Abstract: A computer-implemented method for correcting muffled speech caused by facial coverings is disclosed. The computer-implemented method includes monitoring a user's speech for speech distortion. The computer-implemented method further includes determining that the user's speech is distorted. The computer-implemented method further includes determining that a cause of the user's speech distortion is based, at least in part, on a presence of a particular type of facial covering. The computer-implemented method further includes automatically correcting the speech distortion of the user based, at least in part, on the particular type of facial covering causing the speech distortion.

Abstract: Disclosed are a Digital Enhanced Cordless Telecommunications (DECT) base station, a handset and a communication system. The DECT base station is installed with at least two different voice codecs and is configured to sequentially judge whether the voice codecs of the DECT base station match voice codecs of a handset according to a first codec information data packet sent by the handset, and when a matching is successful, send a response information to the handset to perform voice communication with the handset through a matched voice codec. By using the DECT base station can guarantee the normal voice communication between the DECT base station and the handset in the condition of installing voice codecs in the DECT base station.

Abstract: An apparatus for processing an audio signal includes a configurable first audio signal processor for processing the audio signal in accordance with different configuration settings to obtain a processed audio signal, wherein the apparatus is adapted so that different configuration settings result in different sampling rates of the processed audio signal. The apparatus furthermore includes n analysis filter bank having a first number of analysis filter bank channels, a synthesis filter bank having a second number of synthesis filter bank channels, a second audio processor being adapted to receive and process an audio signal having a predetermined sampling rate, and a controller for controlling the first number of analysis filter bank channels or the second number of synthesis filter bank channels in accordance with a configuration setting.

Abstract: A method, computer program product, and computer system for public speaking guidance is provided. A processor retrieves speaker data regarding a speech made by a user. A processor separates the speaker data into one or more speaker modalities. A processor extracts one or more speaker features from the speaker data for the one or more speaker modalities. A processor generates a performance classification based on the one or more speaker features. A processor sends to the user guidance regarding the speech based on the performance classification.

Abstract: Disclosed systems relate to generating questions from text. In an example, a method includes forming a first semantic tree from a first reference text and second semantic tree from a second reference text. The method includes identifying a set of semantic nodes that are in the first semantic tree but not in the second semantic tree. The method includes forming a first syntactic tree for the first reference text and a second syntactic tree for the second reference text. The method includes identifying a set of syntactic nodes that are in the first syntactic tree but not in the second syntactic tree. The method includes mapping the set of semantic nodes to the set of syntactic nodes by identifying a correspondence between a semantic node and a syntactic node, forming a question fragment from a normalized word, and providing the question fragment to a user device.

Abstract: Techniques are provided for improving computers as tools for assisting in negotiations. Specifically, techniques are provided for using a trained machine learning system to predict the likelihood that a party to a negotiation intends to comply with terms that are under consideration. In some negotiations, each party of a negotiation may use the techniques described herein to determine terms to offer the other party. In such situations, both parties may be both terms-receiving parties and terms-offering parties. By using a trained machine learning system to predict the intent of a party, the possibility of human bias significantly reduced, allowing proposed terms to be based more on objective facts and predictive indicators rather than the prejudices of the agents that have been delegated the responsibility of proposing terms.

Abstract: An audio signal encoding and decoding method using a neural network model, a method of training the neural network model, and an encoder and decoder performing the methods are disclosed. The encoding method includes computing the first feature information of an input signal using a recurrent encoding model, computing an output signal from the first feature information using a recurrent decoding model, calculating a residual signal by subtracting the output signal from the input signal, computing the second feature information of the residual signal using a nonrecurrent encoding model, and converting the first feature information and the second feature information to a bitstream.

Abstract: Data processing apparatus comprises a data memory; a selection controller comprising a computer processor; and a digital interface between a control process implemented by the selection controller and a text handling process implemented by the computer processor or another processor; in which: the selection controller is configured to provide a text document from the data memory to the text handling process to identify one or more characteristics of words in the text document; the selection controller is configured to provide user selection of one or more of the words in the text document to be substituted and of one or more target characteristics; and the selection controller is configured to request from the text handling process a set of one or more substitute words for the selected words such that the substitute words comply with the selected one or more of the target characteristics.

Abstract: Apparatuses and methods of transmitting and receiving a speech signal. The method of transmitting a speech signal includes extracting low frequency feature information from an input speech signal by using a first feature extracting network; and transmitting a speech signal corresponding to the low frequency feature information to a receiving end. The method of receiving a speech signal includes receiving a first speech signal transmitted by a transmitting end; extracting low frequency feature information from the first speech signal and recovering high frequency feature information based on the low frequency feature information, by using a second feature extracting network; and outputting a second speech signal including the low frequency feature information and the high frequency feature information.

Abstract: Provided are an artificial intelligence (AI) system that utilizes a machine learning algorithm such as deep learning, etc., and an application of the AI system. A method performed by a device for providing a voice assistant service through a voice assistant program includes: receiving, from an external device, a character specialized model for the voice assistant program; receiving a user voice input including a request for a response of the voice assistant program and a word indicating a character; determining the character specialized model according to the word indicating the character; generating a response message to the request for the response of the voice assistant program, using the character specialized model; and outputting the generated response message.

Abstract: In some examples, data-driven social media analytics application synthesis may include generating, for each social media analytics application of a plurality of social media analytics applications, a corpus, performing term normalization, and generating a normalized corpus. An actor, an action and an object may be generated for each social media analytics application, which may be mapped into an embedding space. A semantic cohesion network may be generated for each social media analytics application, and a pair-wise semantic cohesion may be determined to identify semantically cohesive groups. A new social media analytics application may be synthesized based on the identified semantically cohesive groups.

Abstract: Various embodiments of the present disclosure evaluate transcription accuracy. In some implementations, the system normalizes a first transcription of an audio file and a baseline transcription of the audio file. The baseline transcription can be used as an accurate transcription of the audio file. The system can further determine an error rate of the first transcription by aligning each portion of the first transcription with the portion of the baseline transcription, and assigning a label to each portion based on a comparison of the portion of the first transcription with the portion of the baseline transcription.

Abstract: Systems and methods are provided for automatic speech recognition. In the method, the system obtains a padded sequence by processing a plurality of acoustic signals. The system compresses the padded sequence by reducing the size of the padded sequence to obtain a compressed sequence. The system inputs the compressed sequence into a pre-trained encoder neural network to obtain an encoded sequence and then decompresses the encoded sequence by recovering the encoded sequence to an original sequential ordering. The system inputs the encoded sequence to a decoding module to obtain recognition texts.

Abstract: Embodiments of the present disclosure relate to a method and an apparatus for speech interaction, and a computer readable storage medium. The method may include determining text information corresponding to a received speech signal. The method also includes obtaining label information of the text information by labeling elements in the text information. In addition, the method further includes determining first intention information of the text information based on the label information. The method further includes determining a semantic of the text information based on the first intention information and the label information.

Abstract: An automatic speech recognition (ASR) system that determines a textual representation of a word from a word spoken in a natural language is provided. The ASR system uses an acoustic model, a language model, and a decoder. When the ASR system receives a spoken word, the acoustic model generates word candidates for the spoken word. The language model determines an n-gram score for each word candidate. The n-gram score includes a base score and a bias score. The bias score is based on a logarithmic probability of the word candidate, where the logarithmic probability is derived using a class-based language model where the words are clustered into non-overlapping clusters according to word statistics. The decoder decodes a textual representation of the spoken word from the word candidates and the corresponding n-gram score for each word candidate.

Abstract: A method, computer program, and computer system to recover a dropped pronoun is provided for receiving data corresponding to one or more input words and determining contextual representations for the received input word data. The dropped pronoun may be identified based on a probability value associated with the contextual representations, and a span associated with one or more of the received input words may and that corresponds to which of the input words the dropped pronoun refers may be determined.

Abstract: An apparatus for processing an audio signal includes a configurable first audio signal processor for processing the audio signal in accordance with different configuration settings to obtain a processed audio signal, wherein the apparatus is adapted so that different configuration settings result in different sampling rates of the processed audio signal. The apparatus furthermore includes n analysis filter bank having a first number of analysis filter bank channels, a synthesis filter bank having a second number of synthesis filter bank channels, a second audio processor being adapted to receive and process an audio signal having a predetermined sampling rate, and a controller for controlling the first number of analysis filter bank channels or the second number of synthesis filter bank channels in accordance with a configuration setting.

Abstract: Systems and processes for operating an intercom system via a digital assistant are provided. The intercom system is trigger-free, in that users communicate, in real-time, via devices without employing a trigger to speak. Acoustic fingerprints are employed to associate users with devices. Acoustic fingerprints include vector embeddings of speech input in an acoustic-feature vector space. Speech heard at multiple devices, as embedded in a fingerprint, may be clustered in the vector space, and the structure of the clusters is employed to associate users and devices. Based on the fingerprints, a device is mapped to a user, and the user employs that device to participate in a conversation, via the intercom service.

Abstract: Embodiments described herein provide for a computer that detects one or more keywords of interest using acoustic features, to detect or query commonalities across multiple fraud calls. Embodiments described herein may implement unsupervised keyword spotting (UKWS) or unsupervised word discovery (UWD) in order to identify commonalities across a set of calls, where both UKWS and UWD employ Gaussian Mixture Models (GMM) and one or more dynamic time-warping algorithms. A user may indicate a training exemplar or occurrence of call-specific information, referred to herein as “a named entity,” such as a person's name, an account number, account balance, or order number. The computer may perform a redaction process that computationally nullifies the import of the named entity in the modeling processes described herein.

Abstract: A speech transmission compensation apparatus that assists discrimination of speech heard by a user, includes: one or more computers each including a memory and a processor configured to: accept input of a speech signal, detect a specific type of sound in the speech signal, analyze an acoustic characteristic of the specific type of sound in the speech signal and output the acoustic characteristic; accept input of the acoustic characteristic being output by the memory and the processor, generate a vibration signal of a duration corresponding to the acoustic characteristic and output the vibration signal; and accept input of the vibration signal being output by the memory and the processor and provide the user with vibration for the duration on the basis of the vibration signal.