Abstract: In one embodiment, the method of processing telephony sessions includes: communicating with an application server using an application layer protocol; processing telephony instructions with a call router; and creating call router resources accessible through a call router Application Programming Interface (API). In another embodiment, the system for processing telephony sessions includes: a call router, a URI for an application server, a telephony instruction executed by the call router, and a call router API resource.

Abstract: Method and apparatus for automatically predicting lexical sememes using a lexical dictionary, comprising inputting a word, retrieving the word's semantic definition and sememes corresponding to the word from an online dictionary, setting each of the retrieved sememes as a candidate sememe, inputting the word's semantic definition and candidate sememe, and estimating the probability that the candidate sememe can be inferred from the word's semantic definition.

Abstract: Methods and systems for dynamically updating machine learning models that provide conversational responses through the use of a configuration file that defines modifications and changes to the machine learning model are disclosed. For example, the configuration file may be used to define an expected behavior and required attributes for instituting modifications and changes (e.g., via a mutation algorithm) to the machine learning model.

Abstract: The present technique relates to an information processing apparatus and an information processing method that can improve the convenience of a voice AI assistance service used in coordination with content. A first information processing apparatus including an insertion unit that inserts a token, which is related to use of a voice AI assistance service in coordination with content, into an audio stream of the content and a second information processing apparatus including a detection unit that detects the inserted token from the audio stream of the content can be provided to improve the convenience of the voice AI assistance service used in coordination with the content. The present technique can be applied to, for example, a system in coordination with the voice AI assistance service.

Abstract: An electronic device performing voice recognition on user utterance based on first voice assistance. The electronic device may receive information on recognition characteristic of second voice assistance for user utterance from an external device and adjust recognition characteristic of the first voice assistance based on the information on the recognition characteristic of the second voice assistance.

Abstract: The method S200 can include: at an aircraft, receiving an audio utterance from air traffic control S210, converting the audio utterance to text, determining commands from the text using a question-and-answer model S240, and optionally controlling the aircraft based on the commands S250. The method functions to automatically interpret flight commands from the air traffic control (ATC) stream.

Abstract: The speech processing apparatus 100 includes an air microphone speech recognition unit 101 which recognizes speech from an air microphone 200 acquiring speech through air, a wearable microphone speech recognition unit 102 which recognizes speech from a wearable microphone 300, a sensing unit 103 which measures environmental conditions, a weight decision unit 104 which calculates the weights for recognition results of the air microphone speech recognition unit 101 and the wearable microphone speech recognition unit 102 on the basis of the environmental conditions, and a combination unit 105 which combines the recognition results outputted from the air microphone speech recognition unit 101 and the wearable microphone speech recognition unit 102, using the weights.

Abstract: The present disclosure provides a method for intelligent automated chatting. A conversation with a user is performed by using a first identity of a first artificial intelligence entity. A message is received from the user in the conversation. Matching rates between the message and trigger contents of other artificial intelligence entities are scored. A second artificial intelligence entity is selected from the other artificial intelligence entities based on the matching rates. A conversation with the user is performed by using a second identity of the second artificial intelligence entity by switching from the first identity of the first artificial intelligence entity to the second identity of the second artificial intelligence entity.

Abstract: An electronic communication method and system for providing private communications from one or more advisors to a participant of an electronic communication are provided. Exemplary methods include establishing an electronic communication between two or more participants (e.g., using a first communication session) and establishing a private session between an advisor and one or more of the participants.

Abstract: This disclosure describes systems and methods that identify activities for which scripts can be built to perform an activity when requested by a user. The scripts can be voice-activated by a defined customized voice command and can include delivery preferences. The user's identity can be verified by analyzing voice biometrics of the customized voice command. After performance of the activity, results can be delivered to the device in the format indicated in the script.

Abstract: Provided is an acquisition unit configured to, in a case where a predetermined function is newly added as a function related to a communication apparatus and of which execution is instructed with a voice input to a voice control device, after an input from the user who permits the execution of the at least one function is performed. The acquisition unit acquires information that is based on a predetermined voice input that indicates whether to permit the execution of the predetermined function and that has been received by voice from the user by the voice control device.

Abstract: The present disclosure provides a conveyance system and the like capable of preferably conveying a conveyed object in accordance with a state of the conveyed object. The conveyance system includes a conveyance robot, a drive controller, which is a controller, an image data acquisition unit, and a setting unit. The conveyance robot conveys the conveyed object. The drive controller controls an operation of the conveyance robot. The image data acquisition unit acquires image data obtained by capturing images of the conveyed object. The setting unit sets an operation parameter of the conveyance robot in the drive controller based on the acquired image data.

Abstract: Systems and methods for altering communications captured by an incident recording device are provided. An incident recording may be captured by a recording device. The incident recording may comprise audio data. A communication activation signal may be detected by the recording device. The communication activation signal may be followed by communication audio data and the communication audio data may be captured in the audio data. Based on detecting the communication activation signal, the recording device may alter the audio data of the incident recording to at least partially alter the communication audio data captured in the audio data.

Abstract: A voice interaction method is provided. The method is applied to a wearable set and includes: collecting voice information through at least two microphones; processing the voice information and determining that the voice information comprises an effective voice instruction; wherein the effective voice instruction is issued by a user for a mobile terminal; and transmitting the effective voice instruction to the mobile terminal. In an embodiment, the processing of the voice information is assigned to an external device, which reduces the power consumption of a mobile terminal; and voice information is collected by at least two microphones to improve an efficiency and quality of a voice collection.

Abstract: An artificial intelligence system and method are disclosed herein. The system includes a processor which implements the method, including: receiving by an input unit a first user input including a request to execute a task using at least one of the electronic device or an external device, transmitting by a wireless communication unit first data associated with the first user input to an external server, receiving a first response from the external server including information associated with at least one of the first user input and a sequence of electronic device states for performing at least a portion of the task, receiving a second user input assigning at least one of a voice command and a touch operation received by a touch screen display as the request to perform the task, and transmitting second data associated with the second user input to the external server.

Abstract: Techniques are described for a contextual natural language understanding (cNLU) framework that is able to incorporate contextual signals of variable history length to perform joint intent classification (IC) and slot labeling (SL) tasks. A user utterance provided by a user within a multi-turn chat dialog between the user and a conversational agent is received. The user utterance and contextual information associated with one or more previous turns of the multi-turn chat dialog is provided to a machine learning (ML) model. An intent classification and one or more slot labels for the user utterance are then obtained from the ML model. The cNLU framework described herein thus uses, in addition to a current utterance itself, various contextual signals as input to a model to generate IC and SL predictions for each utterance of a multi-turn chat dialog.

Abstract: A speech-processing system configured to determine entities corresponding to ambiguous words such as anaphora (“he,” “she,” “they,” etc.) included in an utterance. The system may associate incoming utterances with a speaker identification (ID), device ID, and other data. The system then tracks entities referred to in utterances so that if a later utterance includes an ambiguous entity reference, the system may take the speaker ID, device ID, etc. from the ambiguous reference, along with the text of the utterance and other data, and compare that information to previously mentioned entities (or other entities that may be relevant) to identify the entity mentioned in the ambiguous statement. Once the entity is determined, the system may then complete command processing of the utterance using the identified entity.

Abstract: Disclosed is an electronic apparatus. The electronic apparatus includes a first communicator, a second communicator; and a processor configured to determine whether or not an external electronic apparatus outputting input speech is connectable to a network connectable through the first communicator, based on the input speech, and to transmit a signal for controlling the external electronic apparatus to the external electronic apparatus through the first communicator or the second communicator depending on whether or not the external electronic apparatus is connectable to the network.

Abstract: An artificial intelligence device includes a microphone configured to receive a speech command, a speaker, a communication unit configured to perform communication with an external artificial intelligence device, and a processor configured to receive a wake-up command through the microphone, acquire a first speech quality level of the received wake-up command, receive a second speech quality level of the wake-up command input to the external artificial intelligence device from the external artificial intelligence device through the communication unit, output a notification indicating that the artificial intelligence device is selected as an object to be controlled through the speaker, when the first speech quality level is larger than the second speech quality level, receive an operation command through the microphone, acquire an intention of the received operation command and transmit the operation command to an external artificial intelligence device which will perform operation corresponding to the operati

Abstract: Conversational understanding systems allow users to conversationally interface with a computing device. In examples, a query may be received that includes a request for execution of a task. A data exchange task definition may be accessed. The data exchange task definition assists a conversational understanding system in managing task state tracking for information needed for task execution. Using the data exchange task definition, a per-turn policy for interacting with the user computing device is generated based on the state of a dialogue with a computing device and an evaluation of a process flow chart provided by a task owner resource. The task owner resource may be independent from the conversational understanding system. A response to the query may be generated and output based on the per-turn policy. In examples, the per-turn policy is used to generate one or more responses during a dialogue with a user via a computing device.

Abstract: A chat input identifier may receive various chat inputs based on voice or text inputs from a user. The chat input identifier may apply different filters to the chat inputs to identify one or more chat correction pairs (e.g., chat input with errors, corrected chat input) from among the plurality of chat inputs. The chat correction pairs are used to train an auto-correction model. The trained auto-correction model receives a given chat input that has one or more errors. The auto-correction model processes the given chat input to generate a corrected version of the given chat input (without the need to obtain a correction from the user). The corrected chat input is then provided to a dialog-driven application.

Abstract: A computer system configured for autonomous learning of entity values is provided. The computer system includes a memory that stores associations between entities and fields of response data. The computer system also includes a processor configured to receive a request to process an intent; generate a request to fulfill the intent; transmit the request to a fulfillment service; receive, from the fulfillment service, response data specifying values of the fields; identify the values of the fields within the response data; identify the entities via the associations using the fields; store, within the memory, the values of the fields as values of the entities; and retrain a natural language processor using the values of the entities.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for hotword detection on multiple devices are disclosed. In one aspect, a method includes the actions of receiving, by a first computing device, audio data that corresponds to an utterance. The actions further include determining a first value corresponding to a likelihood that the utterance includes a hotword. The actions further include receiving a second value corresponding to a likelihood that the utterance includes the hotword, the second value being determined by a second computing device. The actions further include comparing the first value and the second value. The actions further include based on comparing the first value to the second value, initiating speech recognition processing on the audio data.

Abstract: Stepwise relationship cadence management can include generating a discourse cadence and confidence (DCC) measure based on a response message. The response message is made in replying to an originating message during a multi-party discourse over an electronic communication channel. The DCC measure indicates a likelihood of improving cadence and confidence with respect to an originator of the originating message and is based on a stepwise relational confidence model (SRCM) generated from an analysis of a plurality of prior multi-party discourses. Stepwise relationship cadence management can also include prompting a user to provide a follow-on message in response to determining that the response message made in replying to the originating message is not likely to improve cadence and confidence.

Abstract: Embodiments of the present disclosure provide an interactive method of a robot, an interactive device of a robot and a device. The method includes: obtaining voice information input by an interactive object, and performing semantic recognition on the voice information to obtain a conversation intention; obtaining feedback information corresponding to the conversation intention based on a conversation scenario knowledge base pre-configured by a simulated user; and converting the feedback information into a voice of the simulated user, and playing the voice to the interactive object.

Abstract: Systems and methods are disclosed for creating a machine generated avatar. A machine generated avatar is an avatar generated by processing video and audio information extracted from a recording of a human speaking a reading corpora and enabling the created avatar to be able to say an unlimited number of utterances, i.e., utterances that were not recorded. The video and audio processing consists of the use of machine learning algorithms that may create predictive models based upon pixel, semantic, phonetic, intonation, and wavelets.

Abstract: A computing system facilities live and robo-advising sessions, and transitions therebetween based on detection of triggers. The computing system may extract voice inputs of a user from ambient sounds captured using a sound sensor. Based on an analysis of the voice inputs and detection of corresponding triggers, the computing system may initiate a robo-advising session, or a live communication session between a user computing device and an advisor computing device. Detection of another trigger during the robo-advising session or the live communication session may lead to a transition to a live communication session or a robo-advising session, respectively.

Abstract: In one aspect, a device includes at least one processor, a touch-enabled display accessible to the at least one processor, and storage accessible to the at least one processor. The storage includes instructions executable by the at least one processor to detect a hover of a body part of a user or other physical object above the touch-enabled display, where the hover does not include the physical object physically touching the touch-enabled display. The instructions are also executable to identify a graphical object underneath the hover and to cache data associated with the graphical object prior to the graphical object being selected based on the physical object physically touching the touch-enabled display.

Abstract: A method, computer program product, and computing system for enabling usage of a conversational application by a plurality of users; gathering usage data concerning usage of the conversational application by the plurality of users; defining a visual representation of the conversational application; and overlaying the usage data onto the visual representation of the conversational application to generate visual traffic flow data.

Abstract: Implementations set forth herein allow a user to access a first application in a foreground of a graphical interface, and simultaneously employ an automated assistant to respond to notifications arising from a second application. The user can provide an input, such as a spoken utterance, while viewing the first application in the foreground in order to respond to notifications from the second application without performing certain intervening steps that can arise under certain circumstances. Such intervening steps can include providing a user confirmation, which can be bypassed, and/or time-limited according to a timer, which can be displayed in response to the user providing a responsive input directed at the notification. A period for the timer can be set according to one or more characteristics that are associated with the notification, the user, and/or any other information that can be associated with the user receiving the notification.

Abstract: The present disclosure provides a signal processing device that includes: a signal collector configured to obtain an image to be processed, a signal collector configured to collect an input signal, an instruction converter configured to convert the signal into an image processing instruction according to a target signal instruction conversion model, an image processor configured to edit the image to be processed according to the image processing instruction and a target image processing model to obtain a result image. Examples taught in the present disclosure implements a user command to process images, which saves users' time spent in learning image processing software prior to image processing and improves user experience.

Abstract: The present disclosure relates to chatbot systems, and more particularly, to techniques for identifying an intent for an utterance based on semantic framing. For an input utterance, a semantic frame is generated. The semantic frame includes semantically relevant grammatical relations and corresponding words identified in the utterance. The semantically relevant grammatical relations define context and relationships of words in the utterance. The semantic frame is used to identify an intent for the utterance, based on an intent model. The intent model maps features to corresponding words for a given intent. The semantic frame is compared to a plurality of intent models, and a best-matching intent model is used to identify the intent for the utterance.

Abstract: A voice recognition apparatus in a motor vehicle is configured to recognize at least one voice command, which is linked to at least one condition and which is related to the actuation of at least two functional units of the motor vehicle by a control device to provide voice-based operation of the motor vehicle by a vehicle occupant. The control apparatus is configured to generate, in accordance with the voice command, which is recognized by the voice recognition apparatus, a rule for actuating the at least two functional units according to the generated rule.

Abstract: A method for controlling operation of an appliance by a user through voice control includes at least the steps of: detecting, by the appliance, a control action performed by the user on the appliance; activating a voice control system by the appliance; capturing, by the voice control system, a voice input from the user as a captured voice input; recognizing, by the voice control system, a piece of information and/or an instruction in the captured voice input from the user as a recognized information and/or instruction; and executing, by the voice control system, a user control action on the appliance in accordance with the recognized information and/or instruction.

Abstract: An electronic device and method are disclosed herein. The electronic device includes a microphone, a camera, an output device, a memory, and a processor. The processor implements the method, including receiving a voice input and/or capturing an image, and analyze the first voice input or the image to determine at least one of a user's intent, emotion, and situation based on predefined keywords and expressions, identifying a category based on the input, selecting first information based on the category, selecting and outputting a first query prompting confirmation of output of the first information, detect a first responsive input to the first query, and when a condition to output the first information is satisfied, output a second query, detecting a second input responsive to the second query, and selectively outputting the first information based on the second input.

Abstract: A computerized personal assistant communicatively couples to a computer database including a plurality of available skills for the computerized personal assistant. The computerized personal assistant recognizes a current context of the user. The computerized personal assistant operates a previously-trained machine learning classifier to assess a match confidence for a candidate skill, the match confidence indicating a quality of match between the current context and a reference context previously associated with the candidate skill. The computerized personal assistant executes instructions defining an assistive action associated with the candidate skill responsive to the match confidence exceeding a predefined match confidence threshold. The computerized personal assistant executes the instructions defining a complementary help action associated with the candidate skill responsive to the match confidence not exceeding the predefined match confidence threshold.

Abstract: An example monitoring device for detecting and measuring a vital sign of a subject includes: a base; a battery mounted to the base; first and second transceivers attached to the base at opposing angles, and powered by the battery to transmit pulses and receive reflected pulses; an antenna powered by the battery, and configured to wirelessly transmit data acquired from the first and second transceivers; and a computing device powered by the battery, and operatively coupled to the first and second transceivers and the antenna, the computing device having a processing device and a memory storing instructions that, when executed by the processing device, cause the monitoring device to determine a respiration rate by detecting a cyclical change in distance based on the reflected pulses.

Abstract: Described herein are systems, methods, and apparatus for determining audio context between an audio source and an audio sink and selecting signal profiles based at least in part on that audio context. The signal profiles may include noise cancellation which is configured to facilitate operation within the audio context. Audio context may include user-to-user and user-to-device communications.

Abstract: A system includes a first microphone that captures audio, a communication module communicatively coupled to the first microphone, a logic circuit communicatively coupled to the first microphone and communication module, a speaker operatively coupled to the logic circuit, and an interaction element. The interaction element and logic circuit are configured to initiate control of audio content for output from the speaker in response to at least one voice command detected in captured audio. Other embodiments are disclosed.

Abstract: In certain embodiments, nuance-based augmentation of gesture may be facilitated. In some embodiments, a video stream depicting sign language gestures of an individual may be obtained via a wearable device associated with a user. A textual translation of the sign language gestures in the video stream may be determined. Emphasis information related to the sign language gestures may be identified based on an intensity of the sign language gestures. One or more display characteristics may be determined based on the emphasis information. The textual translation may be caused to be displayed to the user via the wearable device according to the one or more display characteristics. In some embodiments, a unique voice profile for the individual may be determined. A spoken translation of the sign language gestures may be generated according to the textual translation, the unique voice profile, and the emphasis information.

Abstract: Disclosed is a digital audio tampering forensics method based on phase offset detection, comprising: multiplying a signal to be identified with a time label to obtain a modulation signal of the signal to be identified; then, performing a short-time Fourier transform on the signal to be identified and the modulation signal to obtain a signal power spectrum and a modulation signal power spectrum; computing group delay characteristics by using the signal power spectrum and the modulation signal power spectrum; computing a mean value of the group delay characteristics, and then using the mean value results for smoothing computation to obtain phase information of a current frame signal; computing a dynamic threshold by using the phase information of the current frame signal, and then deciding whether the signal is tampered by using the dynamic threshold and the phase information of the current frame signal.

Abstract: Systems and methods are described to enable a device of a user to automatically join an ongoing conference, where the device is not currently joined to the conference. A first audio signature is generated based on voices of users already in the conference, and a second audio signature is generated based on an audio signal captured by a microphone of the device associated with the first user when the device associated with the first user was not joined to the conference. The first audio signature and the second audio signature are compared, and in response to determining that first audio signature matches the second audio signature, the device associated with the first user is joined to the conference.

Abstract: An electronic device and a controlling method are provided. The controlling method of the electronic device includes transmitting a signal to a plurality of external devices communicatively connected to the electronic device, receiving, from each of the plurality of external devices, intensity information of the signal sensed by an external device and identification information of an external device, determining at least one external device that is positioned in a same space as the electronic device, from among the plurality of external devices, based on the response signal, designating the at least one external device and the electronic device as a device group, and controlling the device group based on the user command, when a user command is input to at least one device from among the device groups.

Abstract: Techniques for implementing multiple wakeword detectors on a single device are described. A digital signal processor (DSP) of the device may initially include an untrained wakeword detection component. The wakeword detection component of the DSP may be trained by engaging a user to speak particular utterances. Once a companion application is configured to implement a wakeword detection component, the companion application's wakeword detection component may be trained specific to the user of the device. Once the companion application's wakeword detection component is trained, the DSP wakeword detection component may be deactivated or its accuracy adjusted.

Abstract: A device can perform device arbitration, even when the device is unable to communicate with a remote system over a wide area network (e.g., the Internet). Upon detecting a wakeword in an utterance, the device can wait a period of time for data to arrive at the device, which, if received, indicates to the device that another speech interface device in the environment detected an utterance. If the device receives data prior to the period of time lapsing, the device can determine the earliest-occurring wakeword based on multiple wakeword occurrence times, and may designate whichever device that detected the wakeword first as the designated device to perform an action with respect to the user speech. To account for differences in sound capture latency between speech interface devices, a pre-calculated time offset value can be applied to wakeword occurrence time(s) during device arbitration.

Abstract: Among other things, a developer of an interaction application for an enterprise can create items of content to be provided to an assistant platform for use in responses to requests of end-users. The developer can deploy the interaction application using defined items of content and an available general interaction model including intents and sample utterances having slots. The developer can deploy the interaction application without requiring the developer to formulate any of the intents, sample utterances, or slots of the general interaction model.

Abstract: Systems and methods for device control by a natural language processing system are disclosed. A user may desire to utilize a voice-enabled device to associate an accessory device with a hub device without having to utilize third-party software associated with the accessory device and/or the hub device. The user may provide a user utterance to associate the accessory device with the hub device. Audio data corresponding to the user utterance may be analyzed and utilized to generate and send directive data to a third-party remote system to transition the hub device to a join mode. Upon association completion, audio may be output confirming that the association has been established successfully.

Abstract: Embodiments of this application disclose a voiceprint recognition method performed by a computer. After obtaining a to-be-recognized target voice message, the computer obtains target feature information of the target voice message by using a voice recognition model, the voice recognition model being obtained through training according to a first loss function and a second loss function. Next, the computer determines a voiceprint recognition result according to the target feature information and registration feature information, the registration feature information being obtained from a voice message of a to-be-recognized object using the voiceprint recognition model. The normalized exponential function and the centralization function are used for jointly optimizing the voice recognition model, and can reduce an intra-class variation between depth features from the same speaker.

Abstract: Provided is a system, server, and method for speech recognition capable of collectively setting a plurality of setting items for device control through an utterance of a single sentence provided in the form of natural language. The system includes: a home appliance configured to receive a speech command that is generated through an utterance of a single sentence for control of the home appliance; and a server configured to receive the speech command in the single sentence from the home appliance and interpret the speech command of the single sentence through multiple intent determination.

Abstract: Disclosed is an electronic device. The electronic device includes a processor configured to execute one or more instructions stored in a memory to: control a receiver to receive a speech signal; determine whether the received speech signal includes speech signals of a plurality of different speakers; when the received speech signal includes the speech signals of the plurality of different speakers, detect feature information from a speech signal of each speaker; determine relations between pieces of speech content of the plurality of different speakers, based on the detected feature information; determine a response method based on the determined relations between the pieces of speech content; and control the electronic device such that an operation of the electronic device is performed according to the determined response method.