Abstract: An information processing apparatus includes: a speech obtainer which obtains speech of a user; a first controller which, when the first controller recognizes that the speech obtained by the speech obtainer is a first activation word, outputs a speech signal corresponding to a second activation word different from the first activation word; and a second controller which performs an activation process for starting transmission of the speech signal of the speech obtained by the speech obtainer to a VPA cloud server when the second controller recognizes that the speech signal output by the first controller indicates the second activation word.

Abstract: A query-processing server that interprets natural language expressions supports the extension of a first semantic grammar (for a particular type of expression), which is declared extensible, by a second semantic grammar (for another type of expression). When an extension is requested, the query-processing server checks that the two semantic grammars have compatible semantic types. The developers need not have any knowledge of each other, or about their respective grammars. Performing an extension may be done by yet another party, such as the query-processing server, or another server, independently of all previous parties. The use of semantic grammar extensions provides a way to expand the coverage and functionality of natural language interpretation in a simple and flexible manner, so that new forms of expression may be supported, and seamlessly combined with pre-existing interpretations. Finally, in some implementations, this is done without loss of efficiency.

Abstract: Conventional audio compression technologies perform a standardized signal transformation, independent of the type of the content. Multi-channel signals are decomposed into their signal components, subsequently quantized and encoded. This is disadvantageous due to lack of knowledge on the characteristics of scene composition, especially for e.g. multi-channel audio or Higher-Order Ambisonics (HOA) content. A method for decoding an encoded bitstream of multi-channel audio data and associated metadata is provided, including transforming the first Ambisonics format of the multi-channel audio data to a second Ambisonics format representation of the multi-channel audio data, wherein the transforming maps the first Ambisonics format of the multi-channel audio data into the second Ambisonics format representation of the multi-channel audio data.

Abstract: The system and method described herein may use various natural language models to deliver targeted advertisements and/or provide natural language processing based on advertisements. In one implementation, an advertisement associated with a product or service may be provided for presentation to a user. A natural language utterance of the user may be received. The natural language utterance may be interpreted based on the advertisement and, responsive to the existence of a pronoun in the natural language utterance, a determination of whether the pronoun refers to one or more of the product or service or a provider of the product or service may be effectuated.

Abstract: Artificial intelligence (AI) technology can be used in combination with composable communication goal statements to facilitate a user's ability to quickly structure story outlines in a manner usable by an NLG narrative generation system without any need for the user to directly author computer code. This AI technology permits attribute structures within an ontology can include an explicit model for the subject attribute, regardless of whether that model is used to compute the value of the subject attribute itself. This explicit model can then be leveraged to support an investigation of drivers of the value for the subject attribute. Narrative analytics that perform driver analysis can then be used to support narrative generation for communication goals relating to explanations, predictions, recommendations, and the like.

Abstract: Email servers configured to perform automatic summarization of content in electronic messages are discloses herein. In one embodiment, upon receiving an email, an email server determines whether the incoming email is a templated message. In response to determining that the incoming email is not a templated message, the email server classifies one or more sentences in the email as a statement of decision, judgement, inference, or fact, cluster the classified statements into clusters, and select one or more of the clusters to automatically generate summaries of the incoming email. The email server can then insert data representing the generated summaries into the email before transmitting the email to a destination via a computer network.

Abstract: A method includes receiving an utterance of speech and segmenting the utterance of speech into a plurality of segments. For each segment of the utterance of speech, the method also includes extracting a speaker-discriminative embedding from the segment and predicting a probability distribution over possible speakers for the segment using a probabilistic generative model configured to receive the extracted speaker-discriminative embedding as a feature input. The probabilistic generative model trained on a corpus of training speech utterances each segmented into a plurality of training segments. Each training segment including a corresponding speaker-discriminative embedding and a corresponding speaker label. The method also includes assigning a speaker label to each segment of the utterance of speech based on the probability distribution over possible speakers for the corresponding segment.

Abstract: Systems and methods for optimizing voice detection via a network microphone device are disclosed herein. In one example, individual microphones of a network microphone device detect sound. The sound data is captured in a first buffer and analyzed to detect a trigger event. Metadata associated with the sound data is captured in a second buffer and provided to at least one network device to determine at least one characteristic of the detected sound based on the metadata. The network device provides a response that includes an instruction, based on the determined characteristic, to modify at least one performance parameter of the NMD. The NMD then modifies the at least one performance parameter based on the instruction.

Abstract: In some aspects, disclosed herein is a device that stores one or more pre-recorded or dynamically generated voice commands that are capable of activating a virtual assistant via a voice-based user interface and causing the virtual assistant to perform a specific task. The device may be activated manually, e.g., by pushing a button. In some aspects, the device relieves a user of a virtual assistant of the need to speak a specific command in order to cause a virtual assistant to perform a specific task.

Abstract: Systems and methods for natural language processing and classification are provided. In some embodiments, the systems and methods include a communication editor dashboard which receives the message, performs natural language processing to divide the message into component parts. The system displays the message in a first pane with each of the component parts overlaid with a different color, and displaying in a second pane the insights, the confidence scores associated with each insight, the sentiment and the actions. In another embodiment, the systems and methods include combining outputs from multiple machine learned AI models into a unified output. In another embodiment, the systems and methods include responding to simple question using natural language processing.

Abstract: What is described is a method for associating noises of at least one signal class (like disturbing noise) of a plurality of signal classes (like disturbing noise and non-disturbing noise). The method has the steps of “receiving environmental noises” and “establishing whether the environmental noises or a set of parameters derived from the environmental noises fulfill/s a predefined rule which describes the signal class of the plurality of signal classes”. Starting from this, the steps of “logging that the predefined rule has been fulfilled”, “recording the environmental noises received for a migrating time window”, “deriving a set of parameters from the environmental noises for the migrating time window and storing the set of parameters” or “emitting an activation signal for another device for associating a noise” are performed.

Abstract: The present disclosure is generally directed to a data processing system for customizing content in a voice activated computer network environment. With user consent, the data processing system can improve the efficiency and effectiveness of auditory data packet transmission over one or more computer networks by, for example, increasing the accuracy of the voice identification process used in the generation of customized content. The present solution can make accurate identifications while generating fewer audio identification models, which are computationally intensive to generate.

Abstract: A home appliance including an audio input unit including at least one microphone and into which a voice command formed of natural language is inputted; a communication unit which transmits the voice command to a voice recognition system as voice data, and receives a response signal from the voice recognition system; a controller which sets an operation corresponding to the response signal, outputs an operation state, and outputs a guidance announcement, according to a result of voice recognition of the voice recognition system; and an audio output unit which outputs the guidance announcement corresponding to the operation, wherein the controller determines whether it is possible to set the operation or to support a function for the operation in response to the response signal and an operation state of the home appliance, and performs the operation.

Abstract: Artificial intelligence-based processing can be used to classify audio information received from an audio input unit. In an example, audio information can be received from a microphone configured to monitor an environment. A processor circuit can identify identifying one or more features of the audio information received from the microphone and use a first applied machine learning algorithm to analyze the one or more features and determine whether the audio information includes an indication of an abnormal event in the environment. In an example, the processor circuit can use a different second applied machine learning algorithm, such as a neural network-based deep learning algorithm, to analyze the same one or more features and classify the audio information as including an indication of a particular event type in the environment.

Abstract: Disclosed are techniques for generating a language model that is applicable to the interpretation of commands for invoking application-based actions via a digital assistant device. In various embodiments, command templates that are each mapped to one of a plurality of action datasets are obtained to generate synthetic documents of a language model document corpus. Each synthetic document can be modified to include a tag that corresponds to an associated command template from which the document's generation was based. The language model can include a plurality of document clusters that are generated based on the modified synthetic documents, among other things.

Abstract: Disclosed are techniques for the automated discovery and extraction of discourse phrases, or in other words terms that representative of a topic or concept communicated via a plurality of electronic documents, to facilitate the generation of a language model that is applicable to interpreting commands for invoking application-based actions via a digital assistant device. An electronic document corpus can be generated having a plurality of electronic documents that are clustered based on entropy, among other things. The clusters can be associated with a corresponding plurality of cluster attractors that are generally representative of a context of the documents included therein. The clusters can be grouped based on determined relationships, such that the groups can be further analyzed and terms or phrases representative of a discourse associated with the grouped documents can be determined.

Abstract: Disclosed are techniques for automatically extracting discovered topics and/or from determined discourse clusters for the generation of a language model that is applicable to interpreting commands received from a digital assistant device. An electronic document corpus can be generated having a plurality of documents that are clustered based on entropy, among other things. The clusters can be associated with a corresponding plurality of cluster attractors that are generally representative of a context of the documents included therein. The documents within the cluster for each of the document clusters can be analyzed, so that clusters determined representative of a hierarchical discourse community can be determined and logically merged. The merged clusters can be analyzed, such that topics and/or sub-topics can be determined and extracted therefrom, for indexing and storage, among other things.

Abstract: Various embodiments of the present application set forth a computer-implemented method that includes processing a first natural language (NL) request, where the first NL request includes a first artifact. The method further includes determining that a first relationship, associated with the first artifact and useable to process the first NL request, is unavailable in a first NL language processing system. The method further includes generating a first data relationship recommendation based on the first NL request. In addition, the method includes causing the first data relationship recommendation to be provided to a user.

Abstract: This patent specification discloses a system for selecting an optimal audio codec algorithm to compress audio files that are wrapped within a Material eXchange Format (MXF) file. This patent specification melds the Material eXchange Format (MXF) for files together with matched-filter technology to provide a standards-compatible implementation for the selection and utilization of an optimal audio compression technology for a specific audio file included within an MXF file.

Abstract: In some implementations, a determination that a first party has spoken a query for a voice-enabled virtual assistant during a voice call between the first party and a second party is made, in response to the determination that the first party has spoken the query for the voice-enabled virtual assistant during the voice call between the first party and the second party, the voice call between the first party and the second party is placed on hold, a determination that the voice-enabled virtual assistant has resolved the query is made, and in response to the determination that the voice-enabled virtual assistant has handled the query, the voice call between the first party and the second party is resumed from hold.