Abstract: An indication associated with an AI mode enabled by an AI system is received from a user with an affirmative opt-in status. A first task request associated with the user is identified. One or more instructions associated with the first task request are contextually recognized. The first task request is completed based on the contextually recognized one or more instructions.

Abstract: Example methods, apparatus and articles of manufacture to determine semantic information for audio are disclosed. Example apparatus disclosed herein are to process an audio signal obtained by a media device to determine values of a plurality of features that are characteristic of the audio signal, compare the values of the plurality of features to a first template having corresponding first ranges of the plurality of features to determine a first score, the first template associated with first semantic information, compare the values of the plurality of features to a second template having corresponding second ranges of the plurality of features to determine a second score, the second template associated with second semantic information, and associate the audio signal with at least one of the first semantic information or the second semantic information based on the first score and the second score.

Abstract: A system for determining intent in a voice signal receives a first voice signal that indicates to perform a task. The system sends a first response that comprises a hyperlink associated with a particular webpage used to perform the task. The system receives a second voice signal that indicates whether to access the hyperlink. The system determines intent of the second voice signal by comparing keywords of the second voice signal with keywords of the first response. The system activates the hyperlink in response to determining that the keywords of the second voice signal correspond to the keywords of the first response.

Abstract: Implementations set forth herein relate to an automated assistant that can operate as an interface between a user and a separate application to search application content of the separate application. The automated assistant can interact with existing search filter features of another application and can also adapt in circumstances when certain filter parameters are not directly controllable at a search interface of the application. For instance, when a user requests that a search operation be performed using certain terms, those terms may refer to content filters that may not be available at a search interface of the application. However, the automated assistant can generate an assistant input based on those content filters in order to ensure that any resulting search results will be filtered accordingly. The assistant input can then be submitted into a search field of the application and a search operation can be executed.

Abstract: A network validation system is described which may perform operations such as generating, analyzing, verifying, correcting, recommending, and deploying language, symbols, etc., such as domain specific language, configured to allow users to express their intent on the configuration and operation of a network, such as a cloud-based network. The network validation system may provide domain specific language that includes rules, statements, symbols, data, etc., configured to convey the intent of users on the configuration and operation of networks for purposes such as configuring and/or validating communication paths, testing or setting associated network object configurations, and may be employed to report violations in such configurations relative to user intent of the one or more users. The network validation system may also be employed to monitor such domain specific language and generate telemetry signaling, for example, that a rule has or has not been violated, actions a user may take, etc.

Abstract: Audio data, corresponding to an utterance spoken by a person within a detection range of a voice communications device, can include an audio message portion. The audio data can be captured and analyzed to determine the intent to send a message. Based at least in part upon that intent, a remaining portion of the audio data can be analyzed to determine the intended message target or recipient, as well as the portion corresponding to the actual message payload. Once determined, the audio file can be trimmed to the message payload, and the message payload of the audio data can be delivered as an audio message to the target recipient.

Abstract: One or more non-transitory computer readable media contain program instructions that, when executed, cause one or more processors to: receive first raw data including one or more first data points generated by a first object of a plurality of objects associated with one or more buildings; generate first input timeseries according to the one or more data points; access a database of interconnected smart entities, the smart entities including object entities representing each of the plurality of objects and data entities representing stored data, the smart entities being interconnected by relational objects indicating relationships between the smart entities; identify a first object entity representing the first object from a first identifier in the first input timeseries; identify a first data entity from a first relational object indicating a relationship between the first object entity and the first data entity; and store the first input timeseries in the first data entity.

Abstract: Methods, devices, and systems for processing audio information are disclosed. An exemplary method includes receiving an audio stream. The audio stream may be monitored by a low power integrated circuit. The audio stream may be digitized by the low power integrated circuit. The digitized audio stream may be stored in a memory, wherein storing the digitized audio stream comprises replacing a prior digitized audio stream stored in the memory with the digitized audio stream. The low power integrated circuit may analyze the stored digitized audio stream for recognition of a keyword. The low power integrated circuit may induce a processor to enter an increased power usage state upon recognition of the keyword within the stored digitized audio stream. The stored digitized audio stream may be transmitted to a server for processing. A response received from the server based on the processed audio stream may be rendered.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for computing numeric representations of words. One of the methods includes obtaining a set of training data, wherein the set of training data comprises sequences of words; training a classifier and an embedding function on the set of training data, wherein training the embedding function comprises obtained trained values of the embedding function parameters; processing each word in the vocabulary using the embedding function in accordance with the trained values of the embedding function parameters to generate a respective numerical representation of each word in the vocabulary in the high-dimensional space; and associating each word in the vocabulary with the respective numeric representation of the word in the high-dimensional space.

Abstract: The present invention relates to a system for the control of a medical implant in a mammal body. The system comprises a first and a second part being adapted for communication with each other. In the system the first part is adapted for implantation in the mammal body for the control of and communication with the medical implant, and the second part is adapted to be worn on the outside of the mammal body and adapted to receive control commands from a user and to transmit these commands to the first part.

Abstract: A pharmacy order facilitation method includes receiving a message; training a machine learning model; generating an intent; generating a response message; and transmitting the response message. A computing system includes a processor and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: receive a message; train a machine learning model; generate an intent; generate a response message; and transmit the response message. A computing system includes a mobile device; a server device configured to: train a machine learning model; analyze the inbound message; identify a customer intent; perform an action based on the customer intent; and transmit an outbound message.

Abstract: Embodiments of the present invention provide a speech recognition method and a terminal. The method includes: listening, by a speech wakeup apparatus, to speech information in a surrounding environment; when determining that the speech information obtained by listening matches a speech wakeup model, buffering, by the speech wakeup apparatus, speech information, of first preset duration, obtained by listening, and sending a trigger signal for triggering enabling of a speech recognition apparatus, where the trigger signal is used to instruct the speech recognition apparatus to read and recognize the speech information buffered by the speech wakeup apparatus; and recognizing first speech information buffered by the speech wakeup apparatus and the second speech information obtained by listening, to obtain a recognition result.

Abstract: A method of building a natural language understanding application is provided. The method includes receiving at least one electronic record containing programming code and creating executable code from the programming code. Further, the executable code, when executed by a processor, causes the processor to create a parse and an interpretation of a sequence of input tokens, the programming code includes an interpret-block and the interpret-block includes an interpret-statement. Additionally, the interpret-statement includes a pattern expression and the interpret-statement includes an action statement.

Abstract: The present technology extends to methods, systems, and computer program products for expanding semantic classes via user feedback. Aspects of the technology learn how a set of labels can be expanded from user-generated tags. Text labels applied by human reviewers to digital content can be inspected and compared to one another. When a threshold of human-generated text tags contain similar terminology, the set of labels can be expanded to define a representation of the similar terminology. Similar terminology can include terms that originate from the same base term, are synonyms, are more specific terms related to a general term category, etc. Similar terminology can be consolidated into a defining term that is used to generate a new (more granular) label or a new top level label. Accordingly, new semantic classes can be discovered from user-generated feedback. New semantic classes can provide a more granular representation of content item classification.

Abstract: The present disclosure relates to systems and methods for providing subtitle for a video. The video's audio is transcribed to obtain caption text for the video. A first machine-trained model identifies sentences in the caption text. A second model identifies intra-sentence breaks with in the sentences identified using the first machine-trained model. Based on the identified sentences and intra-sentence breaks, one or more words in the caption text are grouped into a clip caption to be displayed for a corresponding clip of the video.

Abstract: A system and method for voice-based control of sexual stimulation devices. In some configurations, the system and method involve receiving voice data, analyzing the voice data to detect spoken commands, and generating control signals based on the commands. In some configurations, the system and method involve receiving voice data, analyzing the voice data for non-speech vocalizations, detecting voice stress patterns, and generating control signals based on the detected patterns. In some configurations, the analyses of the voice data are performed by machine learning algorithms which may be trained on associations between speech and non-speech vocalizations of a user while the user engages in one or more voice-based training tasks, associating speech and non-speech vocalizations with controls of the sexual stimulation device. In some configurations, machine learning algorithms are used to make the associations. In some configurations, data from other biometric sensors is included in the associations.

Abstract: One or more non-transitory computer readable media contain program instructions that, when executed, cause one or more processors to: receive first raw data including one or more first data points generated by a first object of a plurality of objects associated with one or more buildings; generate first input timeseries according to the one or more data points; access a database of interconnected smart entities, the smart entities including object entities representing each of the plurality of objects and data entities representing stored data, the smart entities being interconnected by relational objects indicating relationships between the smart entities; identify a first object entity representing the first object from a first identifier in the first input timeseries; identify a first data entity from a first relational object indicating a relationship between the first object entity and the first data entity; and store the first input timeseries in the first data entity.

Abstract: A method for decoding an encoded audio bitstream is disclosed. The method includes receiving the encoded audio bitstream and decoding the audio data to generate a decoded lowband audio signal. The method further includes extracting high frequency reconstruction metadata and filtering the decoded lowband audio signal with an analysis filterbank to generate a filtered lowband audio signal. The method also includes extracting a flag indicating whether either spectral translation or harmonic transposition is to be performed on the audio data and regenerating a highband portion of the audio signal using the filtered lowband audio signal and the high frequency reconstruction metadata in accordance with the flag.

Abstract: A frequency band expansion device includes processing circuitry to calculate a weighting coefficient based on a frequency gradient of the input signal; to generate a white noise signal; to generate a first white noise signal by performing filtering on the white noise signal; to generate a second white noise signal by regulating a phase characteristic of the white noise signal; to generate a third white noise signal by performing weighted addition on the first white noise signal and the second white noise signal by using the weighting coefficient; and to generate the output signal by adding together the input signal and a signal corresponding to the third white noise signal, wherein the processing circuitry is configured so that the phase characteristic of the second white noise signal becomes the same as the phase characteristic of the first white noise signal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for neural network adaptive beamforming for multichannel speech recognition are disclosed. In one aspect, a method includes the actions of receiving a first channel of audio data corresponding to an utterance and a second channel of audio data corresponding to the utterance. The actions further include generating a first set of filter parameters for a first filter based on the first channel of audio data and the second channel of audio data and a second set of filter parameters for a second filter based on the first channel of audio data and the second channel of audio data. The actions further include generating a single combined channel of audio data. The actions further include inputting the audio data to a neural network. The actions further include providing a transcription for the utterance.