Patent Publication Number: US-2023139640-A1

Title: Voice recognition device and voice recognition method

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a U.S. national stage application of International Application No. PCT/JP2020/012349, filed on Mar. 19, 2020. 
    
    
     BACKGROUND 
     Technical Field 
     The present invention relates to a voice recognition device and a voice recognition method. 
     Background Information 
     A voice recognition device recognizes speech uttered by a user and performs various types of processing based on the voice recognition result. A vehicle equipment control device disclosed in Japanese Laid-Open Patent Application No. 2006-308848 (Patent Document 1) has a keyword detection means that detects keywords, which includes ambiguous words, and, insofar as possible, is able to perform voice recognition in accordance with the user&#39;s intentions, even when an instruction by speech uttered by the user is unclear. 
     SUMMARY 
     However, when a device installed in a moving body such as a vehicle is controlled by means of the vehicle equipment control device disclosed in Patent Document 1, depending on the type of device, control by means of an unclear instruction may not be suitable. 
     The problem to be solved by the present invention is to provide a voice recognition device and a voice recognition method that can identify a control request based on an instruction by means of a user&#39;s voice, in an appropriate detection mode corresponding to each control target device. 
     The voice recognition device and voice recognition method according to the present invention sets a detection mode for identifying a control request in accordance with the control target device and identifies a control request based on the set detection mode, thereby solving the problem described above. 
     By the present invention, since the detection mode can be set in accordance with the control target device, it is possible to identify a control request based on an instruction by means of a user&#39;s voice in an appropriate detection mode corresponding to each control target device. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Referring now to the attached drawings which form a part of this original disclosure. 
         FIG.  1    is a block diagram showing the configuration of a vehicle that utilizes a voice recognition device according to a first embodiment of the present invention. 
         FIG.  2    is a flowchart showing a voice recognition method that uses the voice recognition device shown in  FIG.  1   . 
         FIG.  3    is a diagram showing an example of a first detection mode target device and a second detection mode target device, which are set in advance by the voice recognition device shown in  FIG.  1   . 
         FIG.  4    is a table illustrating the difference between the voice recognition ranges of a second detection mode based on rule-based recognition and a first detection mode based on natural language recognition. 
         FIG.  5    is a block diagram showing the configuration of a vehicle that includes a voice recognition device according to a second embodiment of the present invention. 
         FIG.  6    is a block diagram showing the configuration of a vehicle that utilizes a voice recognition device according to a third embodiment of the present invention. 
         FIG.  7    is a flowchart showing the voice recognition method that uses the voice recognition device shown in  FIG.  6   . 
         FIG.  8    is a table showing misrecognition level points that are added in accordance with each vehicle state in the voice recognition method shown in  FIG.  7   . 
         FIG.  9    is a diagram showing the correspondence relationship between the control target device and the detection mode when it is determined that the sound collection environment is unfavorable in the voice recognition method shown in  FIG.  7   . 
         FIG.  10    is a flowchart showing another example of a voice recognition method that uses the voice recognition device shown in  FIG.  6   . 
     
    
    
     DETAILED DESCRIPTION OF EMBODIMENTS 
     Embodiments of the present invention will be described below based on the drawings. 
     First Embodiment 
     A voice recognition device  100  according to the first embodiment and a voice recognition method using the voice recognition device  100  will be described with reference to  FIGS.  1 - 4   . As shown in  FIG.  1   , a vehicle  1 , which is a moving body, includes the following on-board devices: an interior light  3 , an air conditioner  4 , a door windows control device  5 , a roof window control device  6 , a rear doors control device  7 , a display  12 , an audio device  13 , a navigation device  14 , a call device  15 , a travel control device  31 , headlamps  32 , seat control devices  33 , and a trunk control device  34 . Further, the vehicle  1  comprises a device control unit  11  that controls these on-board devices, a speech acquisition unit  101 , which is a microphone for inputting voiced instructions from the user, and a communication unit  107  that is connected to the device control unit  11  and the speech acquisition unit  101  by wire or wirelessly and that can communicate with a server  20  outside of the vehicle. The interior light  3 , the air conditioner  4 , and the audio device  13  are environmental control devices that adjust the ambient conditions of the interior or inside of the vehicle  1 . That is, the interior light  3  adjusts the ambient conditions that include light intensity. The air conditioner  4  adjusts the ambient conditions that include temperature. The audio device  13  adjusts the ambient conditions that include sound volume. 
     Further, the communication unit  107  of the vehicle  1  can communicate wirelessly with the server  20 . The server  20  also has a server-side communication unit (not shown) that can communicate with the communication unit  107  of the vehicle  1 . The server  20  includes a speech data conversion unit  102 , a control target device identification unit  104 , a detection mode setting unit  105 , and a control request identification unit  106 . The display  12 , the audio device  13 , the navigation device  14 , the call device  15 , the device control unit  11 , the speech acquisition unit  101 , and the communication unit  107  provided in the vehicle  1 , and the speech data conversion unit  102 , the control target device identification unit  104 , the detection mode setting unit  105 , and the control request identification unit  106  of the server  20  constitute a navigation system  10 . The navigation system  10  is, for example, an IVI system. Further, the speech acquisition unit  101  and the communication unit  107  provided in the vehicle  1 , and the speech data conversion unit  102 , the control target device identification unit  104 , the detection mode setting unit  105 , and the control request identification unit  106  of the server  20  constitute the voice recognition device  100 . That is, the voice recognition device  100  constitutes a part of the navigation system  10 . Further, the voice recognition device  100  receives voiced instructions from the user and controls one or more or all of the on-board devices via the device control unit  11 . That is, the navigation system  10  has the voice recognition device  100  that receives a request to control various types of devices installed in the vehicle  1  based on voiced instructions from a user in the vehicle  1 . The voice recognition device  100  is a voice recognition system. 
     As shown in  FIG.  3   , the door windows control device  5  includes a door windows locking device  5   a  and a door windows opening/closing device  5   b . The roof window control device  6  includes a roof window locking device  6   a  and a roof window opening/closing device  6   b . The rear doors control device  7  includes a rear doors locking device  7   a  and a rear doors opening/closing device  7   b . The trunk control device  34  includes a trunk locking device  34   a  and a trunk opening/closing device  34   b.    
     Further, the seat control devices  33  control the various functions of a seat provided in the interior of the vehicle  1  and include a seat massage device  33   a , a seat heater  33   b , and a seat position adjustment device  33   c . The seat position adjustment device  33   c  can adjust the seat height, the front-rear seat position, and the seat backrest angle. 
     Further, the travel control device  31  shown in  FIG.  1    controls the travel of the vehicle  1  when autonomous driving mode is selected as the travel mode of the vehicle  1 . Specifically, the travel control device  31  controls a drive actuator, a steering actuator, and a brake actuator of the vehicle  1 . 
     The display  12  is a touch panel display equipped with an input function that allows the user to input control instructions to the audio device  13 , the navigation device  14 , the call device  15 , and other on-board devices by means of touch operations. Further, the display  12  can output information regarding incoming calls to the call device  15 , information regarding callers speaking via the call device  15 , and guidance information from the navigation device  14 , and the like, as images that include text information and icons. Further, the audio device  13  can output audio that reports incoming calls to the call device  15 , audio of the called party speaking through the call device  15 , audio providing guidance information from the navigation device  14 , and the like. The display  12  is not limited to a touch panel display with an input function, but may be any device that outputs 2D or 3D images that include text information. Further, the display  12  is not limited to a display provided in the dashboard of the vehicle  1 , but may also be a windshield projection heads-up display or various other displays. The display  12  and the audio device  13  constitute an information provision device. 
     The speech data conversion unit  102  of the server  20  receives information the speech acquired by the speech acquisition unit  101  via the communication unit  107  and converts the information to speech data. Speech data are speech-based text data. 
     Further, the control target device identification unit  104  of the server  20  analyzes the speech data converted by the speech data conversion unit  102  and identifies the control target device to be operated from keywords included in the speech data. A control target device is one or more of the following on-board devices, for example: the interior light  3 , air conditioner  4 , the door windows control device  5 , the roof window control device  6 , the rear doors control device  7 , the display  12 , the audio device  13 , the navigation device  14 , the call device  15 , the travel control device  31 , the headlamps  32 , the seat control devices  33 , and the trunk control device  34 . When identifying a control request, the control target device identification unit  104  refers to dictionary data and context data stored in the server  20 . Further, depending on the control target device, the control target device identification unit  104  pre-sets each control target device as a first detection mode target device or a second detection mode target device. The control target device identification unit  104  refers to target device information, in which each control target device is pre-set as a first detection mode target device or a second detection mode target device, in order to determine whether the identified control target device is the first or the second detection mode target device. The first detection mode target device is a device for which a first detection mode based on natural language recognition, described further below, is to be used, when a control request is identified. The second detection mode target device is a device for which a second detection mode based on rule-based recognition, described further below, is to be used, when a control request is identified. Information indicating whether the “control target device is the first or the second detection mode target device,” as determined by the control target device identification unit  104  (hereinafter also referred to as determination information), is then output to the display  12  and/or the audio device  13  via the communication unit  107  or the device control unit  11  on the vehicle  1  side. That is, the determination information indicating whether the identified control target device is the first detection mode target device or the second detection mode target device is displayed on the display  12  as an image that includes video or text, or output as audio by the audio device  13 . Further, the determination information of the control target device set by the control target device identification unit  104  is output to the detection mode setting unit  105 . 
     The detection mode setting unit  105  sets a detection mode for identifying the control request corresponding to the speech data converted by the speech data conversion unit  102  in accordance with the determination information of the control target device determined by the control target device identification unit  104 . Specifically, the detection mode setting unit  105  sets the detection mode to either a first detection mode based on the natural language recognition, described further below, or a second mode based on rule-based recognition, described further below, in accordance with the determination information of the control target device. The detection mode information set by the detection mode setting unit  105  is output to the display  12  and/or the audio device  13  via the communication unit  107  and the device control unit  11  on the vehicle  1  side. That is, information indicating whether the current detection mode is set to the first detection mode or the second detection mode (hereinafter also referred to as “detection mode setting information”) is displayed on the display  12  as an image including video or text, or output as audio by the audio device  13 . Further, the detection mode setting information indicating the detection mode set by the detection mode setting unit  105  is output to the control request identification unit  106 . 
     The control request identification unit  106  analyzes the speech data converted by the speech data conversion unit  102  and identifies the contents of the control request with respect to the control target device based on the detection mode set by the detection mode setting unit  105 . In a similar manner to the control target device identification unit  104 , the control request identification unit  106  refers to dictionary data and context data stored in the server  20  when identifying a control request. The control request identification unit  106  then transmits the contents of the control request with respect to the identified control target device to the device control unit  11  via the communication unit  107  on the vehicle  1  side. The device control unit  11  controls the control target device based on the contents of the control request with respect to the control target device and the received information regarding the control target device. 
     Next, the procedure of the voice recognition method by means of the voice recognition device  100  will be described using the flowchart shown in  FIG.  2   . 
     First, in Step S1, the speech acquisition unit  101  of the voice recognition device  100  on the vehicle  1  side acquires speech uttered by the user. Specifically, the speech acquisition unit  101  detects that the user has spoken based on frequency, and, when the user&#39;s speech is detected, acquires speech information containing speech uttered by the user as the voice recognition target. In this manner, as a result of the speech acquisition unit  101  acquiring speech information only when the user is speaking, the control load on the voice recognition device  100  can be reduced compared with the case in which speech information is constantly acquired. Further, if a specific keyword indicating the start of a voiced instruction is set in advance, the speech acquisition unit  101  may acquire speech information as the voice recognition target immediately after the user utters the specific keyword. 
     Next, in Step S2, the speech data conversion unit  102  of the voice recognition device  100  on the server  20  side converts the acquired speech into speech data that can be recognized as text. 
     Next, in Step S3, the control target device identification unit  104  analyzes the speech data converted by the speech data conversion unit  102  and identifies the target device to be controlled. The control target device identification unit  104  analyzes the speech data by means of natural language recognition to identify the control target device. Specifically, if the user voices “open the roof window,” the control target device identification unit  104  refers to the dictionary data and the context data to identify the control target device as the roof window opening/closing device  6   b . Further, even if the user utters a spoken instruction such as “open the upper window,” “open the roof,” or the like, the control target device identification unit  104  determines that the “upper window” or “roof” in this case means the roof window and identifies the control target device as the roof window opening/closing device  6   b . That is, the control target device identification unit  104  is able to identify the control target device even if the user&#39;s voiced speech data do not match the predefined control request text. 
     Next, in Step S4, the control target device identification unit  104  determines whether the control target device identified in Step S3 is a first detection mode target device. Here, the method for determining whether the control target device is a first detection mode target device, or a second detection mode target device and not a first detection mode target device, will be described with reference to  FIG.  3   . 
     In the example shown in  FIG.  3   , the on-board devices of the vehicle  1  are preliminarily divided into three categories in accordance with their operational importance. The operational importance is the degree to which the control of the on-board device affects the driving conditions of the vehicle  1  or the user riding in the vehicle  1 . Thus, since an on-board device with a higher operational importance has a greater effect on the way the vehicle  1  is being driven, there is a greater demand to bring the probability of misrecognition of the control request as close to zero as possible. That is, the higher the operational importance of a control target device, the more the more accurately and reliably must the control request identified by the voice recognition device  100  match the actual voiced instruction of the user. 
     Specifically, the navigation device  14 , the call device  15 , the audio device  13 , the display  12 , and interior light  3 , the air conditioner  4 , the seat massage device  33   a , and the seat heater  33   b  are classified under operational importance category “1 (Low).” These accessory devices are thought to have little effect on the driving, and thus are classified as having the lowest operational importance. On the other hand, the seat position adjustment device  33   c  is classified under operational importance category “2 (Medium).” That is, the position and height of the seat in which the user is seated can affect the user&#39;s driving of the vehicle  1 , so that the seat position adjustment device  33   c  has greater operational importance than the seat massage device  33   a  and the seat heater  33   b . Further, the travel control device  31 , the headlamps  32 , the door windows locking device  5   a , the door windows opening/closing device  5   b , the roof window locking device  6   a , the roof window opening/closing device  6   b , the rear doors locking device  7   a , the rear doors opening/closing device  7   b , the trunk locking device  34   a , and the trunk opening/closing device  34   b  have a significantly large impact on the user and the driving of the vehicle  1 , and thus are classified under operational importance category “3 (High).” The control target device identification unit  104  determines the on-board devices classified into the “1 (Low)” operational importance category and the on-board devices classified into the “2 (Medium)” operational importance category as first detection mode target devices. Further, the control target device identification unit  104 , determines the on-board devices classified into the “3 (High)” operational importance category as second detection mode target devices. 
     The distinction between a first detection mode target device and a second detection mode target device is preset for each on-board device, but the control target device identification unit  104  can change the setting of the first detection mode target device and the second detection mode target device as deemed necessary. 
     Next, as shown in  FIG.  2   , in Step S4, if it is determined that the control target device is a first detection mode target device, then in Step S5, the detection mode setting unit  105  sets the detection mode to the first detection mode. Then, in Step S6, the control request identification unit  106  determines whether the contents of the user&#39;s instruction can be read from the speech data converted in Step S2 by means of natural language recognition. Whether the contents of the instruction can be read is determined based on whether the control request identification unit  106  is able to interpret the speech data converted by the speech data conversion unit  102  based on natural language recognition with reference to the dictionary data and the context data and thus identify the contents of the control request. If the instruction cannot be read from the speech data, in Step S12, the voice recognition device  100  asks the user to repeat the instruction. This is presented to the user as an image containing text on the display  12  or by the audio device  13  providing voiced guidance. On the other hand, if the instruction contents can be read from the speech data, in Step S7 the control request identification unit  106  identifies the control request with respect to the control target device. That is, the control request identification unit  106  interprets the speech data converted by the speech data conversion unit  102  based on natural language recognition with reference to the dictionary data and the context data and thus identifies the contents of the control request. In Step S11, the identified control request is transmitted to the device control unit  11  of the vehicle  1  in order to control the control target device, and the process comes to an end. 
     In Step S4, if it is determined that the control target device is not a first detection mode target device, that is, if it is determined that the control target device is a second detection mode target device, in Step S8 the detection mode setting unit  105  sets the detection mode to the second detection mode. Then, in Step S9, it is determined whether the speech data converted in Step S2 match a predefined control request text; if not, in Step S12, the user is asked to repeat the instruction. Asking the user to repeat the instruction is a process of proposing or requesting that the user redo the voiced input (utterance of an instruction). At this time, the control request identification unit  106  outputs to the display  12  or the audio device  13 , via the communication unit  107  and the device control unit  11  of the vehicle  1 , information guiding the user to redo the instruction (voiced input/utterance) so that the speech data will match the control request text. 
     On the other hand, if the speech data match the control request text, in Step S10 the control request identification unit  106  identifies the control request corresponding to the control request text by means of the second detection mode based on rule-based recognition. In Step S11, the identified control request is transmitted to the device control unit  11 , via the communication unit  107  of the vehicle  1 , to control the control target device, and the flow ends. 
     The determination of whether the speech data in the rule-based recognition match the control request text is executed by comparing the control request text with all of the speech data (text data) based on the speech input in Step S1. All of the speech data are based on speech that is input from the beginning to the end of the utterance. That is, the control request identification unit determines whether the control request text matches the speech data based on the series of voiced sounds from beginning to end of the utterance. 
     Here, the difference between the first detection mode based on natural language recognition and the second detection mode based on rule-based recognition will be described using  FIG.  4   .  FIG.  4    shows the difference between the first detection mode and the second detection mode in a case in which the control target device is an air conditioner and the contents of the control request is “I want to turn ON the air conditioner.” In the example shown in  FIG.  3   , the air conditioner  4  is specified as the first detection mode target device, but in the example shown in  FIG.  4   , for convenience of the explanation, either the first detection mode or the second detection mode may be applied for the identification of the control request to the air conditioner  4 . 
     As shown in  FIG.  4   , if the control target device is an air conditioner and the contents of the control request is “I want to turn ON the air conditioner,” the control request text corresponding to the contents of this control request is predefined as “turn on the air conditioner.” 
     In the second detection mode based on rule-based recognition, if it is determined that the speech data based on speech uttered by the user match the control request text, the control request with respect to the air conditioner, which is the control target device, is identified (refer to  FIG.  2   , Step S10). That is, in the example shown in  FIG.  4   , in the case that the detection mode setting unit  105  sets the detection mode to the second detection mode, the device control unit  11  turns the power to the air conditioner  4  ON only when the user utters “turn on the air conditioner” in accordance with the defined control request text. Therefore, if the user voices an utterance that does not match a control request text, for example “power on the air conditioner,” “well, I want to turn on the air conditioner,” or “it will get cold if the air conditioner is turned on,” the device control unit  11  does not turn ON the power to the air conditioner  4 , and maintains the OFF state. 
     In the first detection mode based on natural language recognition, even in a case that the user utters something different than “turn on the air conditioner,” which is the control request text, the device control unit  11  turns the power to the air conditioner  4  ON when the user utters “power on the air conditioner” or “well, I want to turn on the air conditioner,” for example. Specifically, if the user utters “power on the air conditioner,” the control request identification unit  106  separates the speech data into “air conditioner” and “power on,” refers to the dictionary data, and determines that “power on” is a synonym for “turn on,” thereby identifying the control request “I want to turn ON the air conditioner.” In the dictionary data used in the first detection mode, one registered word and another word having the same meaning and content as this word are stored in association with each other as synonyms. Further, if the user utters “well, I want to turn on the air conditioner,” the control request identification unit  106  determines that “well” is an interjection, and thus a word that has no meaning, and that “well, I want to turn on the air conditioner” is speech data that have the same meaning as the request “turn on the air conditioner.” The control request identification unit  106  thereby identifies the control request “I want to turn ON the air conditioner” based on the speech data “well, I want to turn on the air conditioner.” 
     In other words, the range of speech data that can be recognized for each control request is narrower in the second detection mode based on rule-based recognition than in the first detection mode based on natural language recognition. That is, since the second detection mode based on rule-based recognition identifies only control requests for which the control request text is defined, the range of the speech data that can specify the contents of the control request is limited in accordance with the number of the defined control requests. Further, since the second detection mode based on rule-based recognition identifies only control requests that match a defined control request text, the speech data that can be identified in the second detection mode (that can be input in the second detection mode) are limited. That is, when the detection mode is set to the second detection mode, the degree of flexibility of voiced input will be lower than when the detection mode is set to the first detection mode. Therefore, the conditions for identifying the control request are stricter in the second detection mode than in the first detection mode. 
     In other words, the first detection mode based on natural language recognition has a wider range of speech data that can be recognized in accordance with each control target device and control request than the second detection mode based on rule-based recognition. That is, the conditions for identifying the control target device and the control request are more relaxed in the first detection mode than in the second detection mode. 
     On the other hand, if the user utters “it will get cold if the air conditioner is turned on,” the control request identification unit  106  analyzes the combination of words and their order in accordance with the dictionary data and the context data, and infers that the user&#39;s voiced instruction means “if the air conditioner is turned ON, the interior temperature of the vehicle will fall below a suitable temperature, so I do not want to turn ON the air conditioner.” Therefore, the control request identification unit  106  does not transmit an instruction to turn ON the air conditioner  4  to the device control unit  11  of the vehicle  1 . That is, if the user utters “it will get cold if the air conditioner is turned on,” the power to the air conditioner  4  is kept in the OFF state and is not turned ON regardless of whether the detection mode is set to the first detection mode or the second detection mode. 
     The control request identification unit  106  of the voice recognition device  100  can learn the pattern of correspondence between the speech data and the contents of the user&#39;s actual instructions, and periodically update the dictionary data and the context data. 
     From the foregoing, the voice recognition device  100  and the voice recognition method using the voice recognition device  100  according to the present embodiment set a detection mode for identifying a control request corresponding to the speech data in accordance with the control target device and identify a control request based on the set detection mode. Therefore, the voice recognition device  100  is able to identify the control request based on the user&#39;s voiced instruction in a suitable detection mode corresponding to each control target device. 
     Furthermore, the voice recognition device  100  sets the detection mode to the first detection mode that analyzes the speech data by means of natural language recognition when the identified control target device is a first detection mode target device, and sets the detection mode to the second detection mode that analyzes the speech data by means of voice recognition of a means different from natural language recognition when the identified control target device is a second detection mode target device. That is, in accordance with the control target device, the voice recognition device  100  can set the detection mode to either the first detection mode that uses natural language recognition or the second detection mode that uses voice recognition of a means different from natural language recognition. Further, the second detection mode has a narrower and more limited range of speech data that can be recognized in accordance with each control request than the first detection mode. Therefore, depending on the control target device, the voice recognition device  100  can use the first detection mode based on natural language recognition, which accepts ambiguous voiced instructions (instructions with a high degree of flexibility), or the second detection mode based on voice recognition, which is less flexible but more accurate than natural language recognition. When speech data using natural language recognition are analyzed, the number of target words to be recognized by the control request identification unit  106  may increase, and the speech data may contain words that have multiple meanings. Therefore, if the detection mode is set to the first detection mode, the probability of misrecognition of the control request is higher than when the detection mode is set to the second detection mode. Thus, for example, when a control instruction is issued with respect to a control target device that has high operational importance and for which an ambiguous voiced instruction is not suitable, the voice recognition device  100  can select the second detection mode as the detection mode to be used, which is expected to carry out highly accurate voice recognition. On the other hand, when a control instruction is issued with respect to a control target device whose operational importance is not very high, the voice recognition device  100  can select the first detection mode, which has a wide range of voice recognition, and a high degree of flexibility of speech that can be input. 
     Further, if the detection mode is set to the second detection mode, the voice recognition device  100  determines whether the speech data match a predefined control request text. Then, if it is determined that the speech data match the control request text, the voice recognition device  100  identifies the control request corresponding to the control request text. That is, the second detection mode is a detection mode for analyzing the speech data by means of rule-based recognition. Therefore, for example, when a control request is identified with respect to the control target device that has a high operational importance and for which voice recognition by means of natural language recognition is not suitable, the voice recognition device  100  can select the second detection mode for analyzing speech data by means of rule-based recognition. Thus, when a control request is identified with respect to the control target device for which voice recognition by means of natural language recognition is not suitable, the voice recognition device  100  can improve the degree of certainty of voice recognition and prevent misrecognition of the user&#39;s voiced instruction. 
     Further, when the second detection mode is set and the speech data based on a voiced instruction do not match the control request text, the voice recognition device  100  guides the user to redo the voiced instruction. As a result, if the detection mode is set to the second detection mode, the voice recognition device  100  can prompt the user to voice an instruction in a manner that enables rule-based recognition. 
     Further, when the control target device is identified to be the travel control device  31  for controlling the travel of the vehicle  1 , the control target device identification unit  104  determines that the control target device is a second detection mode target device. Since the control of the drive actuator, steering actuator, or brake actuator of the vehicle  1  by the travel control device  31  significantly affects the travel state of the vehicle  1 , the operational importance of the travel control device  31  is particularly high. Therefore, when the control target device identification unit  104  determines that the travel control device  31  is a second detection mode target device, the control request identification unit  106  can reliably and accurately identify the control request with respect to the travel control device  31 . Thus, the stability of the travel state of the vehicle  1  is maintained. 
     Further, when the control target device is identified to be the locking device of a door, window, or the trunk, or the opening/closing device of a door, window, or the trunk of the vehicle  1 , the control target device identification unit  104  determines that the control target device is a second detection mode target device. That is, the control target device identification unit  104  pre-sets the door windows locking device  5   a , the door windows opening/closing device  5   b , the roof window locking device  6   a , the roof window opening/closing device  6   b , the rear doors locking device  7   a , the rear doors opening/closing device  7   b , the trunk locking device  34   a , and the trunk opening/closing device  34   b  as second detection mode target devices. Whether a door, window, or the trunk of the vehicle  1  is locked, and whether a door, window, or the trunk is open have a great effect on the travel state of the vehicle  1  as well as on the user in the vehicle  1 . Thus, the operational importance of the door windows locking device  5   a , the door windows opening/closing device  5   b , the roof window locking device  6   a , the roof window opening/closing device  6   b , the rear doors locking device  7   a , the rear doors opening/closing device  7   b , the trunk locking device  34   a , and the trunk opening/closing device  34   b  is particularly high. When the control target device identification unit  104  determines that these locking devices and opening/closing devices are second detection mode target devices, the control request identification unit  106  can reliably and accurately identify the control request with respect to the door windows control device  5 , the roof window control device  6 , the rear doors control device  7 , and the trunk control device  34 . Thus, the stability of the travel state of the vehicle  1  is maintained. 
     When the control target device is identified to be an environment adjustment device that adjusts the environmental conditions including at least one of the temperature, light intensity, and sound volume inside the vehicle  1 , that is, the interior light  3 , the air conditioner  4 , or the audio device  13 , the control target device identification unit  104  determines that the control target device is a first detection mode target device. The interior light  3 , the air conditioner  4 , and the audio device  13  have lesser effects on the user and the travel state of the vehicle  1  than the travel control device  31  or a locking device or an opening/closing device of doors, etc. As a result, as shown in  FIG.  3   , the operational importance of the interior light  3 , the air conditioner  4 , and the audio device  13  is “1 (Low).” Therefore, when the control target device identification unit  104  determines that the interior light  3 , the air conditioner  4 , or the audio device  13  is a first detection mode target device, the control request identification unit  106  can use the first detection mode, which has a high degree of flexibility of speech that can be input, to identify the control requests to these devices. The user can thus issue instructions to control the ON/OFF of the interior light  3 , the air conditioner  4 , or the audio device  13 , or to control the light intensity of the interior light  3 , or the air volume of the air conditioner  4 , or to set the volume of the audio device  13  more intuitively, by using a variety of patterns of speech. 
     When the control target device is identified as the seat control device  33  for controlling the state of a seat in the vehicle  1 , that is, as the seat massage device  33   a , the seat heater  33   b , or the seat position adjustment device  33   c , the control target device identification unit  104  determines that the control target device is a first detection mode target device. The seat control devices  33  have a lesser effect on the user and the travel state of the vehicle  1  than the travel control device  31  or a locking device or an opening/closing device for doors, etc. Thus, as shown in  FIG.  3   , the operational importance of the seat massage device  33   a , and the seat heater  33   b  is “1 (Low),” and the operational importance of the seat position adjustment device  33   c  is “2 (Medium).” Therefore, when the control target device identification unit  104  determines that the seat massage device  33   a , the seat heater  33   b , or the seat position adjustment device  33   c  is a first detection mode target device, the control request identification unit  106  can use the first detection mode, which that has a high degree of flexibility of speech that can be input, to identify the control request of each of the seat control devices  33 . The user can thus issue an instruction to control more intuitively the switching of the massage strength of the seat massage device  33   a , the temperature of the seat surface heated by the seat heater  33   b , or the height, position, etc., of the seat adjusted by the seat position adjustment device  33   c  by using a variety of patterns of speech (speech with high degree of flexibility). 
     When the control target device is identified as an information provision device for providing information to the user, that is, as the display  12  or the audio device  13 , the control target device identification unit  104  determines that the control target device is a first detection mode target device. The display  12  and the audio device  13  have lesser effects on the user and the travel state of the vehicle  1  than the travel control device  31  or a locking device or opening/closing device for doors, etc. As a result, as shown in  FIG.  3   , the operational importance of the display  12  and the audio device  13  is “1 (Low).” Therefore, when the control target device identification unit  104  determines that the display  12  or the audio device  13  is a first detection mode target device, the control request identification unit  106  can use the first detection mode, which has a high degree of flexibility of speech that can be input, to identify the control request. The user can thus more intuitively issue instructions to control the ON/OFF of the display  12  or the audio device  13 , or to control the brightness of the screen or the size of the text of the display  12 , or to set the volume of the audio device  13  by using a variety of patterns of speech. 
     The audio device  13  is an environment adjustment device that adjusts the environmental conditions of the interior of the vehicle  1  as well as an information provision device. Further, the information provision device is not limited to the display  12  or the audio device  13 , but may include a meter panel (not shown), or the like. 
     Further, the control target device identification unit  104  analyzes the speech data based on natural language recognition to identify the control target device in Step S3 shown in  FIG.  2   . As a result, the control target device identification unit  104  can identify the control target device even if the user voices an instruction in a manner that does not match the control request text. 
     In this embodiment, the speech data conversion unit  102 , the control target device identification unit  104 , the detection mode setting unit  105 , and the control request identification unit  106  are provided in the server  20 , but some of these functions may be provided in the vehicle  1 . 
     Second Embodiment 
     The configuration of the vehicle  1  including a voice recognition device  200  according to a second embodiment is shown in  FIG.  5   . In the following description, the same reference numerals as those shown in  FIGS.  1 - 4    indicate the same or similar constituent elements or steps, so that their detailed explanations have been omitted. As shown in  FIG.  5   , the vehicle  1  has a navigation system  110  that controls one or more or all of the display  12 , the audio device  13 , the navigation device  14 , and the call device  15  by means of voiced input. The navigation system  110  has the voice recognition device  200 , which receives requests to control various types of devices installed in the vehicle  1  based on instructions voiced by the user in the vehicle  1 . The speech acquisition unit  101 , the speech data conversion unit  102 , the control target device identification unit  104 , the detection mode setting unit  105 , the control request identification unit  106 , and the communication unit  107  constituting the voice recognition device  200  are all provided in the vehicle  1 . The detection mode setting unit  105  and the control request identification unit  106  can exchange data or signals with the device control unit  11  via the communication unit  107 . The voice recognition device  200  identifies a control request with respect to the control target device by means of the same procedure as the voice recognition method shown in  FIG.  2   . 
     As described above, similarly to the speech recognizer  100  of the first embodiment, the speech recognizer  200  of this embodiment sets a detection mode for identifying control requests corresponding to speech data according to the control target device and identifies control requests based on the set detection mode. Therefore, like the voice recognition device  100 , the voice recognition device  200  is able to identify a control request based on the user&#39;s voiced instructions in a detection mode suitable for each control target device. Further, since the voice recognition device  200  is installed in the vehicle  1 , control requests based on the user&#39;s voiced instructions suitable for each control target device can be identified regardless of the communication environment. 
     Third Embodiment 
     A voice recognition device  300  according to a third embodiment and a voice recognition method using the voice recognition device  300  will be described with reference to  FIGS.  6 - 10   . As shown in  FIG.  6   , the server  20  has a sound collection environment determination unit  108 . The sound collection environment determination unit  108  determines whether the sound collection environment for the acquisition of speech by the speech acquisition unit  101  is favorable. Further, the vehicle  1  has a vehicle speed sensor  2  that detects the travel speed of the vehicle  1 . The vehicle speed sensor  2  detects the travel speed of the vehicle  1  from the rotational speed of the wheels (wheel speed) of the vehicle  1 , for example. Further, the vehicle  1  has a wind speed sensor  8  that detects the wind speed around the vehicle  1 . Further, the vehicle  1  is provided with a vehicle information acquisition unit  103  that acquires state information of the vehicle  1 . The vehicle information acquisition unit  103  is connected to the vehicle speed sensor  2  and the wind speed sensor  8  by wire or wirelessly. Further, the vehicle information acquisition unit  103  is also connected to the speech acquisition unit  101  and the communication unit  107  by wire or wirelessly. The vehicle information acquisition unit  103  constitutes a moving body information acquisition unit. 
     The display  12 , the audio device  13 , the navigation device  14 , the call device  15 , the device control unit  11 , the speech acquisition unit  101 , the vehicle information acquisition unit  103 , and the communication unit  107  provided in the vehicle  1 , and the sound collection environment determination unit  108 , the speech data conversion unit  102 , the control target device identification unit  104 , the detection mode setting unit  105 , and the control request identification unit  106  of the server  20 , constitute a navigation system  210 . Further, the speech acquisition unit  101 , the vehicle information acquisition unit  103 , and the communication unit  107  provided in the vehicle  1 , and the sound collection environment determination unit  108 , the speech data conversion unit  102 , the control target device identification unit  104 , the detection mode setting unit  105 , and the control request identification unit  106  of the server  20  constitute the voice recognition device  300 . That is, the voice recognition device  300  constitutes a part of the navigation system  210 . Further, the voice recognition device  300  receives instructions voiced by the user and controls one or more or all of the on-board devices via the device control unit  11 . That is, the navigation system  210  has the voice recognition device  1  that receives a request to control various types of devices installed in the vehicle  300  based on instructions voiced by the user in the vehicle  1 . The voice recognition device  300  is a voice recognition system. 
     Here, the vehicle information acquisition unit  103  acquires state information of the vehicle  1  via the vehicle speed sensor  2 , the wind speed sensor  8 , the speech acquisition unit  101 , and the communication unit  107 . The state information of the vehicle  1  relates to elements that affect the acoustic environment of the interior of the vehicle  1 . For example, the state information of the vehicle  1  includes the noise level of the interior of the vehicle  1 ; information regarding the open or closed state of openings, such as the door windows, the roof window, or the rear doors; the travel speed of the vehicle  1 ; the wind speed around the vehicle  1 ; the volume setting of the audio device  13 ; the air volume emitted from the air conditioner  4 ; and the like. The noise level of the interior of the vehicle  1  is the loudness of the noise detected by the speech acquisition unit  101 , that is, the magnitude (e.g., measured value) of the sound other than that of the user&#39;s voice, and is calculated in units of dB (decibels). Further, the vehicle information acquisition unit  103  acquires, via the communication unit  107  and the device control unit  11 , the volume setting of the audio device  13 , the air volume emitted from the air conditioner  4 , information regarding the open or closed state of the door windows, the roof window, the rear doors, and the like, as the state information of the vehicle  1 . Further, the vehicle information acquisition unit  103  can also calculate the noise level of, for example, the interior of the vehicle  1  based on the magnitude of the noise in the interior of the vehicle  1  and the volume setting of the audio device  13 , to acquire the calculated noise level as state information of the vehicle  1 . Specifically, the noise level is calculated by summing the number of points assigned according to the loudness of the noise in the interior of the vehicle  1  and the number of points assigned according to the volume setting of the audio equipment  13 . The noise level may be calculated using a value measured by a microphone provided in the interior of the vehicle  1 , or be calculated using a value calculated by a microphone or vibration sensors provided on the body of the vehicle  1 . 
     The sound collection environment determination unit  108  provided in the server  20  determines whether the sound collection environment of the interior of the vehicle  1  is favorable based on the state information of the vehicle  1  acquired by the vehicle information acquisition unit  103 . The sound collection environment of the interior of the vehicle  1  is the environment in which the speech acquisition unit  101  of the voice recognition device  300  acquires the speech voiced by the user. The better the sound collection environment in the interior of the vehicle  1 , the less noise (sounds other than those of the user&#39;s voice) is included in the speech acquired by the speech acquisition unit  101 , and the more likely the voice recognition device  300  will accurately recognize the user&#39;s voiced instructions. On the other hand, the worse the sound collection environment in the interior of the vehicle  1 , the more noise is included in the speech acquired by the speech acquisition unit  101 , and the more likely the voice recognition device  300  will incorrectly identify, that is, misrecognize, the user&#39;s voiced instruction. The process of recognizing the user&#39;s voiced instructions includes the process of identifying the target device to be controlled and/or the process of identifying the contents of a control request with respect to the control target device. 
     Next, the procedure of the voice recognition method by means of the voice recognition device  300  will be described using the flowchart shown in  FIG.  7   . As shown in  FIG.  7   , if it is determined in Step S4 that the control target device is a first detection mode target device, in Step S13, the vehicle information acquisition unit  103  acquires the state information of the moving body, that is, the state information of the vehicle. Then, in Step S14, the sound collection environment determination unit  108  determines, based on the vehicle state information, whether the sound collection environment is favorable or unfavorable. The process of Step S13 may be executed in parallel with the processes of Step S1 to S4. The process of Step S13 may be performed continuously or periodically after the start of this control procedure. Further, the vehicle information acquisition unit  103  may continuously or periodically acquire the vehicle state information before this control procedure is started, and in the process of Step S13, extract and acquire the vehicle state information after the speech acquisition from the state information that was continuously or periodically acquired beforehand. 
     The criteria for determining whether the sound collection environment is favorable or unfavorable based on the vehicle state information will be explained here with reference to  FIG.  8   . Whether the sound collection environment is favorable or unfavorable is determined by a misrecognition level based on the state information of the vehicle  1 . The misrecognition level is an index indicating the probability that the voice recognition device  300  cannot accurately recognize the speech voiced by the user and cannot identify the correct control request. In the example shown in  FIG.  8   , the misrecognition level is expressed as a quantitative index value. That is, the higher the index value of the misrecognition level, the greater the probability that the user&#39;s voiced instruction will be misrecognized due to the high noise level in the interior of the vehicle  1  and the increased inability of the speech data conversion unit  102  to accurately convert speech into speech data. Therefore, the higher the index value of the misrecognition level, the less favorable the sound collection environment. In the table shown in  FIG.  8   , the number of points to be added to the misrecognition level (index value) are defined in accordance with the state information of the vehicle  1 .  FIG.  8    shows an example of the method for calculating the misrecognition level; the number of points to be added and the items that can be added can be defined in advance in accordance with the vehicle characteristics, the characteristics of the voice recognition device, or the like. 
     As shown in  FIG.  8   , the number of points to be added to the misidentification level when the roof window W  1  or door window W  2  of vehicle  1  is open is one. Further, when the air volume of the air conditioner  4  is greater than or equal to a preset reference air volume set, the number of points to be added is two. Further, when the roof window W 1  or the door window W 2  is open, and the travel speed of the vehicle  1  is greater than or equal to 20 km/h or less than 80 km/h, the number of points to be added to the misrecognition level is two. Further, when the roof window W 1  or the door window W 2  is open, and the travel speed of the vehicle  1  is greater than or equal to 80 km/h, the number of points to be added to the misrecognition level is three. Further, when the noise level of the interior of the vehicle  1  is greater than or equal to a preset reference noise level, the number of points to be added to the misrecognition level is three. The roof window W 1  and the door window W 2  of the vehicle  1  constitute the openings of the vehicle  1 . The openings of the vehicle  1  are not limited to the roof window W 1  or the door window W 2 , but may be, for example, a door of the vehicle  1 . 
     The misrecognition level (index value) of the sound collection environment is calculated by adding the number of points shown on the right side of the table of  FIG.  8    in accordance with the state information of the vehicle  1 . For example, when the roof window W 1  is open and the vehicle speed is greater than or equal to 20 km/h and less than 80 km/h, the number of points indicating the misrecognition level is calculated as three points by adding one point and two points. Further, when the roof window W 1  is open, the air conditioner air volume is greater than or equal to the reference air volume, and the vehicle speed is greater than or equal to 80 km/h, the number of points indicating the misrecognition level is calculated as six points by adding one, two, and three points. 
     In Step S14, the sound collection environment determination unit  108  sets the reference level of the misrecognition level to four points, determines that the sound collection environment is favorable when the misrecognition level is less than the reference level of four points, and determines that the sound collection environment is unfavorable when the misrecognition level is greater than or equal to four points. The number of points of the reference level can be defined in advance in accordance with the characteristics, etc., of the voice recognition device. Further, the number of points of the reference level can be defined in advance based on experiments or simulations. 
     In Step S14, if it is determined that the sound collection environment is favorable, in Step S5 the detection mode setting unit  105  sets the detection mode to the first detection mode. That is, if the sound collection environment determination unit  108  determines that the sound collection environment is favorable and the control target device identification unit  104  determines that the control target device is a first detection mode target device, the detection mode setting unit  105  sets the detection mode to the first detection mode. 
     In Step S14, if it is determined that the sound collection environment is unfavorable, on the other hand, in Step S15 the control target device identification unit  104  changes the setting of the control target device from a first detection mode target device to a second detection mode target device. That is, if the sound collection environment determination unit  108  determines that the sound collection environment is unfavorable, the control target device identification unit  104  changes and resets the control target device, which was previously set as a first detection mode target device, to a second detection mode target device. The server  20  outputs information indicating the change in the setting of the control target device, that is, information including the fact that the setting of the control target device has been changed from a first detection mode target device to a second detection mode target device, to the display  12  or the audio device  13  via the communication unit  107  and the device control unit  11  of the vehicle  1 . Then, in Step S8, the detection mode setting unit  105  sets the detection mode to the second detection mode. 
     Here,  FIG.  9    shows an example in which, in step S15, the control target device identification unit  104  changes and resets the setting of the control target device from a first detection mode target device to a second detection mode target device. In Step S14, if it is determined that the sound collection environment is unfavorable, the navigation device  14 , the call device  15 , the audio device  13 , the display  12 , the interior light  3 , the air conditioner  4 , the seat massage device  33   a , and the seat heater  33   b , classified as having an operational importance of “1 (Low),” as shown in  FIG.  9   , are determined to be second detection mode target devices, and the control request is identified as the second detection mode based on rule-based recognition. Further, the seat position adjustment device  33   c , which is classified as having an operational importance of “2 (Medium),” is also determined to be a second detection mode target device, and the control request is identified as the second detection mode based on rule-based recognition. 
     The settings of the travel control device  31 , the headlamps  32 , the door windows locking device  5   a , the door windows opening/closing device  5   b , the roof window locking device  6   a , the roof window opening/closing device  6   b , the rear doors locking device  7   a , the rear doors opening/closing device  7   b , the trunk locking device  34   a , and the trunk opening/closing device  34   b , which are classified as having an operational importance of “3 (High),” are not changed. Therefore, if it is determined that the sound collection environment is unfavorable in Step S14, the control target devices are all set as second detection mode target devices, and the second detection mode based on rule-based recognition is applied to all of the identifications of the control requests with respect to the control target devices. 
     As described above, in this embodiment of the voice recognition device  300  and the voice recognition method using the voice recognition device  300 , if the sound collection environment determination unit  108  determines that the sound collection environment is favorable and the control target device identification unit  104  determines that the control target device is a first detection mode target device, the detection mode setting unit  105  sets the detection mode to the first detection mode. Therefore, the voice recognition device  300  applies the first detection mode based on natural language recognition to the first detection mode target device whose operational importance is not very high only when the sound collection environment is favorable, i.e., when there is little noise in the sound collection environment, and identifies the control request. That is, the voice recognition device  300  is configured to avoid the application of the first detection mode based on natural language recognition in a noisy sound collection environment. Thus, the voice recognition device  300  can reduce the probability of misrecognition, even when identifying a control request by means of natural language recognition, which has a high degree of flexibility of speech that can be input, so that the control request with respect to the control target device can be more reliably identified. 
     Further, if the sound collection environment determination unit  108  determines that the sound collection environment is unfavorable, the control target device identification unit  104  changes and resets the control target device, which was preset as a first detection mode target device, to a second detection mode target device. Here, if the sound collection environment is unfavorable, that is, a noisy sound collection environment, the probability of misrecognition in the identification of control requests increases. Therefore, a control target device that was preset as a first detection mode target device can be reset as a second detection mode target device, and the second detection mode based on rule-based recognition can be applied to identify the control request, thereby preventing misrecognition. 
     The sound collection environment determination unit  108  acquires the air volume emitted from the air conditioner  4 , which is an air-conditioning device, as state information. Since the higher the air volume of the of the air conditioner  4 , the more noise tends to become mixed with the speech acquired by the speech acquisition unit  101 , by acquiring the air volume emitted from the air conditioner  4  as the state information, the sound collection environment determination unit  108  is able to better assess whether the sound collection environment is favorable or unfavorable. 
     Further, the sound collection environment determination unit  108  acquires as state information the opened/closed state of the roof window W 1  or the door window W 2 , which are openings provided in the vehicle  1 , and the travel speed of the vehicle  1  when the roof window W 1  or the door window W 2  is open. This is because when the vehicle  1  is traveling with an open roof window W 1  or door window W 2 , noise that enters the interior of the vehicle  1  from the outside, such as wind noise, the sound of oncoming vehicles, and the like, increases as the travel speed of the vehicle  1  increases. Therefore, by acquiring the opened/closed state of the roof window W 1  or the door window W 2  and the travel speed of the vehicle  1  as state information, the sound collection environment determination unit  108  is able to better assess whether the sound collection environment is favorable or unfavorable. 
     Further, the sound collection environment determination unit  108  acquires as state information the opened/closed state of the roof window W 1  or the door window W 2 , which are openings provided in the vehicle  1 , and the wind speed around the vehicle  1  when the roof window W 1  or the door window W 2  is opened. This is because when roof window W 1  or door window W 2  of the vehicle  1  is open, the air volume that blows into the interior of the vehicle  1  increases, raising the noise level as the wind speed around the vehicle  1  increases. Even if the vehicle  1  is not traveling but is stopped, if the roof window W 1  or the door window W 2  is open, the wind speed around the vehicle  1  affects the sound collection environment in the interior of the vehicle  1 . Therefore, by acquiring as state information the opened/closed state of the roof window W 1  or the door window W 2  and the wind speed around the vehicle  1 , the sound collection environment determination unit  108  is able to better assess whether the sound collection environment is favorable or unfavorable. The openings of the vehicle  1  are not limited to the roof window W 1  and the door window W 2 , and may be other windows or doors. 
     Further, the sound collection environment determination unit  108  acquires the noise level in the interior of the vehicle  1  as state information. Since the higher the noise level in the interior of the vehicle  1 , the more noise tends to become mixed with the speech acquired by the speech acquisition unit  101 , by acquiring the noise level in the interior of the vehicle  1  as state information, the sound collection environment determination unit  108  is able to better assess whether the sound collection environment is favorable or unfavorable. 
     Further, in the case that the control target device identification unit  104  changes and resets a control target device that was preset as a first detection mode target device to a second detection mode target device, the voice recognition device  300  outputs information indicating the change in the setting of the control target device to the display  12  or the audio device  13  provided in the vehicle  1 . This ensures that the user can reliably confirm that the setting of the control target device has been changed from a first detection mode target device to a second detection mode target device, and the user can more readily voice an instruction that conforms to the current setting of the control target device. 
     The voice recognition method using the voice recognition device  300  according to this embodiment is not limited to the processing steps shown in  FIG.  7   . Another example of the voice recognition method using the voice recognition device  300  is shown in  FIG.  10   . As shown in  FIG.  10   , if, in Step S3, the control target device is identified, in Step S23 the vehicle information acquisition unit  103  acquires the vehicle state information. The process of Step S23 may be executed in parallel with the processes of Step S1 to S4. Then, in Step S24, the sound collection environment determination unit  108  determines whether the sound collection environment is favorable or unfavorable based on the vehicle state information. In Step S24, if it is determined that the sound collection environment is unfavorable, the voice recognition device  300  uniformly sets the detection mode to the second detection mode without determining whether the control target device is a first detection mode target device. In other words, if the sound collection environment determination unit  108  determines that the sound collection environment is favorable and the control target device identification unit  104  determines that the control target device is a second detection mode target device, or if the sound collection environment determination unit  108  determines that the sound collection environment is unfavorable, the detection mode setting unit  105  sets the detection mode to the second detection mode. In this case as well, if it is determined that the sound collection environment is unfavorable, as shown in  FIG.  9   , all of the control target devices are set to second detection mode target devices, and the second detection mode based on rule-based recognition is applied to all of the identifications of the control requests with respect to the control target devices. The voice recognition device  300  can thereby reduce the probability of misrecognition, even when identifying control requests by means of natural language recognition, which has a high degree of flexibility of speech that can be input. 
     Further, the vehicle information acquisition unit  103  can acquire the travel state of the vehicle  1  as state information of the vehicle  1 . In this case, when it is determined that the vehicle  1  is stopped based on the travel state of the vehicle  1 , the control target device identification unit  104  can change and reset the control target device, which was preset as a second detection mode target device, to a first detection mode target device. Specifically, the headlamps  32 , the door windows locking device  5   a , the door windows opening/closing device  5   b , the roof window locking device  6   a , the roof window opening/closing device  6   b , the rear doors locking device  7   a , the rear doors opening/closing device  7   b , the trunk locking device  34   a , and the trunk opening/closing device  34   b , which are second detection mode target devices shown in  FIG.  3   , have little influence on the user while the vehicle  1  is stopped. Therefore, the settings of these on-board devices may be changed to the first detection mode target device, and the control requests may be identified by means of the first detection mode based on natural language recognition, which has a high degree of flexibility of speech that can be input. That is, while the vehicle  1  is stopped, all of the control target devices may be set as first detection mode target devices, and the first detection mode based on natural language recognition may be applied to all of the identifications of the control requests with respect to the control target devices. Further, in the case that the control target device identification unit  104  changes and resets a control target device that was preset as a second detection mode target device to a first detection mode target device, the voice recognition device  300  may output information indicating the change in the setting of the control target device to the display  12  or the audio device  13  provided in the vehicle  1 . 
     Further, the voice recognition devices  100 ,  200 , and  300  may set the first detection mode or the second detection mode in accordance with the identified control target device regardless of whether the natural language recognition or rule-based recognition is used as the method of voice recognition. For example, both the first detection mode and the second mode may be based on natural language recognition. In this case as well, the second detection mode has a narrower range of the speech data that can be recognized in accordance with each control request than the first detection mode. Specifically, the first detection mode may be a detection mode based on multi-intent type natural language recognition, and the second detection mode may be a detection mode based on single-intent type natural language recognition. In a detection mode based on multi-intent type natural language recognition, the control request identification unit  106  can identify two control target devices (air conditioner  4  and door window W 2 ) and the control request (“I want to turn OFF the air conditioner” and “I want to open the door window”) for each control target device, from a voiced instruction that contains two or more control requests, such as “turn off the air conditioner and open the window,” or the like. On the other hand, in a detection mode based on single-intent type natural language recognition, the control request identification unit  106  can identify a control request only when one control request is included per voiced instruction, such as “turn off the air conditioner” or “open the window.” 
     Further, as shown in  FIG.  3   , the voice recognition devices  100 ,  200 , and  300  may change the method of natural language recognition depending on whether the control target device is classified as having an operational importance of “1 (Low)” or an operational importance of “2 (Medium).” Specifically, the detection mode setting unit  105  may set the first detection mode based on multi-intent type natural language recognition with respect to a control target device classified as having an operational importance of “1 (Low)” and set the first detection mode based on single-intent type natural language recognition with respect to a control target device that is classified as having an operational importance of “2 (Medium).” Not limited thereto, the detection mode setting unit  105  may set detection modes based on natural language recognition by means of two or more types of methods, as deemed suitable, depending on the first detection mode target device. 
     Further, the moving body is not limited to a vehicle, but may be a train or an airplane. 
     The vehicle  1  described above corresponds to a moving body according to the present invention. The interior light  3  described above corresponds to the environment adjustment device according to the present invention. The air conditioner  4  described above corresponds to the environment adjustment device and the air conditioning device according to the present invention. The display  12  described above corresponds to the information provision device according to the present invention. The audio device  13  described above corresponds to the environment adjustment device and the information provision device according to the present invention. The vehicle information acquisition unit  103  described above corresponds to the moving body information acquisition unit according to the present invention. The roof window W 1  and the door window W 2  described above correspond to the openings of the present invention.