Patent Publication Number: US-11037558-B2

Title: Audio modulation for an audio interface

Description:
BACKGROUND 
     1. Field 
     The disclosure relates generally to an improved computer system and, more specifically, to a method, apparatus, system, and computer program product for generating audio communications. 
     2. Description of the Related Art 
     Virtual assistants have become commonly available to help users perform tasks. The virtual assistants are artificial intelligence (AI) systems that can perform tasks or services for a user. A virtual assistant can use voice queries and a natural language interface to interact with the user through a computing device such as a smart phone, a tablet computer, a personal computer, a smart speaker, or some other type of device. These computing devices are cognitive audio interfaces with which the users can interact. 
     For example, a virtual assistant can manage a calendar, manage a timer, set an alarm, provide audio instructions for preparing a dish from a recipe, play music, make a to-do list, provide weather information, provide traffic information, deliver audio messages, control smart devices, or perform other tasks. In some situations, the information provided can be more important or urgent than in other situations. For example, a situation in which a user asks for instructions on how to handle a flat tire while driving is more urgent than when a situation in which the user asks for traffic or weather information. Current virtual assistants do not distinguish between situations that have different levels of urgency when receiving requests from users. 
     SUMMARY 
     According to one embodiment of the present invention, a method generates an audio communication. An urgency for a user is determined by a computer system in response to detecting a trigger event in a verbal communication from the user. A frequency modulator is selected by the computer system from a plurality of frequency modulators based on the urgency determined to form a selected frequency modulator. A frequency of words in an audio communication is modulated by the computer system using the selected frequency modulator to form a modulated audio communication. The modulated audio communication comprises a natural language response generated in response to the trigger event. The modulated audio communication is sent by the computer system to an audio output device. 
     According to another embodiment of the present invention, an audio communications system comprises a computer system. The computer system determines an urgency for a user in response to detecting a trigger event in a verbal communication from the user and selects a frequency modulator from a plurality of frequency modulators based on the urgency determined to form a selected frequency modulator. The computer system modulates a frequency of words in an audio communication using the selected frequency modulator to form a modulated audio communication. The modulated audio communication comprises a natural language response generated in response to the trigger event and sends the modulated audio communication to an audio output device. 
     According to yet another embodiment of the present invention, a computer program product for generating an audio communication comprises a computer-readable storage media with first program code, second program code, third program, and fourth program code stored on the computer readable storage media. The first program code is run to determines an urgency for a user in response to detecting a trigger event in a verbal communication from the user. The second program code, is run to select a frequency modulator from a plurality of frequency modulators based on the urgency determined to form a selected frequency modulator. The third program code is run to modulating a frequency of words in an audio communication using the selected frequency modulator to form a modulated audio communication. The audio communication comprises a natural language response generated in response to the trigger event. The fourth program code is run to send the modulated audio communication to an audio output device. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a pictorial representation of a network of data processing systems in which illustrative embodiments may be implemented; 
         FIG. 2  is a block diagram of an audio communication environment in accordance with an illustrative embodiment; 
         FIG. 3  is a diagram of a communications processor in accordance with an illustrative embodiment; 
         FIG. 4  is a flowchart of a process for generating an audio communication in accordance with an illustrative embodiment; 
         FIG. 5  is a flowchart of a process for generating audio communications in which an urgency for a user changes in accordance with an illustrative embodiment. 
         FIG. 6  is a flowchart of a process for selecting a frequency modulator taking into account language proficiency in accordance with an illustrative embodiment; 
         FIG. 7  is a flowchart of a process for selecting a set of frequency modulators in accordance with an illustrative embodiment; 
         FIG. 8  is a block diagram of a client device in accordance with an illustrative embodiment; and 
         FIG. 9  is a block diagram of a data processing system in accordance with an illustrative embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     The present invention may be a system, a method, and/or a computer program product. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer-readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer-readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer-readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer-readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer-readable program instructions described herein can be downloaded to respective computing/processing devices from a computer-readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer-readable program instructions from the network and forwards the computer-readable program instructions for storage in a computer-readable storage medium within the respective computing/processing device. 
     Computer-readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++ or the like, and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The computer-readable program instructions may run entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may run the computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions. 
     These computer program instructions may be provided to a processor of a general-purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which are processed via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer program instructions may also be stored in a computer-readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which run on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be processed substantially concurrently, or the blocks may sometimes be processed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     The illustrative examples recognize and take into account one or more different considerations. For example, the illustrative examples recognize and take into account that currently available virtual assistants do not determine an urgency of a situation. Further, the illustrative examples recognize and take into account that virtual assistants do not modulate the frequency of a response based on the urgency of a situation. For example, the illustrative examples recognize and take into account that current virtual assistants do not modulate a frequency of words in an audio response to a user. 
     With reference now to the figures and, in particular, with reference to  FIG. 1 , a pictorial representation of a network of data processing systems is depicted in which illustrative embodiments may be implemented. Network data processing system  100  is a network of computers in which the illustrative embodiments may be implemented. Network data processing system  100  contains network  102 , which is the medium used to provide communications links between various devices and computers connected together within network data processing system  100 . Network  102  may include connections, such as wire, wireless communication links, or fiber optic cables. 
     In the depicted example, server computer  104  and server computer  106  connect to network  102  along with storage unit  108 . In addition, client devices  110  connect to network  102 . As depicted, client devices  110  include client computer  112 , client computer  114 , and client computer  116 . Client devices  110  can be, for example, computers, workstations, or network computers. In the depicted example, server computer  104  provides information, such as boot files, operating system images, and applications to client devices  110 . Further, client devices  110  can also include other types of client devices such as mobile phone  118 , tablet computer  120 , and smart speaker  122 . In this illustrative example, server computer  104 , server computer  106 , storage unit  108 , and client devices  110  are network devices that connect to network  102  in which network  102  is the communications media for these network devices. Some or all of client devices  110  may form an Internet of things (IoT) in which these physical devices can connect to network  102  and exchange information with each other over network  102 . 
     Client devices  110  are clients to server computer  104  in this example. Network data processing system  100  may include additional server computers, client computers, and other devices not shown. Client devices  110  connect to network  102  utilizing at least one of wired, optical fiber, or wireless connections. 
     Program code located in network data processing system  100  can be stored on a computer-recordable storage medium and downloaded to a data processing system or other device for use. For example, program code can be stored on a computer-recordable storage medium on server computer  104  and downloaded to client devices  110  over network  102  for use on client devices  110 . 
     In the depicted example, network data processing system  100  is the Internet with network  102  representing a worldwide collection of networks and gateways that use the Transmission Control Protocol/Internet Protocol (TCP/IP) suite of protocols to communicate with one another. At the heart of the Internet is a backbone of high-speed data communication lines between major nodes or host computers consisting of thousands of commercial, governmental, educational, and other computer systems that route data and messages. Of course, network data processing system  100  also may be implemented using a number of different types of networks. For example, network  102  can be comprised of at least one of the Internet, an intranet, a local area network (LAN), a metropolitan area network (MAN), or a wide area network (WAN).  FIG. 1  is intended as an example, and not as an architectural limitation for the different illustrative embodiments. 
     As used herein, “a number of,” when used with reference to items, means one or more items. For example, “a number of different types of networks” is one or more different types of networks. 
     Further, the phrase “at least one of,” when used with a list of items, means different combinations of one or more of the listed items can be used, and only one of each item in the list may be needed. In other words, “at least one of” means any combination of items and number of items may be used from the list, but not all of the items in the list are required. The item can be a particular object, a thing, or a category. 
     For example, without limitation, “at least one of item A, item B, or item C” may include item A, item A and item B, or item B. This example also may include item A, item B, and item C or item B and item C. Of course, any combinations of these items can be present. In some illustrative examples, “at least one of” can be, for example, without limitation, two of item A; one of item B; and ten of item C; four of item B and seven of item C; or other suitable combinations. 
     In this illustrative example, user  124  interacts with virtual assistant  126  in server computer  104  using a client device, such as mobile phone  118  or smart speaker  122 . For example, user  124  can make a request in verbal communication  128  that is detected by mobile phone  118 . Verbal communication  128  also includes a trigger event that causes processing of verbal communication  128  as a request. For example, user  124  can request a daily briefing in verbal communication  128 . Mobile phone  112  sends verbal communication  128  to virtual assistant  126  in server computer  104 . 
     In response, virtual assistant  126  analyses verbal communication  128  to generate a response. In this illustrative example, the response is a natural language response in an audio communication. Additionally, virtual assistant  126  determines an urgency of the situation for user  124 . For example, if user  124  has a meeting in 10 minutes, the urgency is higher than if user  124  has a meeting in 2 hours. 
     With a determination of the urgency for user  124 , virtual assistant  126  modulates a frequency of the words in the audio communication to have a frequency based on the urgency of the situation for user  124 . The modulation is made using a selected frequency modulator. 
     For example, the frequency is higher if the meeting is in 10 minutes as opposed to 2 hours. As a result, the frequency or speed at which words are spoken in the natural language response is faster in the audio communication. This modulation of audio communication forms modulated audio communication  132  which is sent to mobile phone  118  and presented to user  124  by a speaker in mobile phone  118 . 
     With reference now to  FIG. 2 , a block diagram of an audio communication environment is depicted in accordance with an illustrative embodiment. In this illustrative example, audio communications environment  200  includes components that can be implemented in hardware such as the hardware shown in network data processing system  100  in  FIG. 1 . Network data processing system  100  and the components in network data processing system  100  in  FIG. 1  are an example of a network data processing system that can be used in audio communications environment  200 . 
     As depicted, audio communications system  202  in audio communications environment  200  includes computer system  204  and client device  206 . Computer system  204  is a physical hardware system and includes one or more data processing systems. When more than one data processing system is present in computer system  204 , those data processing systems are in communication with each other using a communications medium. The communications medium can be a network. The data processing systems can be selected from at least one of a computer, a server computer, a tablet computer, or some other suitable data processing system. 
     In this illustrative example, client device  206  is a hardware system and can include software. Client device  206  can take a number of different forms. For example, client device  206  can be selected from a group comprising a mobile phone, a laptop computer, a tablet computer, smart glasses, a smart speaker, and other suitable devices. 
     Client device  206  is operated by user  208 . In this illustrative, client device  206  detects verbal communication  212  originating from user  208 . When trigger event  214  is present in verbal communication  212 , client device  206  sends verbal communication  212  to communications processor  216  in computer system  204 . Trigger event  214  can take a number of different forms. For example, trigger event  214  is selected from at least one of a key phrase spoken by user  208 , an emergency call made by user  208 , a wake word spoken by user  208 , a gesture made by user  208 , or some other suitable input made by user  208 . 
     Communications processor  216  is designed to process verbal communication  212  received from user  208 . As depicted, communications processor  216  includes artificial intelligence system  218  which operates to process verbal communication  212  and generate audio communication  220 . Verbal communication  212  is what user  208  says or speaks. 
     Artificial intelligence system  218  is a system that has intelligent behavior and can be based on function of a human brain. Artificial intelligence system  218  comprises at least one of an artificial neural network, a cognitive system, a Bayesian network, a fuzzy logic, an expert system, a natural language system, a cognitive system, or some other suitable system. Machine learning is used to train artificial intelligence system  218 . Machine learning involves inputting data to the process and allowing the process to adjust and improve the function of artificial intelligence system  218 . 
     In this illustrative example, natural language processes in artificial intelligence system  218  and communications processor  216  are used to process verbal communication  212 . The natural language processes can include at least one of speech recognition, natural language understanding, natural language generation, or other processes used to process verbal communications. Communications processor  216  identifies request  222  within verbal communication  212  and generates response  224 . As depicted, response  224  is natural language response  226 , which is a response that is in a human language. 
     Further, communications processor  216  determines urgency  228  for user  208  in response to detecting trigger event  214  in verbal communication  212  from user  208 . For example, communications processor  216  determines urgency  228  of situation  230  for user communications processor  216  determines urgency  228  for user  208 . In this illustrative example, situation  230  is one or more circumstances for user  208 . Situation  230  can also include a location and an environment around user  208 . 
     In this illustrative example, situation  230  can be determined by artificial intelligence system  218 . Artificial intelligence system  218  can process verbal communication  212  to identify situation  230 . For example, if verbal communication  212  is “I am on the highway and have a flat tire . . . what should I do?”, situation  230  is a “flat tire.” Subsequent verbal communications relating to the “flat tire” are all considered to be part of situation  230 . As another example, the situation can be mowing a yard, swimming in an ocean, staining a fence, playing a chess game, or some other situation. 
     As depicted, urgency  228  can be identified based on situational context  231  for user  208  in situation  230 . In this illustrative example, situational context  231  can include at least one of an environmental context, a temporal context, an emotional context, or other types of context for user  208  in situation  230 . 
     Communications processor  216  can determine situational context  231  from verbal communication  212 . Moreover, communications processor  216  can also use other types of information to identify situational context  231 . For example, situational context  231  can be determined using at least one of an input interaction rate of user  208 , an emotion of user  208  in verbal communication  212  from user  208 , a location of user  208 , biometric information for user  208 , a current time relative to a calendar event for user  208 , or some other information about situation  230  for user  208 . 
     The information used to identify situational context  231  can be obtained from a number of different sources. For example, an interaction rate is a number of input requests that user  208  receives over a period of time. This interaction rate can be determined by client device  206  or communications processor  216 . In another example, the location of user  208  can be identified using a global positioning in client device  206  in addition to or in place of location information spoken by user  208  in verbal communication  212 . 
     In the illustrative example, a platform that performs motion-based analytics that is in communication with communications processor  216  can perform emotional analysis. As another example, calendar information can be obtained from a calendar server or a work scheduler that is in communication with communications processor  216 . 
     Communications processor  216  generates audio communication  220  which comprises natural language response  226 , generated in response to trigger event  214 . Communications processor  216  selects frequency modulator  232  to modulate audio communication  220  from a plurality of frequency modulators  234  based on urgency  228  to form selected frequency modulator  236 . In the illustrative example, frequency modulators  234  can be implemented using software, hardware, or a combination thereof. For example, frequency modulator  232  can be a circuit that is designed to modulate audio communication  220  to have a selected frequency. In another illustrative example, frequency modulator  232  can be a software process that runs on a hardware processor unit to modulate audio communication  220 . 
     Communications processor  216  modulates frequency  238  of words  240  in audio communication  220  using selected frequency modulator  236  to form modulated audio communication  242 . In this illustrative example, frequency  238  of words  240  is the speed at which words  240  are spoken in audio communication  220 . For example, as frequency  238  increases, the speed at which words  240  are spoken in audio communication  220  increases. As frequency  238  decreases, the speed at which words  240  are spoken in audio communication  220  decreases. 
     In this illustrative example, audio communication  220  comprises natural language response  226  generated in response to trigger event  214 . Communications processor  216  sends modulated audio communication  242  to audio output device  244  in client device  206 . Modulated audio communication  242  can be audio data or a higher level of representation of the audio data for playback by a remote computing device. 
     As depicted, communications processor  216  selects new frequency modulator  246  from the plurality of frequency modulators  234  when urgency  228  changes for user  208 . For example, as situation  230  progresses, urgency  228  for situation  230  can change. In other words, urgency  228  for situation  230  can change over time. 
     As user  208  speaks, additional verbal communications are generated. These verbal communications are processed by communications processor  216  to determine urgency  228 . Over time, urgency  228  can change as additional verbal communications are processed. 
     For example, user  208  may say “I am on the highway, and my car has a flat tire.” Situation  230  identified in verbal communication  212  is a flat tire situation. Verbal communications from user  208  about the flat tire are part of situation  230 . 
     In this example, communications processor  216  generates audio communication  220  with natural language response  226 . For example, audio communication  220  is “Please steer the car into the emergency lane. Please do not disconnect this call.” 
     Further, communications processor  216  determines urgency  228  using verbal communication  212 . Urgency  228  is identified as high urgency seen this illustrative example. Communications processor  216  selects frequency modulator  232  as a frequency modulator used for high urgency situations. Communications processor  216  modulates audio communication  220  using selected frequency modulator  236  and sends modulated audio communication  242  to user  208 . 
     During situation  230 , user  208  may then say at a later time “I have moved the car into the emergency lane . . . Can you send a tow truck or someone to change the tire?” This verbal communication is a subsequent verbal communication to verbal communication  212  for situation  230 . 
     In response to the subsequent verbal communication, communications processor  216  generates a new audio communication with a natural language response that says “A road assistance vehicle is on the way.” 
     Additionally, communications processor  216  determines urgency  228  has changed to normal urgency from high urgency and selects a new frequency modulator from the plurality of frequency modulators used for normal urgency situations. Communications processor  216  modulates the new audio communication using the newly selected frequency modulator. This new modulated audio communication is then sent to user  208 . 
     In this manner, communications processor  216  can dynamically change the frequency modulators used to generate audio communications when urgency  228  changes during situation  230  for user  208 . A similar change can be made for different situations. 
     In another illustrative example, communications processor  216  can also modulate amplitude  248  of words  240  in audio communication  220  in addition to or in place of frequency  238  using selected frequency modulator  236 . Further, amplitude  248  can also be modulated differently for different situations based on the selection of a frequency modulator from the plurality of frequency modulators  234 . 
     In the illustrative example, communications processor  216  is also capable of selecting a frequency modulator from the plurality of frequency modulators  234  based on characteristics of user  208 . For example, communications processor  216  can determine language proficiency  250  for user  208 . Language proficiency  250  is a measure of the ability of user  208  to speak or understand a particular language. Language proficiency  250  can take into account at least one of accuracy, fluency, vocabulary, or other factors spec to the ability of user  208  being able to speak a language. Language proficiency  250  can be different for different users based on an amount of experience or knowledge they have with a particular language. 
     Additionally, language proficiency  250  can also change based on age, physiological conditions, or environmental conditions. For example, user  208  may have a more difficult time hearing based on an age of user  208  or the environment. If user  208  is in a loud environment, language proficiency  250  may be lower than if a lower noise environment is present because of an inability of user  208 . As the noise in the environment increases, the ability of user  208  to clearly hear and understand natural language responses in audio communications in the loud environment can be reduced. 
     In the illustrative example, language proficiency  250  for user  208  can be identified in a number of different ways. For example, results from a language proficiency test taken by user  208  can be used. In another illustrative example, verbal communications from user  208  can be analyzed by artificial intelligence system  218  to determine language proficiency  250 . For example, natural language processes that include natural language understanding can analyze at least one of vocabulary, speech patterns, grammar, sentence structure, pronunciation, word choice, or other metrics in verbal communications from user  208 . 
     In another illustrative example, the loud environment may result in a reduced ability of user  208  to understand audio communications generated by communications processor  216  with a particular frequency that would normally be appropriate for urgency  228 . The response of user  208  can be used to identify a situation in which language proficiency  250  is lower than desired in the loud environment. 
     For example, the verbal communications made by user  208  can indicate that user  208  does not understand natural language responses in prior audio communications sent by communications processor  216 . In other words, the verbal communications by user  208  can indicate if a desired level of understanding of natural language responses in the audio communications sent by communications processor  216  is absent. In one illustrative example, verbal communication  212  can be modulated to decrease frequency  238 , increase amplitude  248 , or both for audio communication  220  in an attempt to increase the comprehension of audio communications by user  208 . 
     An adaptation or selection of words used in natural language responses in the audio communications can be made based on feedback on how well user  208  understands the natural language responses in the audio communications. For example, a simpler vocabulary can be used if the responses made by user  208  indicate that a desired level of comprehension of the audio communications is not present. 
     Communications processor  216  selects frequency modulator  232  from the plurality of frequency modulators  234  based on urgency  228  and language proficiency  250  to form selected frequency modulator  236 . For example, language proficiency  250  can be used as a weighting factor. 
     For example, urgency  228  can be a value that corresponds to values for the plurality of frequency modulators  234 . For example, if 7 frequency modulators are present, urgency  228  can have an integer value from 1 to 7 with 1 being for the frequency modulator having the highest frequency. 
     Language proficiency  250  can be used to adjust urgency  228 . For example, a highest proficiency for language proficiency  250  can have a value of 0 while a below average score for language proficiency  250  can have a value of 3 and a poor score can have a value of 5. The value for language proficiency  250  is added to the value of urgency  228  and obtain an adjusted value for urgency  228  that corresponds to one of the frequency modulators. The adjusted value of urgency  228  in this example does not go above 7. Thus, this feature allows communications processor  216  to take into account language proficiency  250  of user  208  in comprehending the language used in natural language response  226 . 
     For example, if language proficiency  250  of user  208  is lower than average for the language in audio communications  220 , a lower urgency frequency modulator from the plurality of frequency modulators  234  can be selected instead of the frequency modulator that would be selected if the proficiency of user  208  for the language is average. The lower frequency causes words  240  in modulated audio communication  242  to be spoken slower to user  208 . In this manner, communications processor  216  can also take into account language proficiency  250  for user  208  for the language used in natural language response  226  in communicating with user  208 . 
     Further, communications processor  216  can generate natural language response  226  based on urgency  228  of situation  230  of user  208 . For example, when urgency  228  is a low urgency situation, natural language response  226  can be more verbose and chatty as compared to when urgency  228  is a high urgency situation. 
     With a high urgency situation, natural language response  226  can be more concise and contain word choices less subject to misinterpretation. For example, natural language response  226  can use a nautical alphabet to spell out words that are important in a high urgency situation such that the words are less likely to be misunderstood. 
     In the illustrative examples, communications processor  216  can be used in various programs, products, interfaces, or other applications. For example, communications processor  216  can be used in audio-enabled interfaces, cognitive audio interfaces, virtual assistants, virtual avatars, tangible cognitive interfaces such as robots, or other physical or software applications. 
     Communications processor  216  can be implemented in software, hardware, firmware, or a combination thereof. When software is used, the operations performed by communications processor  216  can be implemented in program code configured to run on hardware, such as a processor unit. When firmware is used, the operations performed by communications processor  216  can be implemented in program code and data and stored in persistent memory to run on a processor unit. When hardware is employed, the hardware may include circuits that operate to perform the operations in communications processor  216 . 
     In the illustrative examples, the hardware may take a form selected from at least one of a circuit system, an integrated circuit, an application specific integrated circuit (ASIC), a programmable logic device, or some other suitable type of hardware configured to perform a number of operations. With a programmable logic device, the device can be configured to perform the number of operations. The device can be reconfigured at a later time or can be permanently configured to perform the number of operations. Programmable logic devices include, for example, a programmable logic array, a programmable array logic, a field programmable logic array, a field programmable gate array, and other suitable hardware devices. Additionally, the processes can be implemented in organic components integrated with inorganic components and can be comprised entirely of organic components excluding a human being. For example, the processes can be implemented as circuits in organic semiconductors. 
     In one illustrative example, one or more technical solutions are present that overcome a technical problem with communicating with users based on an urgency for the users. As a result, one or more technical solutions may provide a technical effect of modulating audio communications sent to users in a manner that changes a frequency of the audio communications based on the urgency of the situations for the users. 
     One or more technical solutions provide a technical effect taking into account urgency in generating a natural language response in an audio communication. For example, one or more technical solutions modulate a natural language response in an audio communication to have a frequency based on the urgency for the user. One or more technical solutions modulates the frequency of words in the audio communication based on the urgency of the situation for the user. For example, one or more technical solutions increases a speed at which the words are spoken when the urgency of the situation is greater as compared to the speed at which the words are spoken when the urgency is lower. 
     As a result, computer system  204  operates as a special purpose computer system in which communications processor  216  in computer system  204  enables facilitating communications with users in a more effective manner based on the urgency for situations for the users. In particular, communications processor  216  transforms computer system  204  into a special purpose computer system as compared to currently available general computer systems that do not have communications processor  216 . 
     The illustration of audio communications environment  200  in  FIG. 2  is not meant to imply physical or architectural limitations to the manner in which an illustrative embodiment can be implemented. Other components in addition to or in place of the ones illustrated may be used. Some components may be unnecessary. Also, the blocks are presented to illustrate some functional components. One or more of these blocks may be combined, divided, or combined and divided into different blocks when implemented in an illustrative embodiment. 
     For example, although not shown, a network is used to facilitate communications between computer system  204  and client device  206 . This network can be similar to network  102  used in network data processing system  100  in  FIG. 1 . As another illustrative example, artificial intelligence system  218  can be a separate component from communications processor  216  instead being part of communications processor  216 . 
     With reference next to  FIG. 3 , a diagram of a communications processor is depicted in accordance with an illustrative embodiment. As depicted, communications processor  300  is an example of an implementation for communications processor  216  in  FIG. 2 . In this illustrative example, communications processor  300  includes controller  302 , modulator selector  304 , and input/output (I/O) interface  306 . 
     As depicted, input/output interface  306  facilitates communication with client device  308  and dialogue module  310 . Input/output interface  306  comprises hardware and may include software. For example, input/output interface  306  can include at least one of a network interface card (NIC), a universal serial bus (USB) port, a shared memory, a bus system, or some other suitable interface that provides for the exchange of information between controller  302 , client device  308 , and dialogue module  310 . 
     In this illustrative example, dialogue module  310  can be implemented using an artificial intelligence system. Dialogue module  310  analyzes verbal communication  312  received from user  314  utilizing client device  308  and generates audio communication  316  containing natural language response  318 . Natural language response  318  is text using words that are structured in a manner that is understood and used by people to communicate with each other. For example, natural language response  318  may be in English, French, Spanish, Russian, or some other language spoken by people to communicate with each other. Audio communication  316  is the audio or spoken version of the text in natural language response  318 . 
     As depicted, modulator selector  304  determines an urgency for audio communication  316 . The urgency can be determined for user  314 . For example, the urgency can be determined based on the situation of user  314 . The situation can be determined from one or more circumstances for user  314 . The situation can also include a location and an environment around user  314 . 
     Based on the urgency identified, modulator selector  304  selects one of frequency modulators  320  to modulate audio communication  316 . Controller  302  controls the selected frequency modulator to modulate audio communication  316 , which results in modulated audio communication  332 . 
     In this illustrative example, frequency modulators  320  comprise critical urgency frequency modulator  322 , high urgency frequency modulator  324 , medium urgency frequency modulator  326 , normal urgency frequency modulator  328 , and low urgency frequency modulator  330 . Controller  302  returns modulated audio communication  332  to client device  308  using input/output interface  306 . 
     The urgency can be determined by modulator selector  304  using verbal communication  312 . As depicted, verbal communication  312  can be analyzed by modulator selector  304  in determining the urgency. Modulator selector  304  can analyze verbal communication  312  to identify at least one of an emotional state, a location, a time, and other information that may be used to determine the urgency for audio communication  316 . For example, the emotional state of user  314  can be determined from at least one of inflection, intonation, voice pitch, speech pattern, words, or other information in verbal communication  312 . Additionally, the urgency of the situation for user  314  can be determined from information about the environment obtained from verbal communication  312 . 
     Additionally, modulator selector  304  can interface with external systems  334  to obtain information for use in determining the urgency for audio communication  316 . For example, modulator selector  304  communicates with a work scheduler or a calendar system to determine how close an upcoming event is to the current time. As the upcoming event is closer in time, the urgency can increase. For example, user  314  can request a daily briefing. If a meeting is scheduled within five minutes, modulator selector  304  can select high urgency frequency modulator  324  for use in modulating audio communication  316  containing the daily briefing. If, however, the meeting is set for two hours later, modulator selector  304  selects low urgency frequency modulator  330  for use in modulating audio communication  316  containing the daily briefing. 
     In this illustrative example, modulator selector  304  can be implemented in a number of different ways. For example, modulator selector  304  can be implemented using at least one of an artificial intelligence system, a rules-based system, an expert system, or some other suitable mechanism. 
     The illustration of communications processor  300  is show for purposes of illustrating one manner in which communications processor  216  in  FIG. 2  can be implemented and not meant to limit the manner in which communications processor  216  can be implemented in other examples. For example, in other illustrative examples, communications processor  300  can use 3 frequency modulators, 10 frequency modulators, or some other number of frequency modulators other than the 5 frequency modulators show in  FIG. 3 . 
     Turning next to  FIG. 4 , a flowchart of a process for generating an audio communication is depicted in accordance with an illustrative embodiment. The processes in  FIG. 4  can be implemented in hardware, software, or both. When implemented in software, the processes can take the form of program code that is run by one of more processor units located in one or more hardware devices in one or more computer systems. For example, these processes can be implemented in communications processor  216  in computer system  203  in  FIG. 2  or communications processor  300  in  FIG. 3 . 
     The process begins by determining an urgency of a situation for a user in response to detecting a trigger event in a verbal communication from the user (step  400 ). The process selects a frequency modulator from a plurality of frequency modulators based on the urgency determined to form a selected frequency modulator (step  402 ). 
     The process modulates a frequency of words in an audio communication using the selected frequency modulator to form a modulated audio communication (step  404 ). In step  404 , the modulated audio communication comprises a natural language response generated in response to the trigger event. In the illustrative examples, the frequency is how fast the words are spoken in the audio response rather than how often a word is repeated in the audio response. The process sends the modulated audio communication to an audio output device (step  406 ). The process terminates thereafter. 
     Turning next to  FIG. 5 , a flowchart of a process for generating audio communications in which an urgency for a user changes is depicted in accordance with an illustrative embodiment. The processes in  FIG. 5  can be implemented in hardware, software, or both. When implemented in software, the processes can take the form of program code that is run by one of more processor units located in one or more hardware devices in one or more computer systems. For example, these processes can be implemented in communications processor  216  in computer system  203  in  FIG. 2  or communications processor  300  in  FIG. 3 . 
     The process begins by receiving a verbal communication from a user utilizing a client device (step  500 ). A determination is made as to whether a trigger event is present in the verbal communication (step  502 ). If a trigger event is absent, the process terminates. 
     Otherwise, the process determines the urgency for a user (step  504 ). In step  504 , the urgency can be determined using at least one of the verbal communication or from other information. For example, the other information may include a global positioning system (GPS) location received from a client device used by the user. This location is received as part of the verbal communication or as a separate piece of data. In another example, the location information may be received from a vehicle operated by the user. As yet another example, movement information received from the client device can be used to determine an urgency of the situation. In still other illustrative examples, biometric information can be used and obtained from the client device in the form of a smart watch. 
     The process selects a frequency modulator based on the urgency determined for the user (step  506 ). The process generates an audio communication including a natural language response (step  508 ). In this illustrative example, the wording, grammatical structure, language, or other characteristics of the natural language response generated in step  508  can be generated based on the urgency determined for the user. 
     The process modulates the audio communication using a selected frequency modulator (step  510 ). The process sends a modulated audio communication to client the device to be output to the user (step  512 ). 
     The process waits for a subsequent verbal communication (step  514 ). When the subsequent verbal communication is received, the process returns to step  502  as described above. In this manner, the process can select a new frequency modulator as the urgency changes for the user. 
     With reference now to  FIG. 6 , a flowchart of a process for selecting a frequency modulator taking into account language proficiency is depicted in accordance with an illustrative embodiment. The processes in  FIG. 6  can be implemented in hardware, software, or both. When implemented in software, the processes can take the form of program code that is run by one of more processor units located in one or more hardware devices in one or more computer systems. For example, these processes can be implemented in communications processor  216  in computer system  203  in  FIG. 2  or communications processor  300  in  FIG. 3 . This process is an example of an implementation of step  402  in  FIG. 4  and step  506  in  FIG. 5 . 
     The process begins by determining a language proficiency for a user for a language used in an audio communication (step  600 ). The process selects a frequency modulator from a plurality of frequency modulators based on an urgency and the language proficiency for the user to form a selected frequency modulator (step  602 ). The process terminates thereafter. 
     With reference now to  FIG. 7 , a flowchart of a process for selecting a set of frequency modulators is depicted in accordance with an illustrative embodiment. The processes in  FIG. 7  can be implemented in hardware, software, or both. When implemented in software, the processes can take the form of program code that is run by one of more processor units located in one or more hardware devices in one or more computer systems. For example, these processes can be implemented in communications processor  216  in computer system  203  in  FIG. 2  or communications processor  300  in  FIG. 3 . This process is similar to the process in  FIG. 4  in which step  402  and step  404  are not performed when taking into account that portions of a natural language response may have different urgencies for presentation to a user. These urgencies for the portions of the natural language response are referred to as response urgencies. As depicted, different portions of the natural language response in an audio communication can be modulated differently based on the urgency for each portion of the natural language response. 
     The process begins by determining an urgency for a user in response to detecting a trigger event in a verbal communication from the user (step  700 ). The process determines a set of response urgencies for a set of portions of a natural language response in an audio communication (step  702 ). As used herein, “a set of,” when used with reference to items, means one or more items. For example, “a set of response urgencies” is one or more response urgencies. 
     The process selects a set of frequency modulators from a plurality of modulators based on a set of response urgencies for a set of portions and the urgency for the user to form a set of selected frequency modulators (step  704 ). The process modulates a set of frequencies of words in the set of portions of the natural language response in the audio communication using the set of selected frequency modulators to form a modulated audio communication (step  706 ). The process sends the modulated audio communication to an audio output device (step  708 ). The process terminates thereafter. 
     For example, when a user says “I am on the highway, and my car has a flat tire,” this verbal communication has a critical urgency. The natural language response is “Please steer the car into the emergency lane. Please do not disconnect the call.” Using the process in  FIG. 7 , the frequency modulators are selected based on the set of response urgencies in the natural language response in the urgency for the user. 
     In this illustrative example, a first portion of the natural language response, “Please steer the car into the emergency lane,” is modulated using a critical frequency modulator while a second portion of natural language response, “Please do not disconnect this call,” is modulated using a normal modulator, which is at a lower level or urgency as compared to the first portion. The urgency determined for the user and the response urgencies for the different portions of the natural language response are used to select the set of frequency modulators. For example, the urgency determined for the user can be used as the ceiling or highest level frequency modulator that can be selected using the response urgencies for the portions of the natural language response. In some illustrative examples, the set of frequency modulators can be selected without taking into account the urgency for the user. 
     The flowcharts and block diagrams in the different depicted embodiments illustrate the architecture, functionality, and operation of some possible implementations of apparatuses and methods in an illustrative embodiment. In this regard, each block in the flowcharts or block diagrams may represent at least one of a module, a segment, a function, or a portion of an operation or step. For example, one or more of the blocks can be implemented as program code, hardware, or a combination of the program code and hardware. When implemented in hardware, the hardware may, for example, take the form of integrated circuits that are manufactured or configured to perform one or more operations in the flowcharts or block diagrams. When implemented as a combination of program code and hardware, the implementation may take the form of firmware. Each block in the flowcharts or the block diagrams can be implemented using special purpose hardware systems that perform the different operations or combinations of special purpose hardware and program code run by the special purpose hardware. 
     In some alternative implementations of an illustrative embodiment, the function or functions noted in the blocks may occur out of the order noted in the figures. For example, in some cases, two blocks shown in succession can be performed substantially concurrently, or the blocks may sometimes be performed in the reverse order, depending upon the functionality involved. Also, other blocks can be added in addition to the illustrated blocks in a flowchart or block diagram. For example, step  506  and step  508  can be performed in reverse order or at substantially the same time. 
     With reference to  FIG. 8 , a block diagram of a client device is depicted in accordance with an illustrative embodiment. Client device  800  is an example of one manner in which client device  206  in  FIG. 2  can be implemented for facilitating audio communications. In this illustrative example, client device  800  includes physical hardware components such as processor unit  802 , communications framework  804 , memory  806 , data storage  808 , communications unit  810 , display  812 , and audio interface  814 . 
     Communications framework  804  allows different components in client device  800  to communicate with each other when connected to communications framework  804 . Communications framework  804  is a bus system in this illustrative example. 
     Processor unit  802  processes program code for software loaded into memory  806 . Processor unit  802  include one or more processors. For example, processor unit  802  can be selected from at least one of a multicore processor, a central processing unit (CPU), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a network processor, or some other suitable type of processor. 
     Memory  806  is connected to processor unit  802  through communications framework  804 . As depicted, memory  806  can include at least one of a random access memory (RAM), a read-only memory (ROM), a static random access memory (SRAM), a dynamic random access memory (DRAM), or other suitable types of memory devices or circuits. 
     As depicted, data storage  808  is connected to communications framework  804  and can store data, program code, or other information. Instructions in program code can be loaded from data storage  808  into memory  806  for processing by processor unit  802 . Data storage  808  can comprise at least one of a hard disk drive, a flash drive, a solid-state disk drive, an optical drive, or some other suitable type of data storage device or system. 
     In this illustrative example, communications unit  810  provides for communications with other data processing systems or devices. In these illustrative examples, communications unit  910  includes at least one of a network interface card, a wireless communications device, a universal serial bus port, or other suitable device. 
     Display  812  is connected to communications framework  804  and provides a mechanism to display information to a user. In this example, display  812  can be a touch screen display, which enables receiving user input through this display. 
     In this illustrative example, audio interface  814  is connected to communications framework  804 . As depicted, audio interface  814  can include hardware, software, or both that control the operation of audio output device  816  and audio sensor  818  in audio interface  814 . Audio output device  816  is hardware that is capable of generating audio signals for output and can include at least one of a paper cone speaker, an audio transducer, a line out jack, a digital to analog converter (DAC), or other type of audio device. Audio sensor  818  is hardware that is capable of detecting sounds. For example, audio sensor  818  can be comprised of at least one of a microphone, a fiber-optic microphone, a laser microphone, a microelectronic mechanical system (MEMS), a transducer, a line input jack and associated circuitry, or an analog to digital converter (ADC). 
     The illustration of client device  800  is an example of one manner in which client device  800  can be implemented. This illustration is not meant to limit the manner in which client device  800  can be embodied in other illustrative examples. For example, audio output device  816  and audio sensor  818  can be implemented as a single component. When audio output device  816  is a loud speaker, audio sensor  818  can also be implemented using the loud speaker. 
     Turning now to  FIG. 9 , a block diagram of a data processing system is depicted in accordance with an illustrative embodiment. Data processing system  900  can be used to implement server computer  104 , server computer  106 , client devices  110 , in  FIG. 1 . Data processing system  900  can also be used to implement computer system  204  in  FIG. 2 . In this illustrative example, data processing system  900  includes communications framework  902 , which provides communications between processor unit  904 , memory  906 , persistent storage  908 , communications unit  910 , input/output (I/O) unit  912 , and display  914 . In this example, communications framework  902  takes the form of a bus system. 
     Processor unit  904  processes instructions for software that can be loaded into memory  906 . Processor unit  904  include one or more processors. For example, processor unit  904  can be selected from at least one of a multicore processor, a central processing unit (CPU), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a network processor, or some other suitable type of processor. 
     Memory  906  and persistent storage  908  are examples of storage devices  916 . A storage device is any piece of hardware that is capable of storing information, such as, for example, without limitation, at least one of data, program code in functional form, or other suitable information either on a temporary basis, a permanent basis, or both on a temporary basis and a permanent basis. Storage devices  916  may also be referred to as computer-readable storage devices in these illustrative examples. Memory  906 , in these examples, can be, for example, a random-access memory or any other suitable volatile or non-volatile storage device. Persistent storage  908  may take various forms, depending on the particular implementation. 
     For example, persistent storage  908  may contain one or more components or devices. For example, persistent storage  908  can be a hard drive, a solid-state drive (SSD), a flash memory, a rewritable optical disk, a rewritable magnetic tape, or some combination of the above. The media used by persistent storage  908  also can be removable. For example, a removable hard drive can be used for persistent storage  908 . 
     Communications unit  910 , in these illustrative examples, provides for communications with other data processing systems or devices. In these illustrative examples, communications unit  910  is a network interface card. 
     Input/output unit  912  allows for input and output of data with other devices that can be connected to data processing system  900 . For example, input/output unit  912  may provide a connection for user input through at least one of a keyboard, a mouse, or some other suitable input device. Further, input/output unit  912  may send output to a printer. Display  914  provides a mechanism to display information to a user. 
     Instructions for at least one of the operating system, applications, or programs can be located in storage devices  916 , which are in communication with processor unit  904  through communications framework  902 . The processes of the different embodiments can be performed by processor unit  904  using computer-implemented instructions, which may be located in a memory, such as memory  906 . 
     These instructions are referred to as program code, computer usable program code, or computer-readable program code that can be read by a processor in processor unit  904 . The program code in the different embodiments can be embodied on different physical or computer-readable storage media, such as memory  906  or persistent storage  908 . 
     Program code  918  is located in a functional form on computer-readable media  920  that is selectively removable and can be loaded onto or transferred to data processing system  900  for processing by processor unit  904 . Program code  918  and computer-readable media  920  form computer program product  922  in these illustrative examples. In the illustrative example, computer-readable media  920  is computer-readable storage media  924 . 
     In these illustrative examples, computer-readable storage media  924  is a physical or tangible storage device used to store program code  918  rather than a medium that propagates or transmits program code  918 . 
     Alternatively, program code  918  can be transferred to data processing system  900  using a computer-readable signal media. The computer-readable signal media can be, for example, a propagated data signal containing program code  918 . For example, the computer-readable signal media can be at least one of an electromagnetic signal, an optical signal, or any other suitable type of signal. These signals can be transmitted over connections, such as wireless connections, optical fiber cable, coaxial cable, a wire, or any other suitable type of connection. 
     The different components illustrated for data processing system  900  are not meant to provide architectural limitations to the manner in which different embodiments can be implemented. In some illustrative examples, one or more of the components may be incorporated in or otherwise form a portion of, another component. For example, the  906 , or portions thereof, may be incorporated in processor unit  904  in some illustrative examples. The different illustrative embodiments can be implemented in a data processing system including components in addition to or in place of those illustrated for data processing system  900 . Other components shown in  FIG. 9  can be varied from the illustrative examples shown. The different embodiments can be implemented using any hardware device or system capable of running program code  918 . 
     Thus, the illustrative embodiments of the present invention provide a computer-implemented method, computer system, and computer program product for generating an audio communication. An urgency for a user is determined by a computer system in response to detecting a trigger event in a verbal communication from the user. A frequency modulator is selected by the computer system from a plurality of frequency modulators based on the urgency determined to form a selected frequency modulator. A frequency of words in an audio communication is modulated by the computer system using the selected frequency modulator to form a modulated audio communication, wherein the modulated audio communication comprises a natural language response generated in response to the trigger event. The modulated audio communication is sent by the computer system to an audio output device. 
     In the different illustrative examples, the urgency for a user can be determined. This determination can be made by determining the situation the user and the urgency of the situation. The frequency modulator can be selected and used to modulate the natural language response in the audio communication to provide a frequency that is appropriate for the urgency of the situation for the user. 
     In yet other illustrative examples, one or more frequency modulators can be selected to modulate the natural language response in the audio communication based on the urgency of one or more portions of the natural language response. In still other illustrative examples, an amplitude of the audio communications can also be modulated based on the urgency. Further, the selection of the frequency modulator can change as the urgency changes. For example, the urgency within a situation such as a flat tire can change from critical to normal depending on where the user is located and whether the user has stopped the vehicle. In this manner, the audio communication can have a frequency that changes as the urgency in the situation where the user changes. 
     The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiment. The terminology used herein was chosen to best explain the principles of the embodiment, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed here.