Abstract: Methods, systems, apparatus, including computer programs encoded on a computer storage medium, for a user device to learn offline voice actions. In one aspect, the method includes actions of detecting, by the user device, an utterance at a first time when the user device is connected to a server by a network, providing, by the user device, the utterance to the server using the network, receiving, by the user device and from the server, an update to the grammar of the user device, detecting, by the user device, a subsequent utterance of the utterance at a second time when the user device is not connected to the server by a network, and in response to detecting, by the user device, the subsequent utterance of the utterance at the second time, identifying, by the user device, an operation to perform based on (i) the subsequent utterance, and (ii) the updated grammar.

Abstract: According to an embodiment, an electronic device comprises: a communication module comprising communication circuitry, a memory, and at least one processor.

Abstract: An information processing apparatus is connected to a voice processing server that analyzes text data transmitted from a voice input/output apparatus that converts an instruction by an utterance of a user to the text data and outputs the text data, and outputs an instruction obtained by analysis and utterance language information indicating a language of the utterance, and the information processing apparatus includes: a communicator that communicates with the voice processing server; a destination searcher that determines on the basis of the utterance language information whether to include a space character in a target of the search, and searches for a name indicated in a search character string from a destination list on the basis of a result of the determination; and a hardware processor that performs control to transmit a search result of a destination by the destination searcher to the voice processing server via the communicator.

Abstract: A donation processing system receives a text message from a donor indicating that they would like to make a donation to a non-profit organization. In response to the text message, a response message indicating the particulars of the donation including the donation amount and the non-profit organization is sent to the user. The donor reviews the information and, if the information is correct, a confirmation message is sent from the donor in response to the response message. The confirmation message confirms the donation. The donation is then made to the non-profit organization in response to the confirmation message.

Abstract: A multi-tenant system performs custom configuration of a tenant-specific chatbot to process and act upon natural language requests. The multi-tenant system configures the tenant-specific chatbots without requiring tenant-specific training. The multi-tenant system providing a user interface for configuring a tenant-specific set of permitted actions. The multi-tenant system determines a set of example phrases for each of the selected permitted actions. The multi-tenant system receives a natural language request from a user and identifies the action that the user wants to perform. The multi-tenant system uses a neural network to compare the natural language request with example phrases to identify an example phrase that matches the natural language request. The multi-tenant system performs the action corresponding to the matching example phrase.

Abstract: Methods and apparatuses are described for intelligent dialogue recovery in virtual assistant communication sessions. A chat session is established between a virtual assistant (VA) and a remote device. A primary dialogue is created between the VA and the remote device, including (i) requesting from a first natural language processing (NLP) service an intent associated with user messages and (ii) waiting for a corresponding response. A secondary dialogue is created between the VA and the remote device that is synchronized to a state of the primary dialogue. When the response from the first NLP service succeeds, primary messages are generated and transmitted to the remote device in the primary dialogue. When the response from the first NLP service fails, an intent is requested from the second NLP service, and secondary messages are generated and transmitted to the remote device in the secondary dialogue.

Abstract: Typical graphical user interfaces and predefined data fields limit the interaction between a person and a computing system. An oral communication device and a data enablement platform are provided for ingesting oral conversational data from people, and using machine learning to provide intelligence. At the front end, an oral conversational bot, or chatbot, interacts with a user. On the backend, the data enablement platform has a computing architecture that ingests data from various external data sources as well as data from internal applications and databases. These data and algorithms are applied to surface new data, identify trends, provide recommendations, infer new understanding, predict actions and events, and automatically act on this computed information. The chatbot then provides audio data that reflects the information computed by the data enablement platform. The system and the devices, for example, are adaptable to various industries.

Abstract: A system, apparatus, and method for processing a natural language, and a computer readable recording medium are provided. The system includes a user device configured to receive a compound or complex sentence and a natural language processing apparatus configured to generate a plurality of control commands for the user device based on whether operations intended by a user are sequentially performable in the compound or complex sentence received from the user device.

Abstract: Systems and methods are disclosed for enabling verbal interaction with an NLUI application without relying on express wake terms. The NLUI application receives an audio input comprising a plurality of terms. In response to determining that none of the terms is an express wake term pre-programmed into the NLUI application, the NLUI application determines a topic for the plurality of terms. The NLUI application then determines whether the topic is within a plurality of topics for which a response should be generated. If the determined topic of the audio input is within the plurality of topics, the NLUI application generates a response to the audio input.

Abstract: A display device for displaying an utterance and information extracted from the utterance, includes an input/output interface configured to display display blocks for a series of dialogue scenes in chronological order of acquisition of utterances, each of the series of dialogue scenes being indicated by dialogue scene data stored in correspondence with utterance data indicating a corresponding one of the utterances, display dialogue scene information within each of the display blocks for the series of dialogue scenes, the dialogue scene information including the corresponding one of the utterances, an utterance type indicating a type of the corresponding one of the utterances, or utterance focus point information of the corresponding one of the utterances, and switch, based on an operation input, between displaying the dialogue scene information and not displaying the dialogue scene information within each of the display blocks for the series of dialogue scenes.

Abstract: A gateway device includes a call handling equipment (CHE) listener interface, an Internet Protocol (IP) interface, a provisioning engine, and a message parsing engine. The CPE listener interface forms a communication channel with a CHE and receives call event data from the CHE. The IP interface communicates with a cloud-based processing system. The provisioning engine receives, from the cloud-based processing system via the IP interface, instructions for parsing data from a data output format of the CHE into a consistent data format of the cloud-based processing system. The message parsing engine parses the call event data received from the CHE via the CHE listener interface, and formats the call event data according to the consistent data format. The gateway device transmits the formatted call event data to the cloud-based processing system via the IP interface.

Abstract: An IVR and chatbot, or other system, employing a language model, the language model resulting from a method and computer product encoding the method is available for preparing a domain or subdomain specific glossary. The method included using probabilities, word context, common terminology and different terminology to identify domain and subdomain specific language and a related glossary updated according to the method.

Abstract: Example methods, apparatus, systems and articles of manufacture are disclosed to determine tags for unknown media using multiple media features. Disclosed examples extract features from portions of the unknown media. Disclosed examples weight the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features. Disclosed examples search a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media, the list of suggested tags including relevancy scores for respective ones of the tags in the list. Disclosed examples assign a tag from the list of suggested tags to the unknown media based on a comparison of the relevancy score for the tag to a threshold.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for interleaving matrix operations of a gated activation unit. One of the methods includes receiving a plurality of weight matrices of a gated activation unit of the neural network, the gated activation unit having two or more layers, each layer defining operations comprising: (i) a matrix operation between a weight matrix for the layer and concatenated input vectors and (ii) a nonlinear activation operation using a result of the matrix operation. Rows of the plurality of weight matrices are interleaved by assigning groups of corresponding rows to respective thread blocks, each thread block being a computation unit for execution by an independent processing unit of a plurality of independent processing units of a parallel processing device.

Abstract: Systems and methods for correcting recognition errors in speech recognition systems are disclosed herein. Natural conversational variations are identified to determine whether a query intends to correct a speech recognition error or whether the query is a new command. When the query intends to correct a speech recognition error, the system identifies a location of the error and performs the correction. The corrected query can be presented to the user or be acted upon as a command for the system.

Abstract: A method, computer system, and a computer program product for context-based wake word threshold modification is provided. The present invention may include receiving an audio data generated by a computing device operating in a sleep mode. The present invention may include processing the received audio data to determine a context associated with a user of the computing device. The present invention may include in response to detecting a potential wake word in the received audio data, calculating a wake word confidence score associated with an accuracy of the detected potential wake word. The present invention may include retrieving a wake word threshold, wherein the wake word threshold is determined based on the context associated with the user of the computing device. The present invention may include, in response to the calculated wake word confidence score exceeding the retrieved wake word threshold, activating a wake mode of the computing device.

Abstract: A vehicle operation detection device includes sensors laid out in a vehicle along an axis in an opening-closing direction of a door of the vehicle. When the user moves a part of a body toward the sensors and a motion of moving the part of the body along the axis is detected, the sensors detect an opening-closing operation for the door. The vehicle operation detection device further includes light-emitting members laid out in the vehicle along the axis in the opening-closing direction and an operation direction indicator configured to drive the light-emitting members in sequence in a first direction in a fully-closed state of the door and drives the light-emitting members in sequence in a second direction in a fully-open state of the door.

Abstract: Provided is an apparatus that includes a voice recognition section that executes a voice recognition process on a user speech and a learning processing section that executes a process of updating a degree of confidence on the basis of an interaction made between a user and the information processing apparatus after the user speech. The degree of confidence is an evaluation value indicating the reliability of a voice recognition result of the user speech. The voice recognition section generates data on degrees of confidence in recognition of the user speech in which data plural user speech candidates based on the voice recognition result of the user speech are associated with the degrees of confidence which are evaluation values each indicating reliability of the corresponding user speech candidate.

Abstract: Techniques for processing incoming audio using multiple wakeword detectors are described. Audio data representing an utterance may be processed by different wakeword detectors that can detect different wakewords and are associated with different speech processing components. When a wakeword is detected by one of the wakeword detectors, it may be processed by the corresponding speech processing component.

Abstract: A hearing apparatus includes: a receiving unit configured to obtain a first speech signal; a processor configured to provide of an electrical output signal based on the first speech signal; and a receiver for providing an audio output signal based on the electrical output signal; wherein the hearing apparatus is configured to determine a first word count of the first speech signal, and update a total word count based on the first word count.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for speech recognition. One of the methods includes receiving first audio data corresponding to an utterance; obtaining a first transcription of the first audio data; receiving data indicating (i) a selection of one or more terms of the first transcription and (ii) one or more of replacement terms; determining that one or more of the replacement terms are classified as a correction of one or more of the selected terms; in response to determining that the one or more of the replacement terms are classified as a correction of the one or more of the selected terms, obtaining a first portion of the first audio data that corresponds to one or more terms of the first transcription; and using the first portion of the first audio data that is associated with the one or more terms of the first transcription to train an acoustic model for recognizing the one or more of the replacement terms.

Abstract: A setting facilitation apparatus (1400) includes a keyword input reception section (1410), a control command selection section (1420), and a specific control registration section (1430) and is used to facilitate setting of specific control in a control system (1001) that controls a control device through sound inputs. The keyword input reception section (1410) receives an input of information corresponding to a keyword. The control command selection section (1420) displays a certain control command to the control device (1010, 1020) on an edit screen (G) and receives selection of the control command. The specific control registration section (1430) registers a keyword (K) input by the keyword input reception section (1410) and the control command selected by the control command selection section (1420) to a specific control (DB 1104T) while associating the keyword and the control command with each other.

Abstract: A method for instantaneous learning in text-to-speech (TTS) during dialog includes receiving a user pronunciation of a particular word present in a query spoken by a user. The method also includes receiving a TTS pronunciation of the same particular word that is present in a TTS input where the TTS pronunciation of the particular word is different than the user pronunciation of the particular word. The method also includes obtaining user pronunciation-related features and TTS pronunciation related features associated with the particular word. The method also includes generating a pronunciation decision selecting one of the user pronunciation or the TTS pronunciation of the particular word that is associated with a highest confidence. The method also include providing the TTS audio that includes a synthesized speech representation of the response to the query using the user pronunciation or the TTS pronunciation for the particular word.

Abstract: In some examples, a method is disclosed. The method includes detecting, by a smart device, an audible utterance of a trigger word. The method also includes, responsive to the detection of the audible utterance of the trigger word, recording audio via the smart device. The method also includes processing, via the smart device, the recorded audio to determine whether the recorded audio contains a command for the smart device or a different smart device to perform an action. The method also includes, responsive to determining that the recorded audio includes a command for the smart device or a different smart device to perform the action, determining whether the command is serviceable by the smart device without involvement of the different smart device. The method also includes, responsive to determining whether the command is serviceable by the smart device without involvement of the different smart device, taking action regarding the command.

Abstract: Disclosed are systems, servers and methods for providing a novel framework that enables the unique cataloging and organization of audio files, upon which audio rendering experiences can be created and provided to requesting users, whether the users are individuals or third party partners. The disclosed framework enables audio files to be stripped down, uniquely stored, and then stitched together in a novel manner that previously did not exist within the computing arts. The disclosed systems and methods, therefore, provide a novel platform where audio is not just provided to consumers, but audio experiences are compiled from various types of audio formats and types in a unique, dynamically determined manner for a listening user.

Abstract: In one embodiment, a method includes receiving a user input at a client system, wherein the user input is associated with one or more intents and one or more slots, generating one or more first dialog acts based on the user input, calculating a task-confidence score based on one or more intent-confidence scores associated with the one or more intents, respectively, and one or more slot-confidence scores associated with the one or more slots, respectively, generating one or more second dialog acts modifying the one or more first dialog acts responsive to the task-confidence score being less than a threshold score, and presenting a response to the user input at the client system, wherein the response is based on one or more of the first dialog acts or the second dialog acts.

Abstract: A tool for managing text-item recognition systems such as NER (Named Entity Recognition) systems. The tool applies the system to a text corpus containing instances of text items, such as named entities, to be recognized by the system, and selecting from the text corpus a set of instances of text items which the system recognized. The tool tokenizes the text corpus such that each instance in the aforementioned set is encoded as a single token and processing the tokenized text via a word embedding scheme to generate a word embedding matrix. The tool, responsive to selecting a seed token corresponding to an instance in the aforementioned set, performs a nearest-neighbor search of the embedding space to identify a set of neighboring tokens for the seed token, and identifies the text corresponding to each neighboring token as a potential instance of a text item to be annotated.

Abstract: Computer-based natural language understanding of input and output for a computer interlocutor is improved using a method of classifying conversation segments from transcribed conversations. The improvement includes one or more methods of splitting transcribed conversations into groups related to a conversation ontology using metadata; identifying dominant paths of conversational behavior by counting the frequency of occurrences of the behavior for a given path; creating a conversation model comprising conversation behaviors, metadata, and dominant paths; and using the conversation model to assign a probability score for a matched input to the computer interlocutor or a generated output from the computer interlocutor.

Abstract: One or more processing devices derive values indicative of various aspects of how a particular service in an information technology (IT) environment is performing at a point in time or for a period of time. The values are derived by a search query over machine data associated with the one or more entities that provide the service. The one or more processing devices define and apply time varying static thresholds in respect to the values. A user (e.g., IT manager) may be enabled to manipulate or define multiple sets of KPI thresholds that vary over time.

Abstract: Method starts with processing, by a processor, audio signal to generate audio caller utterance and transcribed caller utterance. Processor generates identified task based on transcribed caller utterance. Processor samples audio caller utterance to generate samples of audio caller utterance. Processor generates loudness result based on loudness values of samples using loudness neural network associated with identified task. Processor generates pitch result based on pitch values of samples using pitch neural network associated with identified task. Processor generates tone result for each word in transcribed caller utterance using tone neural network associated with identified task. Using task completion probability neural network associated with identified task, processor generates task completion probability result that is based on at least one of: loudness result, pitch result, or tone result. Other embodiments are disclosed herein.

Abstract: The present disclosure is generally related to a data processing system to selectively invoke applications for execution. A data processing system can receive an input audio signal and can parse the input audio signal to identify a command. The data processing system can identify a first functionality of a first digital assistant application hosted on the data processing system in the vehicle and a second functionality of a second digital assistant application accessible via a client device. The data processing system can determine that one of the first functionality or the second functionality supports the command. The data processing system can select one of the first digital assistant application or the second digital assistant application based on the determination. The data processing system invoke one of the first digital assistant application or the second digital assistant application based on the selection.

Abstract: The present disclosure relates to a method and device for generating a finite state automata for recognizing a chemical name in a text, and a recognition method. According to an embodiment of the present disclosure, the method comprises substituting representation constants of categories of character segments appearing in an organic compound name set into the organic compound name set to obtain a conversion name set; updating the conversion name set based on a conversion name segment which repeatedly appears in the conversion name set; and generating the finite state automata based on the updated conversion name set.

Abstract: A speech recognition method includes receiving speech data, obtaining candidate texts corresponding to the speech data and respective scores of the candidate texts using a speech recognition model, adjusting the score of a current candidate text, from among the obtained candidate texts, in response to a text length of the current candidate text satisfying a condition determined based on text lengths of the obtained candidate texts, and determining a target text corresponding to the speech data, from among the obtained candidate texts and the current candidate texts.

Abstract: It is disclosed a voice pickup method and apparatus for an intelligent rearview mirror, an electronic device and a computer readable storage medium which relates to the technical field of vehicle-mounted equipment, and may be used in the field of automatic driving technologies. A voice pickup implementation of the intelligent rearview mirror according to some embodiments includes: acquiring an image of the interior of the vehicle; determining the position of a person in the vehicle with the image of the interior of the vehicle; and adjusting a beamforming direction of a microphone array according to the position of the person in the vehicle.

Abstract: An electronic apparatus configured to acquire information on a plurality of candidate texts corresponding to input speech of a user through a general speech recognition module, determine text corresponding to the input speech from among the plurality of candidate texts using a trained personal language model, and output the text as a result of speech recognition of the input speech.

Abstract: A electronic apparatus includes a display, a voice receiver configured to receive a user voice input, and a processor to obtain a first text from the user voice input that is received through the voice receiver based on a function corresponding to a first voice recognition related to a first language, based on an entity name not being included in the first text using the function corresponding to the first voice recognition related to the first language, obtain a second text corresponding to the entity name from of the user voice input based on a function corresponding to a second voice recognition related to a second language, and control the display to display a voice recognition result corresponding to the user voice input based on the first text and the second text.

Abstract: Systems and methods for detecting and analyzing audio in a media presentation environment to determine whether to replay missed portions of media content are disclosed herein. In an embodiment, one or more computing devices detect audio in a media presentation environment. The one or more computing devices determine whether the audio relates to the media being presented. If the audio does not relate to the media being presented, the one or more computing devices cause replaying a portion of the media presentation corresponding to when the audio was being detected.

Abstract: A semantic augmentation system includes a sensor with a computing system and a memory in communication with the computing system, the memory storing a plurality of endpoints. The computing system is configured to infer a first and a second semantic identity for an object, based on inputs from the sensor, project a coherent narrative and perform semantic augmentation towards a user. In further examples, the system infers a first narrative comprising two semantic identities and a second narrative wherein the system infers that a user observing view didn't infer the second semantic identity and further doesn't use the second semantic identity in the second narrative. It further, uses the corresponding narrative to remind the user to carry an item and/or credential in order to start an activity.

Abstract: Systems and methods of presenting interrupting content during human speech are disclosed. The proposed systems offer improved duplex communications in conversational AI platforms. In some embodiments, the system receives speech data and evaluates the data using linguistic models. If the linguistic models detect indications of linguistic irregularities such as mispronunciation, a smart feedback assistant can determine that the system should interrupt the speaker in near-real-time and provide feedback regarding their pronunciation. In addition, conversational irregularities may also be detected, causing the smart feedback assistant to interrupt with presentation of moderating guidance. In some cases, emotion models may also be utilized to detect emotional states based on the speaker's voice in order to offer near-immediate feedback. Users can also customize the manner and occasions in which they are interrupted.

Abstract: A multi faceted graphic user interface with multiple shells or layers may be provided for interaction with a user to speech enable interaction with applications and processes that do not necessarily have native support for speech input. The shells may be components of an operating system or of a parent application which supports such shells. Each shell has multiple facets for displaying applications and processes, and typically speech and other input is directed the application or process in the facet which has focus within the active shell. These multiple shells lend themselves to grouping of input or grouping of related applications and processes. For example, input from a speech recognizer, a mouse and a keyboard may each be directed at different shells; or a user may group related windows within various shells, such that all documents are displayed in one shell and all windows of an instant messaging application are displayed in another, thereby enabling better organization of work and work flow.

Abstract: A method of presenting product information in a vending machine may include detecting audio information from a consumer and converting the audio information to a text string. The method may include identifying a keyword in the text string, and determining products from a product database associated with the keyword. The method may include returning a list of the products that correspond to the keyword.

Abstract: Systems and processes for providing user-specific acoustic models are provided. In accordance with one example, a method includes, at an electronic device having one or more processors, receiving a plurality of speech inputs, each of the speech inputs associated with a same user of the electronic device; providing each of the plurality of speech inputs to a user-independent acoustic model, the user-independent acoustic model providing a plurality of speech results based on the plurality of speech inputs; initiating a user-specific acoustic model on the electronic device; and adjusting the user-specific acoustic model based on the plurality of speech inputs and the plurality of speech results.

Abstract: Techniques are disclosed relating to scoring partial matches between words. In certain embodiments, a method may include receiving a request to determine a similarity between an input text data and a stored text data. The method also includes determining, based on comparing one or more words included in the input text data with one or more words included in the stored text data, a set of word pairs and a set of unpaired words. Further, in response to determining that the set of unpaired words passes elimination criteria, the method includes calculating a base similarity score between the input text data and the stored text data based on the set of word pairs. The method also includes determining a scoring penalty based on the set of unpaired words and generating a final similarity score between the input text data and the stored text data by modifying the base similarity score based on the scoring penalty.

Abstract: A method for managing data includes obtaining, by a first data node, a notification, wherein the first data node is associated with a first power zone group (PZG), and in response to the notification: selecting a second data node, wherein the second data node is not associated with the first PZG, sending a data processing request to the second data node, obtaining a response based on the data processing request, wherein the response specifies a confirmation by the second data node to service the data processing request, storing a ledger entry in a ledger service that indicates the confirmation, and initiating a data transfer based on the data processing request, wherein the first data node is associated with the PZG based on a primary power source of the first data node.

Abstract: To provide more useful additional information to the user at a more effective timing. Provided is an information processing apparatus including an output control unit that controls an output of additional information related to a product purchased by a user. The output control unit controls an output of the additional information on the basis of delivery information about the product. In addition, provided is an information processing method that is executed by a processor, the information processing method including controlling an output of additional information related to a product purchased by a user. The controlling of an output includes controlling an output of the additional information on the basis of delivery information about the product.

Abstract: The present invention provides a pronunciation error detection apparatus capable of following a text without the need for a correct sentence even when erroneous recognition such as a reading error occurs.

Abstract: Some implementations are directed to selective invocation of a particular third-party (3P) agent by an automated assistant to achieve an intended action determined by the automated assistant during a dynamic dialog between the automated assistant and a user. In some of those implementations, the particular 3P agent is invoked with value(s) for parameter(s) that are determined during the dynamic dialog; and/or the particular 3P agent is selected, from a plurality of candidate 3P agents, for invocation based on the determined value(s) for the parameter(s) and/or based on other criteria. In some of those implementations, the automated assistant invokes the particular 3P agent by transmitting, to the particular 3P agent, a 3P invocation request that includes the determined value(s) for the parameter(s).

Abstract: An acoustic system and method is disclosed for providing spatial and temporal classification of a range of different types of sound producing targets in a geographical area. The system includes an optical signal transmitter arrangement for repeatedly transmitting, at multiple instants, interrogating optical signals into each of one or more optical fibres distributed across the geographical area and forming at least part of an installed fibre-optic communications network. An optical signal detector arrangement receives, during an observation period following each of the multiple instants, returning optical signals scattered in a distributed manner over distance along the one or more of optical fibres.

Abstract: Examples described herein provide for associating a network device to a network management system (NMS). Examples herein include determining, by a network orchestrator, a set of embeddings indicative of characteristics of the network device and each of a plurality of instances of the NMS. Examples herein include determining, by the network orchestrator for each of the plurality of instances, a probability score based on the set of embeddings, wherein the probability score is indicative of a likelihood of the network device to be associated with the instance. Examples herein further include, based on the probability score for each of the plurality of instances, selecting, by the network orchestrator, a first instance of the plurality of instances to associate with the network device. Examples herein include associating, by the network orchestrator, the network device to the first instance.

Abstract: The present invention allows for the capture and sentiment analysis of text the customer inputs into a chat, but never actually sends to the customer service representative (ghost text). The system captures this ghost text with a ghost capture system (GCS) software module. The GCS module analyzes the ghost text to generate metadata. The ghost text and metadata are used by a sentiment analysis engine to apply appropriate sentiment to the ghost text. The sentiment and ghost text are routed to a customer service representative (CSR). This provides the customer service agent with additional detail and information about a customer's emotions during a text chat conversation, allowing the CSR to determine a court of interaction not only based on the customer's response, but also based on the ghost text and the sentiment from the ghost text.