorithms that convert the text into the speech data. 
     The TTS  135  transmits the converted speech data to the speech guidance unit  120 . At this time, the text received by the TTS  135  may include a guide speech about the operation result of the control target device. At this time, the TTS  135  may receive the guide speech from a NLP  133  or a controller  140 . 
     The controller  140  may perform overall control of the components included in the home appliance  100 . 
     For example, the controller  140  may control the operation of a driver  150  based on a control command extracted from the NLP  133 . Further, the controller  140  may control other control target devices included in the home appliance  100  based on the control command. 
     Further, the controller  140  may provide predetermined information to the user through visual or auditory means in each step of recognizing speech and controlling the home appliance. For example, the controller  140  may display visual information on the speech recognition process and the home appliance control process on the interface  170 . In addition, the controller  140  may provide auditory information on the process of recognizing the speech and the process of controlling the home appliance through the speech guidance unit  120 . 
     The driver  150  performs a specific operation implemented by the home appliance  100 . The operation of the driver  150  may be performed differently for each home electronics. 
     For example, when the home appliance  100  is a washing machine  101 , the driver  150  may include a drum or a tub and a motor that rotates the drum or the tub. 
     As another example, when the home appliance  100  is a refrigerator  106 , the driver  150  may include a refrigerating compartment driver that operates a fan for the refrigerating compartment to supply the cooled air to a refrigerating compartment, a freezer compartment driver that operations a fan for freezer compartment to supply the cooled air to a freezer compartment, and a compressor driver that operates a compressor to compress the refrigerant, and the like. 
     As another example, when the home appliance  100  is a oven range  107 , the driver  150  may include a microwave driver that outputs a microwave into a cavity, and the like. However, these are merely some implementations, and the present disclosure is not limited thereto. 
     The communicator  160  includes one or more communication modules. As a result, the communicator  160  may wirelessly communicate with other electronic devices to transmit and receive various signals to and from other electronic devices. For example, the communicator  160  may exchange data with a separate server using a wireless network. 
     The interface  170  may include a plurality of operation buttons and a display. The user may set an operation option of the product using the plurality of operation buttons provided on the interface  170 . In addition, the interface  170  may display information on a command input by the user, the processed result of a command input by the user, an operation state, an error state, and the like. For example, the interface  170  may be a form in which a touch pad and a touch screen are coupled to each other. 
     The memory  180  records various kinds of information necessary for the operation of the home appliance, and may include a volatile or non-volatile recording medium. 
     The memory  180  may include an algorithm to recognize the control target device and the control command as a keyword. At this time, the data with respect to the control target device name of the plurality of home electronics included in the home appliance  100  in a form of a database. 
     Further, the memory  180  may store information on the specific device to which the above-mentioned specialized control command is applied. The relations between the specialized control command and the specific device may be stored in a form of a database. Referring to the database stored in the memory  180 , the controller  140  may determine the control target device based on the extracted specialized control command. 
     Further, the memory  180  may store information on a name or a nickname that may identify each of the home electronics included in the home appliance  100 . The controller  140  may determine the control target device based on information on the name or nickname of the home electronics pre-stored in the memory  180 . 
     Further, the memory  180  may store group information on a plurality of home electronics included in the home appliance  100  and information on a representative device of each group. The controller  140  may control the operation of the control target device based on group information pre-stored in the memory  180  and the information on the representative devices of each groups. 
     For reference, the controller  140  of the home appliance  100  may perform machine learning on received speech data. The memory  180  may store data used for the machine learning or the result data, and the like. 
     In more detail, a deep learning technology, which is a type of machine learning, learns at deep level in multi-steps based on data. 
     Deep learning may represent a set of machine learning algorithms that extract key data from various kinds of data as it becomes higher step. 
     The deep learning structure may include an artificial neural network (ANN). For example, the deep learning structure may include a deep neural network (DNN) such as a convolutional neural network (CNN), a recurrent neural network (RNN), and a deep belief network (DBN), and the like. 
     The controller  140  may use various types of known deep learning structures. For example, the controller  140  may use a structure such as a convolutional neural network (CNN), a recurrent neural network (RNN), and a deep belief network (DBN), and the like. 
     Specifically, the convolutional neural network (CNN) is a model that simulates a brain function of a person, which is made based on an assumption that extracts the basic features of an object when the person recognizes an object and then complex calculation is made in the brain and recognizes the object based on the result thereof. 
     The recurrent neural network (RNN) may be used for natural language processing, and the like, and may have a structure effective for time-series data processing that changes with time, and may form an ANN structure by stacking layers every moment. 
     The deep belief network (DBN) is a deep learning structure that is made by stacking restricted boltzman machine (RBM) with many layers, which is a deep learning technique. When the RBM learning is repeated and the predetermined number of layers are formed, the deep belief network (DBN) having the number of layers may be formed. 
     On the other hand, the ANN learning of the controller  140  may be made by adjusting the weight of an inter-node connection line, i.e. by adjusting the bias value if necessary, so that a desired output is obtained for a given input. 
     Further, the ANN may continuously update the weight value by learning. Further, a method such as a back propagation, and the like, may be used for the ANN learning. 
     Meanwhile, the memory  180  may include an ANN pre-learned by machine learning. 
     That is, according to an implementation of the present disclosure, the home appliance  100  may perform the machine learning-based speech recognition that processes the received speech data as input data. At this time, both of unsupervised learning and supervised learning may be used as a machine learning method of the ANN. Further, the controller  140  may control to update the ANN structure after learning according to the configuration. 
     In another implementation of the present disclosure, the speech recognition module  130  and the controller  140  may be a separate external server. Hereinafter, a speech recognition server system  200  including a speech recognition server  230  that performs an operation of the speech recognition module  130  and a control server  240  that performs the operation of the controller  140  will be described with reference to  FIGS.  5  and  6   . 
       FIG.  5    shows a speech recognition server system that controls a home appliance according to an implementation of the present disclosure.  FIG.  6    is a block diagram of relations between the home appliance and the speech recognition server system of  FIG.  5   . 
     Referring to  FIGS.  5  and  6   , according to another implementation of the present disclosure, a home appliance  100  includes a plurality of home electronics. For example, as shown in  FIG.  4   , any one of the plurality of home electronics included in the home appliance  100  will be described. 
     The home appliance  100  includes a speech input  110 , a speech guidance unit  120 , a controller  140 , a driver  150 , a communicator  160 , an interface  170 , and a memory  180 . 
     Each component the home appliance  100  includes according to another implementation of the present disclosure may operate substantially the same as each component the home appliance  100  includes according to an implementation of the present disclosure which is described with reference to  FIG.  4   . Hereinafter, the contents overlapping with the description with reference to  FIG.  4    will be omitted and the differences will be mainly described. 
     A speech recognition server system  200  may exchange data with the home appliance  100  through a wireless communication network. Further, the speech recognition server system  200  may control an operation of the home appliance  100 . 
     The speech recognition server system  200  may include a speech recognition server  230  and a control server  240 . 
     The speech recognition server  230  may include an ASR server  231 , an NLP server  233 , and a TTS server  235 . The speech recognition server  230  may operate substantially the same as the above-mentioned speech recognition module  130  the home appliance  100  includes according to the implementation. 
     Specifically, the ASR server  231  may receive speech data generated from a speech input  110  through a communicator  160 . The ASR server  231  may convert received speech data into text data. The ASR server  231  may be variously expressed as a natural language recognition server or a speech recognition server, and the like. The ASR server  231  may use various techniques and algorithms to convert speech data into text data. The converted text data may be transmitted to the NLP server  233 . 
     The NLP server  233  may process a natural language, which is a language that a person routinely uses according to a natural language processing algorithm, and may analyze intent of the user. That is, the NLP server  233  may perform the natural language processing on the text data received from the ASR server  231  to determine a speech command that meets intent of the user. At this time, the NLP server  233  may be variously expressed as an intention analysis server, a natural language processing server, or a complex sentence recognition server, and the like. The NLP server  233  may use various techniques and algorithms to determine the intent of the user. 
     At this time, the NLP server  233  may analyze the text data received from the ASR server  231  and extract a keyword for the speech command. The keyword includes the above-mentioned control target device and control command. 
     At this time, the NLP server  233  may determine the control target device to which a specialized control command is applied when the control command is the specialized control command. That is, the user may omit an utterance of the control target device using the specialized control command. 
     Then, the NLP server  233  determines whether the device that receives the speech of the user is identical to the control target device. Then, when the device is different from the control target device, the NLP server  233  determines whether a first group to which the device belongs is the same as a second group to which the control target device belongs. Then, when the first group is different from the second group, the NLP server  233  transmits a control signal to control the operation of the target device to a control server  240 . 
     However, the operation of determining whether the first group is different from the second group by the NLP server  233  may be performed by the control server  240 . The description thereof will be described in detail with reference to  FIGS.  7  to  10    below. 
     Additionally, the NLP server  233  may communicate with an external service server  500 . For example, if a speech command of the user is a command that requests information such as the weather, the stock, the news, and the like, the NLP server  233  may request the related information to a server that provides the service. Information received from the external service server  400  to the NLP server  233  may be transmitted to the home appliance  100  or the control server  240 . 
     The TTS server  235  may convert text into speech data. The TTS server  235  may be variously expressed as a speech synthesis server or a speech conversion server, and the like. The TTS server  235  may use various types of techniques and algorithms to convert the text into speech data. The TTS  135  may transmit the converted speech data to a speech guidance unit  120  of a home appliance  100  through the communicator  160 . At this time, the text that the TTS server  235  receives may include the guide speech notifying the control result of the control target device. The TTS server  235  may receive the guide speech from the home appliance  100  and provide the converted speech data to the home appliance  100 . 
     The control server  240  may control the operation of the control target device included in the home appliance  100  based on the control command received from the NLP server  233 . 
     For reference, the speech recognition server  230  and the control server  240  may perform machine learning on received speech data and the extracted control target device and the control command. Algorithms and data, and the like, used for the machine learning may be stored in each server and may be used. As the description of the machine learning has been described above, a detailed description will be omitted here. 
     Meanwhile, unlike the home appliance  100  according to an implementation of the present disclosure described with reference to  FIG.  4   , the controller  140  of the home appliance  100  according to another implementation of the present disclosure may only perform a general control operation of the components included in the home appliance  100 . 
     For example, the controller  140  may control the operation of each component of the home appliance  100  based on the control signal received from the control server  240 . Further, the controller  140  may transmit the speech data received from the speech input  110  to the ASR server  231  through the communicator  160 . Further, the controller  140  may transmit the guide speech received from the communicator  160  to the speech guidance unit  120 . Further, the controller  140  may notify the user of an operation state of the home appliance  100  through the interface  170 . 
     In summary, according to an implementation of the present disclosure, the above-mentioned method for controlling the speech recognition, i.e. the operation described with reference to  FIG.  4   , may all be performed by the home appliance  100 . 
     Meanwhile, according to another implementation of the present disclosure, all or some of the above-mentioned method for controlling the speech recognition may be performed by a separate server, i.e., the speech recognition server  230  or the control server  240 . At this time, the operations of the speech recognition server  230  and the control server  240  may be performed substantially in the same manner by the speech recognition module  130  and the controller  140  according to the implementation of  FIG.  4   . 
     Hereinafter, for convenience of explanation, a method for controlling the speech recognition according to some implementations of the present disclosure will be described based on an implementation including the speech recognition server  230  and the control server  240  shown in  FIGS.  5  and  6   . 
       FIG.  7    is a flowchart of a method for controlling speech recognition according to some implementations of the present disclosure.  FIG.  8    shows a representative device for each group of home appliances. 
     Referring to  FIG.  7   , according to an implementation of the present disclosure, in the method for controlling the speech recognition, a home appliance  100  receives speech of a user S 110 . Speech data of the user is input to the home appliance  100  from the speech input  100 . Hereinafter, for convenience of explanation, home electronics that recognizes speech of the user among a plurality of home electronics included in the home appliance  100  will be defined as ‘a speech recognition product’. 
     The speech data inputted to the speech recognition product may be transmitted to speech recognition server system  200 . 
     Then, the speech recognition server system  200  determines whether the received speech data includes a startup word S 120 . 
     The startup word may be set by the manufacturer. For example, the startup word of the speech recognition product may be “Hi, LG”. At this time, the startup word may be changed in various ways and set. 
     Then, when the inputted speech data includes the startup word, the speech recognition server system  200  may control the speech recognition product so as to receive a natural language command from the user S 131 . 
     For reference, according to another implementation, the home appliance  100  may perform simple speech recognition, i.e., startup recognition, and high level of speech recognition such as a natural language processing, and the like, may be performed by the speech recognition server system  200 . 
     For example, if a wake up speech command, e.g., “Hi LG”, including a pre-set startup word is received, the state of the speech recognition product may be converted into a state to receive the natural language command. In this case, the speech recognition product may only perform a speech recognition process by a speech input of the startup word, and the speech recognition for the subsequent natural language command may be performed by the speech recognition server system  200 . That is, as there is a limitation in the system resource of the home appliance  100 , the complex natural language recognition and processing may be performed by the speech recognition server system  200 . 
     For reference, a determination of the startup word may be performed by the home appliance  100  and the speech recognition server system  200  doubly. Accordingly, it is possible to reduce erroneous recognition of determining a speech input of the startup word and increase a recognition rate. 
     Then, when the natural language command is received after the startup word is recognized, an ASR server  231  may perform a speech recognition operation on received speech data S 233 . The ASR server  231  may convert the received speech data into text data. Converted text data may be transmitted to the NLP server  233 . 
     Then, the NLP server  233  may analyze the result of the speech recognition operation performed by the ASR server  231  S 135 . That is, the NLP server  233  may extract a keyword for a speech command from received text data. The extracted keyword may include a control target device and a control command. 
     Then, the NLP server  233  identifies the control target device based on the extracted keyword (S 140 ). At this time, the control target device may be any one of a plurality of home electronics included in the home appliance  100 . For example, the control target device may be any one of a washing machine  101 , a dryer  102 , an air conditioner  103 , a robot cleaner  104 , an air purifier  105 , a refrigerator  106 , an oven range  107 , and a water purifier  108 . That is, when the user directly utters the name of the device, the device may be the control target device. 
     Further, based on the name or the nickname pre-stored by the user, the NLP server  233  may determine the control target device. The user may set the name or the nickname for the specific device as a word desired by the user, and the NLP server  233  may determine the control target device based on the pre-stored name or nickname. This will be described below with reference to  FIG.  17   . 
     On the other hand, when the user does not directly utter the control target device, the NLP server  233  may determine the control target device based on the control command. 
     Specifically, the control command may include a common control command commonly applied to a plurality of devices, and a specialized control command applied only to a specific device. If the control command is a specialized control command, the NLP server  233  may determine the control target device based on the specialized control command. Accordingly, the user may omit the utterance of the control target device by uttering the specialized control command. 
     Then, the NLP server  233  transmits the determined control target device and control command to the control server  240 . 
     Then, the control server  240  determines whether the determined control target device is identical to the speech recognition device that recognizes the speech of the user S 150 . That is, when the user intends to control the speech recognition device, the speech recognition device is identical to the control target device. On the other hand, when the user intends to control a control target device which is not the speech recognition device, the speech recognition device may be different from the control target device. Therefore, the control server  240  determines whether the speech recognition device is identical to the control target device and whether the command of the user enables controlling other electronics. 
     Then, if the command of the user controls the other home electronics, that is, the speech recognition device is different from the determined control target device, the control server  240  determines whether the speech recognition device is a representative device S 160 . 
     The representative devices may be preset one by one for a plurality of groups of home appliances  100 . 
     For example, referring to  FIG.  8   , in the first group G 1  including a washing machine  101  and a dryer  102 , a representative product RP_G 1  may be set as the washing machine  101 . Similarly, in a second group G 2  including an air conditioner  103 , a robot cleaner  104 , and an air cleaner  105 , the representative product RP_G 2  may be set as the air conditioner  103 . Further, in the third group G 3  including a refrigerator  106 , a oven range  107 , and a water purifier  108 , the representative product RP_G 3  may be set as the refrigerator  106 . 
     The user may change the setting of the group and the representative product for the home appliance  100  using a separate interface. If a representative product is not designated, one product may automatically be designated as a representative product in one group. 
     In this example, selecting the representative products may prevent the plurality of home electronics arranged in one place and set as the same group from generating the control command many times. By designating the representative product, only one control command is generated in one group. That is, when there is a control target device in a space different from another space in which the speech recognition product is arranged, only control commands generated from the representative product may be performed by a control server  240 . 
     As a result, it is possible to prevent a command conflict or mutual interference between speech recognition products from occurring even when plurality of speech recognition products are arranged in a space where the user is located. Therefore, the stability in the operation for plurality of speech recognition products may be improved. 
     Then, the control server  240  determines whether a speech recognition product is arranged in a space different from another space where a control target device is disposed (S 165 ). That is, the control server  240  determines whether a group to which the speech recognition product belongs is different from a group to which the control target device belongs. 
     Then, if the group to which the speech recognition product belongs is different from the group to which the control target device belongs, the operation of the control target device is controlled based on a control command S 170 . 
     Then, the control server  240  receives control results for the operation of the control target device. 
     Then, the control server  240  transmits the control result of the operation of the control target device to the speech recognition device. 
     Then, the speech recognition product displays the received control result on the interface  170  (S 180 ). Accordingly, the user may confirm the control result of the control target device through the interface  170  provided on the speech recognition product. 
     Then, the speech recognition device may transmit guide speech including the received control result to a TTS server  235 . The TTS server  235  may convert the received guide speech to speech data and transmit the converted speech data to the speech recognition device. The speech recognition device may convert the received speech data into sound by a speech guidance unit  120  and output it S 185 . 
     On the other hand, when the speech recognition device is not a representative device, the control server  240  transmits an ignore command (Ignore CMD) to the speech recognition product to ignore a control command S 190 . Similarly, even when the speech recognition device is arranged in a space different from another space where the control target device is disposed, the control server  240  transmits an ignore command (Ignore CMD) to the speech recognition product. 
     Additionally, the above-mentioned method for controlling the speech recognition may also be applied to a device that does not have a speech recognition function but may be remotely controlled through the control server  240 . At this time, the home appliance  100  may include a device that does not have the function for the speech recognition. Devices with no function for speech recognition may be included in the specific group and may be the remotely controlled control target devices. Accordingly, the speech recognition device may remotely control the device with no function for speech recognition using the method for controlling the speech recognition described above. 
     Hereinafter, the method for controlling the speech recognition according to some implementations of the present disclosure will be described for each case. 
       FIG.  9    is a flowchart of a method for controlling speech recognition for each case according to an implementation of the present disclosure.  FIG.  10    is a flowchart of a method for controlling speech recognition for each case according to another implementation of the present disclosure. 
     Hereinafter, the same contents as those of the method for controlling speech recognition described with reference to  FIG.  7    will be omitted, and the differences or features will be mainly described. 
     Referring to  FIG.  9   , a home appliance  100  receives speech of a user S 210 . The home appliance  100  receives speech data of the user from a speech input  110 . The speech data inputted to the speech recognition product may be transmitted to a speech recognition server system  200 . 
     Next, a speech recognition server  230  performs a speech recognition operation on the received speech data S 220 . 
     Specifically, an ASR server  231  included in the speech recognition server  230  converts the received speech data into text data. The converted text data is transmitted to an NLP server  233 . 
     Then, the NLP server  233  included in the speech recognition server  230  analyzes the result of the speech recognition operation performed by the ASR server  231  S 135 . That is, the NLP server  233  extracts a keyword for the speech command from the received text data. The extracted keyword may include a control target device and a control command. 
     Then, the NLP server  233  identifies the control target device based on the extracted keyword S 230 . 
     At this time, the NLP server  233  may determine the control target device based on the name or nickname pre-stored by the user. The user may set the name or the nickname for the specific device to a word desired by the user, and the NLP server  233  may determine the control target device based on the pre-stored name or nickname. The description thereof is will be described below with reference to  FIG.  17   . 
     Further, when the user does not directly utter the control target device, the NLP server  233  may determine the control target device based on the control command. At this time, the control command may include a common control command commonly applied to a plurality of products and a specialized control command applied only to a specific product. 
     When the control command is the specialized control command, the NLP server  233  may determine the control target device based on the specialized control command. Accordingly, the user may omit the control target device by uttering the specialized control command. 
     On the other hand, when the control command is a common control command, the NLP server  233  may not determine the control target device. At this time, the NLP server  233  transmits only the common control command to the control server  240 . 
     Then, the control server  240  controls the speech recognition device based on the received common control command S 232 . However, the control server  240  may control all devices that recognize the speech of the user based on the common control command S 234 . 
     For example, “power on” may be identified as a common control command when the user utters “power on”. At this time, the contents with respect to the utterance of the user does not include the control target device, the control server  240  may transmit a control command to turn on the power for all the devices in which the speech of the user is recognized. That is, when the user utters “power on” in the balcony of  FIG.  8   , both the washing machine  101  and the dryer  102  may be turned on. Hereinafter, this operation case is defined as an “A case”. 
     On the other hand, if the control target device is identified in S 230 , the NLP server  233  determines whether the speech recognition device is identical to the control target device S 240 . 
     Then, if the control target device is identical to the speech recognition device, the control server  240  receives the control target device and control command from the NLP server  233  S 242 . 
     Then, the control server  240  controls the control target device based on the control command S 244 . That is, as the control target device is identical to the speech recognition device, the control server  240  controls the speech recognition device based on the control command. 
     For example, when the user utters “power on the washing machine” in front of the washing machine  101 , both the speech recognition device and the control target device are the washing machine  101 . In this case, the control server  240  may control the washing machine  101  to turn on the power. Hereinafter, this operation case is defined as a ‘B case’. 
     Meanwhile, when the control target device is different from the speech recognition product in S 240 , the NLP server  233  determines whether the group to which the control target device belongs is identical to the group to which the speech recognition product belongs S 250 . 
     Then, the group to which the control target device belongs is identical to the group to which the speech recognition device belongs, the NLP server  233  may transmit an ignore command (Ignore CMD) to the speech recognition device to ignore the inputted control command S 254 . 
     For example, when the user utters “power on the washing machine” in front of the dryer  102 , the speech recognition device is the dryer  102  and the control target device is the washing machine  101 . At this time, the group of the dryer  102  is a first group G 1 , and the group of the washing machine  101  is also a first group G 1 . In this case, the NLP server  233  may control the dryer  102  to ignore the control command. Hereinafter, this operation case is hereinafter defined as a ‘C case’. 
     Meanwhile, when a group to which the control target device belongs is different from a group to which the speech recognition device belongs in S 250 , the NLP server  233  determines whether the speech recognition device is a representative device of the group S 260 . 
     Then, when the speech recognition device is a representative device of the group, the control server  240  receives the control target device and the control command from the NLP server  233  S 262 . 
     Then, the control server  240  controls the control target device based on the control command S 264 . In this case, as the control target device is arranged in a space different from another space where the speech recognition device is disposed, the control server  240  receives the control result of the operation of the control target device and transmits information on the received control result to the speech recognition device. Then, the speech recognition device outputs information on the received control result through speech. 
     For example, when the user utters “turn on the air conditioner” in front of the washing machine  101 , the speech recognition device is the washing machine  101  and the control target device is the air conditioner  103 . At this time, the group of the washing machine  101  is a first group G 1 , and the group of the air conditioner  103  is a second group G 2 . Further, the washing machine  101  corresponds to the representative device of the first group G 1 . In this case, the control server  240  may control the power supply of the air conditioner  103  to be turned on. Then, the control server  240  transmits the control result of the air conditioner  103  to the washing machine  101 . The washing machine  101  may output the control result of the air conditioner  103  through speech. Hereinafter, this operation case is hereinafter defined as a ‘D case’. 
     On the other hand, when the speech recognition device is not the representative device of the group in S 260 , the NLP server  233  may transmit an ignore command (Ignore CMD) to the speech recognition device to ignore the inputted control command S 274 . 
     For example, when the user utters “turn on the air conditioner” in front of the dryer  102 , the speech recognition device is the dryer  102  and the control target device is the air conditioner  103 . At this time, the group of the dryer  102  is the first group G 1 , and the group of the air conditioner  103  is the second group G 2 . However, the dryer  102  is not a representative device of the first group G 1 . In this case, the NLP server  233  may control the dryer  102  to ignore the control command. Hereinafter, this operation case is defined as an “E case”. 
     A method for controlling the speech recognition according to another implementation of the present disclosure shown in  FIG.  10    operates substantially in the same manner as the method for controlling the speech recognition according to another implementation of the present disclosure which is described above with reference to  FIG.  9   . 
     S 330 , S 340 , S 350 , and S 360  shown in  FIG.  10    are substantially the same as S 230 , S 240 , S 250 , and S 260  described above with reference to  FIG.  9   . The subject of S 230 , S 240 , S 250 , and S 260  is a speech recognition server  230 , and the subject of S 330 , S 340 , S 350 , and S 360  is a control server  240 . 
     That is, in the implementation in  FIG.  10   , performing a speech recognition operation to identify a control target device and the control command i.e., S 320 , is performed by an NLP server  233 . 
     The determination whether the control target device is identified S 330 , whether the control target device is identical to the speech recognition device S 340 , whether the control target device and the speech recognition device belong to the same group S 350 , and whether the speech recognition device is a representative device of the group (S 360 ) may be performed by the control server  240 . 
     Then, the method for controlling a home appliance  100  with respect to each determination is the same as the above-mentioned manner. The repeated description will be omitted. 
     Hereinafter, according to some implementations of the present disclosure, the method for controlling the speech recognition will be described with specific examples. 
       FIG.  11    is a schematic view of a first implementation of a method for controlling speech recognition according to the present disclosure. 
     Referring to  FIG.  11   , a home appliance  100  may receive speech of a user first (S 410 ). The home appliance  100  may receive speech data of the user from a speech input  110 . Hereinafter, the case where the user utters “Hi LG, turn on the power” in the balcony will be described as an example of a method for controlling the speech recognition of the present disclosure. 
     A washing machine  101  and a dryer  102  disposed in the balcony may recognize a startup word from the speech data of the user, respectively. The startup word may be “Hi LG”. 
     For reference, as mentioned above, an operation of recognizing the startup word may be performed by a speech recognition server system  200 . Hereinafter, for example, the case where the home appliance  100  recognizes the startup word will be described, for convenience of explanation. 
     Then, when the startup word is recognized, the home appliance  100  may process the contents that the user utters as a natural language command after the startup word is inputted. 
     Then, the speech data corresponding to the natural language command may be transmitted to the speech recognition server system  200  S 420 . At this time, the natural language command may include speech data of “turn on the power”. 
     Then, when the natural language command is received, an ASR server  231  performs a speech recognition operation on received speech data S 430 . The ASR server  231  may convert the received speech data into text data. The converted text data may be transmitted to an NLP server  233 . 
     Then, the NLP server  233  may analyze the result of a speech recognition operation performed by the ASR server  231  S 440 . That is, the NLP server  233  may extracts a keyword, that is, a control target device or a control command, for a speech command from received text data. At this time, a control command of the keywords extracted from a natural language command may be ‘turn on the power’. Then, the NLP server  233  transmits the control command to a control server  240 . At this time, the NLP server  233  transmits the fact that the extracted keyword does not include the control target device to the control server  240 . 
     Then, as there is no control target device in the extracted keyword, the control server  240  determines whether the received control command is a common control command or a specialized control command S 450 . At this time, the control server  240  may determine the kind of the control command based on a database in which the common control command and the specialized control command are stored. In the implementation, the control command of ‘power on’ corresponds to the common control command. Therefore, the implementation corresponds to the above-described ‘A case’. 
     Then, the control server  240  controls all products in which the speech is recognized based on the control command (S 460 ). In the implementation, both the washing machine  101  and the dryer  102  that recognize the speech of the user correspond to the speech recognition products. 
     Accordingly, the control server  240  may simultaneously transmit the control command to turn on the power to the washing machine  101  and the dryer  102 . 
     Then, the washing machine  101  and the dryer  102  may output a guide speech notifying that the power is turned on by the speech guidance unit  120 , respectively. At this time, the washing machine  101  and the dryer  102  may receive the guide speech of “power is turned on” from the control server  240 . 
     Then, the washing machine  101  and the dryer  102  transmit the guide speech to a TTS server  235 . Subsequently, the TTS server  235  converts the received guide speech into speech data and transmits the converted speech data back to the washing machine  101  and the dryer  102  S 470 . 
     Then, the washing machine  101  and the dryer  102  convert the received speech data into sound by the speech guidance unit  120  and output the converted sound. That is, the washing machine  101  and the dryer  102  may output the guide speech that “the power is turned on” through sound, respectively. 
     As a result, when the user utters the common control command, the user may learn that all home electronics that recognize the speech operate. Therefore, based on this experience, the user may simultaneously control the plurality of home electronics using the common control command as necessary. 
       FIG.  12    is a schematic view of a method for controlling speech recognition of according to a second implementation present disclosure. Hereinafter, the contents overlapping with the above implementation will be omitted, and differences will be mainly described. 
     Referring to  FIG.  12   , a home appliance  100  receives speech of a user S 510 . The home appliance  100  receives speech data of the user from a speech input  110 . Hereinafter, the case where the user utters “Hi LG, turn on the washing machine” in the balcony will be described as an example of a method for controlling the speech recognition. 
     The washing machine  101  and the dryer  102  disposed in the balcony may recognize the startup word from the speech data of the user, respectively. The startup word may be “Hi LG”. 
     Then, when the startup word is recognized, the home appliance  100  may process the contents that the user utters as a natural language command after the startup word is inputted. 
     Then, the speech data with respect to the natural language command may be transmitted to a speech recognition server system  200  S 520 . At this time, the natural language command may include speech data of “turn on the washing machine”. 
     Then, when the natural language command is received, an ASR server  231  performs a speech recognition operation on the received speech data (S 530 ). The ASR server  231  converts the received speech data into text data. The converted text data is transmitted to an NLP server  233 . 
     Then, the NLP server  233  analyzes the result of a speech recognition operation performed by the ASR server  231  S 540 . That is, the NLP server  233  extracts a keyword, i.e., a control target device or a control as an instruction, for a speech command from the received text data. At this time, among the keywords extracted from the natural language command, the control target device (TG) may be a ‘washing machine’ and the control command may be ‘power on’. 
     Then, the NLP server  233  transmits information on a control target device and a control command to a control server  240 . 
     Then, the control server  240  determines whether the control target device TG is the identical to the speech recognition product S 550 . At this time, the control target device TG may be the washing machine  101  and the speech recognition product may be the washing machine  101  and the dryer  102 . 
     With respect to the washing machine  101  that recognizes the speech of the user, the speech recognition product, i.e., the washing machine  101 , is identical to the control target device TG, i.e., the washing machine  101 . In this case, the control server  240  controls the speech recognition product, i.e., the washing machine  101 , based on the control command. That is, the washing machine  101  corresponds to the above-described ‘B case’. 
     On the other hand, with respect to the dryer  102  that recognizes the speech of the user, the speech recognition product, i.e., the dryer  102 , is different from the control target device TG, i.e., the washing machine  101 . 
     Then, when the speech recognition product is different from the control target device TG, the control server  240  determines whether the speech recognition product and the control target device TG belong to the same group. At this time, both the speech recognition product, i.e., the dryer  102 , and the control target device TG, i.e., the washing machine  101 , belong to the first group G 1 . 
     Then, when the speech recognition product and the control target device TG belong to the same group, the control server  240  controls the speech recognition product, i.e., the dryer  102 , to ignore a control command. That is, the dryer  102  corresponds to the above-described ‘C case’. 
     Then, the control server  240  controls the speech recognition product based on the control command S 560 . Accordingly, the control server  240  transmits a control command to the washing machine  101  to turn on the power. On the other hand, the control server  240  transmits an ignore command (Ignore CMD) to the dryer  102  to ignore the control command. 
     Then, the washing machine  101  outputs a guide speech notifying that the power is turned on to the user by the speech guidance unit  120 . Meanwhile, the state of the dryer  102  is converted into a standby state of the startup word without performing an additional operation. 
     At this time, the washing machine  101  may receive the guide speech of “the power is turned on” from the control server  240 . 
     Then, the washing machine  101  transmits the guide speech to a TTS server  235 . Then, the TTS server  235  converts the received guide speech into speech data, and transmits the converted speech data to the washing machine  101  S 570 . 
     Then, the washing machine  101  may convert the received speech data into sound through the speech guidance unit  120  and output the converted sound. That is, the washing machine  101  may output the guide speech of “the power is on” through speech. 
     As a result, when there are a plurality of speech recognition devices in the same space, only the device intended by the user operates based on the control command, and other home electronics may maintain the standby state. That is, the present disclosure may prevent a command conflict or mutual interference between the speech recognition devices from occurring even when there is a plurality of speech recognition products in a space where the user is disposed. 
       FIG.  13    is a schematic view of a method for controlling speech recognition according to a third implementation of the present disclosure. Hereinafter, the contents overlapping with the above implementation will be omitted, and differences will be mainly described. 
     Referring to  FIG.  13   , a home appliance  100  receives speech of a user (S 610 ). The home appliance  100  receives the speech data of the user from a speech input  110 . Hereinafter, the case where the user utters “Hi LG, turn on the power of the air conditioner” in the balcony may be described as an example of a method for controlling the speech recognition of the present disclosure. 
     A washing machine  101  and a dryer  102  disposed in the balcony recognize a startup word from the speech data, respectively. The startup word may be “Hi LG”. 
     Then, when the startup word is recognized, the home appliance  100  may process the contents that the user utters as a natural language command after the startup word is inputted. 
     Then, the speech data with respect to the natural language command may be transmitted to a speech recognition server system  200  S 620 . At this time, the natural language command may include speech data of “turn on the power of the washing machine”. 
     Then, when a natural language command is received, an ASR server  231  performs a speech recognition operation on the received speech data S 630 . The ASR server  231  converts the received speech data into text data. The converted text data is transmitted to an NLP server  233 . 
     Then, the NLP server  233  analyzes the result of a speech recognition operation performed by the ASR server  231  S 640 . That is, the NLP server  233  extracts a keyword, i.e., a control target device or a control command, for a speech command from the received text data. At this time, among the keywords extracted from the natural language command, the control target device TG may be an ‘air conditioner’ and the control command may be ‘power on’. 
     Then, the NLP server  233  transmits the control target device and the control command to a control server  240 . 
     Then, the control server  240  determines whether the control target device TG is identical to the speech recognition product S 650 . At this time, the control target device TG may be an air conditioner  103  and the speech recognition product may be the washing machine  101  and the dryer  102 . 
     Then, when the control target device TG is identical to the speech recognition product, the control server  240  controls the speech recognition product based on the control command (Case B). 
     On the other hand, when the control target device TG is different from the speech recognition product, the control server  240  determines whether the control target device TG and the speech recognition product belong to the same group. 
     Then, when the control target device TG and the speech recognition device belong to the same group, the control server  240  transmits an ignore command (Ignore CMD) to the speech recognition device (Case C). 
     On the other hand, when the control target device TG and the speech recognition device belong to different groups from each other, the control server  240  determines whether the speech recognition device is a representative device of the group. 
     Then, when the speech recognition device is the representative device of the group, the control server  240  controls the control target device TG based on the control command, i.e. case D. 
     On the other hand, when the speech recognition device is not the representative device of the group, the control server  240  transmits the ignore command (Ignore CMD) to the speech recognition device, i.e. case E. 
     In the case of the washing machine  101  that recognizes the speech of the user, the speech recognition device, i.e., the washing machine  101 , is different from the control target device TG, i.e., the air conditioner  103 . In addition, the speech recognition device, i.e., the washing machine  101 , and the control target device TG, i.e., the air conditioner  103 , belong to different groups from each other. Further, the speech recognition device, i.e., the washing machine  101 , corresponds to the representative device RP_G 1  of the group G 1 . In this case, the washing machine  101  corresponds to the above-described ‘D case’. Therefore, the control server  240  controls the control target device TG, i.e., the air conditioner  103 , based on the control command input to the washing machine  101 . 
     On the other hand, in the case of the dryer  102  that recognizes the speech of the user, the speech recognition device, i.e., the dryer  102 , is different from the control target device TG, i.e., the air conditioner  103 . Further, the speech recognition device, i.e., the dryer  102 , and the control target device TG, i.e., the air conditioner  103 , belong to different groups from each other. However, the speech recognition device, i.e., dryer  102 , is not the representative device RP_G 1  of the group G 1 . In this case, the dryer  102  corresponds to the above-mentioned ‘E case’. Accordingly, the control server  240  controls the dryer  102  to ignore the control command input thereto. 
     Subsequently, the control server  240  controls the control target device TG based on the control command S 660 . That is, the control server  240  transmits a control command to the air conditioner  103  to turn on the power. On the other hand, the control server  240  transmits the ignore command (Ignore CMD) to the dryer  102  to ignore the control command. 
     Then, the control server  240  may receive the control results for the operation of the control target device TG (i.e., the air conditioner  103 ) to the speech recognition device, i.e., the washing machine  101 . 
     At this time, the speech recognition product, that is, the washing machine  101 , may receive the guide speech of “the power of the air conditioner is turned on” from the control server  240 . 
     Then, the speech recognition device, i.e., the washing machine  101 , transmits the guide speech to a TTS server  235 . Subsequently, the TTS server  235  converts the received guide speech into speech data and transmits the converted speech data to the speech recognition product, i.e., the washing machine  101 , S 670 . 
     Then, the speech recognition device, i.e., the washing machine  101 , may convert the received speech data through sound by the speech guidance unit  120  and output the converted sound. That is, the washing machine  101  may output the guide speech of “the power of the air conditioner is turned on” through speech. 
     Thus, through the speech recognition device, the user may remotely control a control target device disposed in a space different from another space where the speech recognition device is arranged. At this time, through the speech recognition device, the control result of the control target device may be informed to the user through speech. As a result, the user may easily control the home electronics disposed in another space and confirm the control result immediately. 
       FIG.  14    is a schematic view of a method for controlling speech recognition according to a fourth implementation of the present disclosure. Hereinafter, the contents overlapping with the above implementation will be omitted, and differences will be mainly described. 
     Referring to  FIG.  14   , a home appliance  100  receives speech of a user S 710 . The home appliance  100  receives speech data of the user from a speech input  110 . Hereinafter, the case where the user utters “Hi LG, how much laundry time is left?” in the living room will be described as an example of a method for controlling the speech recognition of the present disclosure. 
     An air conditioner  103 , the robot cleaner  104 , and an air cleaner  105 , which are disposed in the living room, may recognize the startup words from the speech data of the user, respectively. The startup word may be “Hi LG”. 
     Then, when the startup word is recognized, the home appliance  100  may process the contents that the user utters as a natural language command after the startup word is inputted. 
     Subsequently, the speech data corresponding to the natural language command may be transmitted to the speech recognition server system  200  S 620 . At this time, the natural language command may include the speech data of “How much laundry time is left?”. 
     Then, when the natural language command is received, an ASR server  231  performs the speech recognition operation on the received speech data S 730 . The ASR server  231  converts the received speech data into text data. The converted text data is transmitted to the NLP server  233 . 
     Then, an NLP server  233  analyzes the result of a speech recognition operation performed by the ASR server  231  S 740 . That is, the NLP server  233  extracts the keyword, i.e., the control target device or the control command, for the speech command from the received text data. At this time, among the keywords extracted from the natural language command, the control command may be “how much laundry time is left?”. Then, the NLP server  233  transmits a control command to a control server  240 . At this time, the NLP server  233  transmits to the control server  240  that the extracted keyword has no information on the control target device. 
     Then, as there is no control target device in the extracted keyword, the control server  240  determines whether the received control command is a common control command or a specialized control command S 450 . At this time, the control server  240  may determine the kinds of control command based on a database in which the common control command and the specialized control command are stored. 
     In the implementation, the control command of “how much laundry time is left?” corresponds to the specialized control command for the washing machine  101 . As a result, based on the control command, the NLP server  233  may select the washing machine  101  as the control target device TG 
     Then, the NLP server  233  transmits information on the selected control target device TG and the control command to the control server  240 . 
     Then, the control server  240  determines whether the control target device TG is identical to the speech recognition product (S 650 ). At this time, the control target device TG may be the washing machine  101 , and the speech recognition device may be the air conditioner  103 , the robot cleaner  104 , and the air cleaner  105 . 
     At this time, when the control target device TG is identical to the speech recognition device, the control server  240  controls the speech recognition device based on the control command, i.e. Case B. 
     On the other hand, when the control target device TG is different from the speech recognition device, the control server  240  determines whether the control target device TG and the speech recognition device belong to the same group. 
     Then, when the control target device TG and the speech recognition device belong to the same group, the control server  240  transmits the ignore command (Ignore CMD) to the speech recognition device, i.e. Case C. 
     On the other hand, when the control target device TG and the speech recognition device belong to different groups from each other, the control server  240  determines whether the speech recognition device is the representative device of the group or not. 
     Then, when the speech recognition device is the representative product of the group, the control server  240  controls the control target device TG based on the control command, i.e. Case D. 
     On the other hand, when the speech recognition device is not the representative product of the group, the control server  240  transmits to ignore command (Ignore CMD) to the speech recognition device, i.e. E case. 
     In the case of the air conditioner  103  that recognizes the speech of the user, the speech recognition device, i.e., the air conditioner  103 , is different from the control target device TG, i.e., the washing machine  101 . Further, the speech recognition device, i.e., the air conditioner  103 , and the control target device TG, i.e., the washing machine  101 , belong to different groups from each other. The speech recognition device, i.e., the air conditioner  103 , corresponds to the representative product RP_G 2  of the group G 2 . In this case, the air conditioner  103  corresponds to the above-described ‘D case’. Therefore, the control server  240  controls the control target device TG, i.e., the washing machine  101 , based on the control command input to the air conditioner  103 . 
     On the other hand, in the case of a robot cleaner  104  that recognizes the speech of the user, the speech recognition device, i.e., the robot cleaner  104 , is different from the control target device TG, i.e., the washing machine  101 . Further, the speech recognition product, i.e., the robot cleaner  104 , and the control target device TG, i.e., the washing machine  101 , belong to different groups from each other. However, the speech recognition device, i.e., the robot cleaner  104 , does not correspond to the representative device RP_G 2  of the group G 2 . In this case, the robot cleaner  104  corresponds to the above-described ‘E case’. Therefore, the control server  240  controls the robot cleaner  104  to ignore the input control command. 
     In the case of the air cleaner  105  that recognizes the speech of the user, it corresponds to the above-described ‘E case’ in the same manner as the robot cleaner  104 . Thus, the control server  240  controls the air purifier  105  so as to ignore the inputted control command. 
     Subsequently, the control server  240  controls the control target device TG based on the control command S 760 . That is, the control server  240  transmits a control command to the washing machine  101  to request the remaining laundry time. On the other hand, the control server  240  transmits an ignore command (Ignore CMD) to the robot cleaner  104  and the air cleaner  105  to ignore the control command. 
     Then, the control server  240  receives information on the control result of the operation of the control target device TG, i.e., the washing machine  101 , S 765 . That is, the control server  240  receives information on the remaining laundry time of the washing machine  101 , that is, a feedback signal. 
     Then, the control server  240  transmits information on the control result for the control target device TG, i.e., the washing machine  101 , to the speech recognition product, i.e., the air conditioner  103 , S 770 . That is, the control server  240  transmits remaining time information on the washing machine  101  to the air conditioner  103 . 
     At this time, the air conditioner  103  may receive guide speech of “15 minutes are left to wash” from the control server  240 . 
     Then, the speech recognition device, i.e., the air conditioner  103 , transmits the guide speech to the TTS server  235 . Subsequently, the TTS server  235  may convert the received guide speech into the speech data and transmit the converted speech data to the speech recognition device, i.e., the air conditioner  130 , S 780 . 
     Then, the speech recognition product, i.e., the air conditioner  103 , may convert the received speech data into speech by the speech guidance unit  120  and output the converted sound. That is, the air conditioner  103  may output the guide speech of “15 minutes are left to wash” through speech. 
     Thus, the user may remotely control the control target device disposed in a space different from another space where the speech recognition device is arranged. At this time, through the speech recognition device, the user may be informed of the control result of the control target device through speech. Accordingly, the user may easily control the home electronics disposed in other spaces and may immediately confirm the control results. 
       FIG.  15    shows a speech recognition server system in communication with a user terminal.  FIG.  16    shows a group change interface of a plurality of home electronics the home appliance includes.  FIG.  17    shows an interface to set a name or nickname of a specific home electronics. 
     Referring to  FIG.  15   , a speech recognition server  230  and a control server  240  in a speech recognition server system  200  of the present disclosure may store group information on a plurality of home electronics included in a home appliance  100  and information on the representative devices of the group. The speech recognition server  230  or the control server  240  may control an operation of a control target device based on group information pre-stored in the database and information on the representative devices of the respective groups. 
     Further, the speech recognition server  230  and the control server  240  may store a name or a nickname that may identify each of home electronics included in the home appliance  100 . The speech recognition server  230  or the control server  240  may determine the control target device based on the name or nickname of the home electronics pre-stored in a database. 
     In addition, the speech recognition server  230  may store information on a specific device to which the above-mentioned specialized control command is applied. The information on relations between the specialized control command and the specific device may be stored in a form of a database. Referring to such a database, the speech recognition server  230  may determine the control target device based on the specialized control command extracted from the natural language command. 
     At this time, the speech recognition server  230  and the control server  240  may change the group information on the plurality of home electronics that are included in the home appliance  100  and the representative devices of each group through a user terminal  500 . 
     Further, the names or nicknames of home electronics may be input to the speech recognition server  230  and the control server  240  through the user terminal  500 . 
     Referring to  FIG.  16   , a user terminal  500  may provide group information on a plurality of home electronics that are included in a home appliance  100 , and an interface capable of changing a representative device of each group. 
     When the user moves the position of the home electronics, the group information has to be changed in order to perform an accurate speech recognition operation. The user terminal  500  may provide an interface through which the user may easily change the group information. Therefore, if the arrangement of home electronics is changed in the house, the user may edit group information in response to the position of the home electronics. 
     At this time, the user may change the group information by dragging respective home electronics on the interface. The user may also add or remove the group on the interface. When the space structure in the house due to moving or remodeling, and the like, the function for adding and removing these groups may be used. 
     The representative devices (RP_G 1 , RP_G 2 , RP_G 3 ) of each group may be set automatically. However, if desired by the user, the representative devices (RP_G 1 , RP_G 2 , RP_G 3 ) of each group may be designated and changed. 
     Group information changed by the user terminal  500  and the information on the representative devices of the respective groups are updated to the speech recognition server  230  and a control server  240  so as to be used. 
     Referring to  FIG.  17   , a user terminal  500  may provide an interface through which a name or a nickname that may identify the respective home electronics which are included in a home appliance  100  may be added or changed. 
     The user may issue a command with any one of a brand mane, the product name, or a nickname as a name of a speech recognition product. At this time, a speech recognition server  230  selects the control target device based on the name of the speech recognition devices. 
     At this time, the user may add the name or the nickname of each device by using the interface provided by the user terminal  500 . 
     For example, when the user presses a ‘CHANGING NICKNAME’ button on the interface provided by the user terminal  500 , a message window that may input a user-defined name to say the name of the device is displayed. 
     Then, the user may input the name or nickname of the device in the message window and store information on the inputted name or nickname of the device. 
     The name or nickname of each of home electronics added by the user terminal  500  may be updated by the speech recognition server  230  and used. At this time, the speech recognition server  230  may determine the control target device based on the updated name or nickname of the home electronics. 
     As a result, the user may control the specific device using the name or the nickname that is easy to remember. Therefore, the user convenience with respect to controlling the speech recognition device may be improved. Further, when the user utters the nickname of the device, affection of the user with respect to the product and satisfaction with the use may be improved. 
     While the present disclosure has been mainly described with regard to the implementations of the present disclosure hereinabove, various modifications and changes may be made at the level of those skilled in the art. Therefore, unless such a modification and change do not deviate the range of the present disclosure, it will understand that they are included in the scope of the present disclosure.