Abstract: Techniques are provided for identifying attributes associated with a neologism or an unknown word or name. Real world characteristics can be predicted for the neologism. Trigrams are identified for an input word and word embedding model vector values are calculated for the identified trigrams and entered into a matrix. Trigrams are identified for nearest names. Classification values are calculated based on the trigrams for the input word and the trigrams from the nearest names and the classification values are entered into the matrix. A convolutional neural network can process the matrix to identify one or more characteristics associated with the neologism.

Abstract: An information processing apparatus includes a lexical analysis unit that generates a training word string, a group generation unit that generates a plurality of training word groups, a matrix generation unit that generates, for each training word group, a training matrix in which a plurality of words and respective semantic vectors of the words are associated, a classification unit that calculates, for a word of each position of the training word string, a probability of the word corresponding to a specific word, using the training matrices generated by the matrix generation unit and a determination model that uses a convolutional neural network, and an optimization processing unit that updates parameters of the determination model, such that the probability of the word labeled as corresponding to the specific word is high, among the probabilities of the words of the respective positions of the training word string calculated by the classification unit.

Abstract: An audio encoder has a first information sink oriented encoding branch such as a spectral domain encoding branch, a second information source or SNR oriented encoding branch such as an LPC-domain encoding branch, and a switch for switching between the first and second encoding branches, the second encoding branch having a converter into a specific domain different from the spectral domain such as an LPC analysis stage generating an excitation signal, and the second encoding branch having a specific domain coding branch such as LPC domain processing branch, and a specific spectral domain coding branch such as LPC spectral domain processing branch, and an additional switch for switching between the specific domain coding branch and the specific spectral domain coding branch. An audio decoder has a first domain decoder, a second domain decoder, and a third domain decoder as well as two cascaded switches for switching between the decoders.

Abstract: An audio encoder has a first information sink oriented encoding branch such as a spectral domain encoding branch, a second information source or SNR oriented encoding branch such as an LPC-domain encoding branch, and a switch for switching between the first and second encoding branches, the second encoding branch having a converter into a specific domain different from the spectral domain such as an LPC analysis stage generating an excitation signal, and the second encoding branch having a specific domain coding branch such as LPC domain processing branch, and a specific spectral domain coding branch such as LPC spectral domain processing branch, and an additional switch for switching between the specific domain coding branch and the specific spectral domain coding branch. An audio decoder has a first domain decoder, a second domain decoder, and a third domain decoder as well as two cascaded switches for switching between the decoders.

Abstract: Systems, methods, and storage media for providing an interface for textual editing through speech are disclosed. One aspect of the disclosure may include storing a narrative textual message and presenting the narrative textual message via a client computing platform. Speech uttered by a user may be received. Speech recognition may be performed on the speech to determine words spoken by the user. The words determined from the speech may be analyzed to detect whether an editing command was spoken. The editing command may include a parameter and an edited value for the parameter. The editing command may be processed to insert the edited value for the parameter or replace an initial value to the parameter with the edited value. Information may be transmitted to the client computing platform that causes the narrative textual message to be visually presented including edits based on the editing command.

Abstract: An audio encoder for encoding segments of coefficients, the segments of coefficients representing different time or frequency resolutions of a sampled audio signal, the audio encoder including a processor for deriving a coding context for a currently encoded coefficient of a current segment based on a previously encoded coefficient of a previous segment, the previously encoded coefficient representing a different time or frequency resolution than the currently encoded coefficient. The audio encoder further includes an entropy encoder for entropy encoding the current coefficient based on the coding context to obtain an encoded audio stream.

Abstract: In some implementations, (i) audio data representing a voice command spoken by a speaker and (ii) a speaker identification result indicating that the voice command was spoken by the speaker are obtained. A voice action is selected based at least on a transcription of the audio data. A service provider corresponding to the selected voice action is selected from among a plurality of different service providers. One or more input data types that the selected service provider uses to perform authentication for the selected voice action are identified. A request to perform the selected voice action and (i) one or more values that correspond to the identified one or more input data types are provided to the service provider.

Abstract: Methods, apparatus, and systems are disclosed to segment audio and determine audio segment similarities. An example apparatus includes at least one memory storing instructions and processor circuitry to execute instructions to at least select an anchor index beat of digital audio, identify a first segment of the digital audio based on the anchor index beat to analyze, the first segment having at least two beats and a respective center beat, concatenate time-frequency data of the at least two beats and the respective center beat to form a matrix of the first segment, generate a first deep feature based on the first segment, the first deep feature indicative of a descriptor of the digital audio, and train internal coefficients to classify the first deep feature as similar to a second deep feature based on the descriptor of the first deep feature and a descriptor of a second deep feature.

Abstract: A wearable device includes various sensors including a microphone, heart rate monitor, pressure sensor, and so forth. The user can set the device to acquire audio data of their speech. For example, if the pressure sensor indicates the device is being worn and the user's heart rate exceeds a threshold value, audio data may be acquired. Onboard the device the audio data is processed in various ways such as detecting whether the audio data includes speech, applying a beamforming algorithm, compressing and encrypting the audio, and so forth. The audio data may be processed onboard the device, sent to another device, or a combination thereof for processing to determine sentiment data indicative of perceived emotional content of the speech. A user interface provides the user with information based on the sensor data, sentiment data, and so forth.

Abstract: An example system includes a processor to receive raw and unlabeled videos. The processor is to extract speech from the raw and unlabeled videos. The processor is to extract positive frames and negative frames from the raw and unlabeled videos based on the extracted speech for each object to be detected. The processor is to extract region proposals from the positive frames and negative frames. The processor is to extract features based on the extracted region proposals. The processor is to cluster the region proposals and assign a potential score to each cluster. The processor is to train a binary object detector to detect objects based on positive samples randomly selected based on the potential score.

Abstract: In an embodiment, cognitive adjustment of responses from a virtual assistant includes detecting verbal content in an audio signal, determining that the verbal content includes a voice command associated with a task by correlating the verbal content with voice command data stored in memory, determining a state of the user from the audio signal by cognitively comparing aspects of the verbal content with aspects of profile data associated with the user, and retrieving task data associated with the task for preparing a response to the voice command.

Abstract: A method for extracting an event from a text including obtaining an input text; inputting the input text into a model for extracting trigger words to obtain a trigger word extraction result of the input text; inputting the input text and the trigger word extraction result into a model for extracting arguments to obtain an argument extraction result of the input text; and obtaining an event extraction result of the input text according to the trigger word extraction result and the argument extraction result.

Abstract: Provided is a system, method, and computer program product for conducting secure transactions with at least two appliances. The method includes monitoring audio data with a first appliance including a processor, a speaker, and a microphone; detecting, with the first appliance, an audible request to initiate a transaction from a user from the audio data; communicating, with the first appliance, a transaction request to at least one remote server in response to detecting the audible request to initiate the transaction; detecting, with the first appliance, a credential message received by the first appliance directly from a second appliance via an audio transmission, the credential message corresponding to the transaction request and including a limited use key provided to the second appliance from the at least one remote server or another remote server; and in response to detecting the credential message, initiating, with the first appliance, the transaction based on the limited use key.

Abstract: A single-bit audio stream can be converted to a modified single-bit audio stream with a constant edge rate while maintaining a modulation index of the original audio stream using direct mapping. With direct mapping, a pre-filter bank may be combined with a multi-bit symbol mapper to select symbols for the modified audio stream with a constant edge rate per symbol and the same modulation index as the original audio stream. The output of the pre-filter bank may be an audio stream with no consecutive full-scale symbols. Using the output of the pre-filter bank, a multi-bit symbol mapper may use the symbol selector to output a symbol with a constant edge rate per symbol and the same modulation index as the original signal. The symbols may be converted to an analog signal for reproduction of audio content using a transducer.

Abstract: The present disclosure relates generally to providing a concierge service to handle a wide variety of topics and user intents via a text messaging interface. The concierge service can be part of a connection management system that can dynamically manage and facilitate natural language conversations between a user making a request or providing an instruction and one or more endpoints for the purposes of fulfilling the request or instruction.

Abstract: Provided is a system and method for adapting sentiment analysis to user profiles to reduce bias in customer or user generated content, specifically a system and method that discounts or adjusts bias in sentiment data based on the channel from which the content was received and/or the demographic of the user. The system includes a means to detect sentiment bias for any product, service, or company across multiple channels of customer data; a means to construct models to quantize bias by specific demographics and channels; and a means to adjust sentiment model output to reduce inflation by biased groups.

Abstract: A processor may receive information from one or more users. The information may include identifiers associated with the one or more users and audio associated with the one or more users. The processor may transcribe the audio into a text of the audio. The processor may parse the text into one or more segments. The processor may analyze each of the one or more segments. The processor may determine, from the analyzing, a specific subject of the information.

Abstract: Procedural optimization is facilitated by receiving user input for creating or modifying a body of text comprising a procedure, detecting one or more procedural steps associated with the procedure using a procedural step detection module, automatically searching within a corpus of references for one or more related procedural steps using a related procedural step extraction module, automatically identifying one or more outcomes within the corpus of references associated with the one or more related procedural steps using an outcome extraction module, automatically determining whether the one or more outcomes comprise detrimental results using an outcome analysis module, and, in response to determining a set of detrimental outcomes from the one or more outcomes that comprise detrimental results, presenting a detriment indicator within the user interface in association with the one or more procedural steps.

Abstract: Systems, methods, and storage media for extracting patent document templates from a patent corpus are disclosed. Exemplary implementations may: obtain a patent corpus; receive one or more parameters; determine one or more subsets of the patent corpus by filtering the patent corpus based on the one or more parameters; identify one or more document clusters within individual ones of the one or more subsets of the patent corpus; obtain a patent document template corresponding to the first document cluster; and/or perform other operations.

Abstract: A classification code parser and method can include: reading a classification code having a description; reading a required keyword, and a total number of keywords associated with the classification code; reading text of a note; tokenizing the text of the note to create a note token stream, the note token stream having a note token and a position of the note token within the note token stream; creating a keyword map including a total number of matched keywords; determining a match ratio from the total number of the matched keywords and the total number of the keywords; determining a proximity factor based on a shortest span of tokens within the note token stream containing all the matched keywords; and determining a strength of a match between the classification code and the note based on the match ratio being multiplied by the proximity factor.