Abstract: A problem to be solved is to assist input of information by a user. An information processing device of one embodiment includes a keyword sequence generator generating a keyword sequence by performing morphological analysis on text data in natural language; a category information sequence generator acquiring category information corresponding to each keyword of the keyword sequence based on a database in which keywords are associated with category information and generating a category information sequence; the pattern extractor selecting a category information sequence pattern from category information sequence patterns according to correlation between the category information sequence and each category information sequence pattern; and a determiner comparing the selected category information sequence pattern with the category information sequence and generating presentation information according to a difference between the selected category information sequence pattern and the category information sequence.

Abstract: A method for providing a context awareness service is provided. The method includes defining a control command for the context awareness service depending on a user input, triggering a playback mode and the context awareness service in response to a user selection, receiving external audio through a microphone in the playback mode, determining whether the received audio corresponds to the control command, and executing a particular action assigned to the control command when the received audio corresponds to the control command.

Abstract: A device includes a multi-channel encoder configured to receive a first audio signal and a second audio signal, to perform a downmix operation on the first audio signal and the second audio signal to generate a mid signal, to generate a low-band mid signal and a high-band mid signal based on the mid signal, and to determine, based at least partially on a low band voicing value corresponding to the low band signal and a gain value corresponding to the high-band mid signal, a value of a multi-source flag that flag associated with the high-band mid signal. The multi-channel encoder is configured to generate a high-band mid excitation signal based on the multi-source flag and to generate a bitstream based on the high-band mid excitation signal. The device also includes a transmitter configured to transmit the bitstream and the multi-source flag to a second device.

Abstract: An utterance is analyzed to identify an absence of a known invocation phrase. A skill set is constructed in response to the absence, the skill set including a first skill corresponding to the utterance and a first skill score corresponding to a likelihood that the first skill corresponds to the utterance. The first skill score is adjusted, based on the presence of the first skill in a skill history, where the skill history stores a set of history skills in an order of recency of use of each history skill in the set of history skills. The first skill score is adjusted, based on an association of the first skill with a default installed skill. An installed skill is selected, based on the adjusted first skill score, the installed skill performing an action in response to the utterance.

Abstract: A sound output system includes a receiving apparatus comprising receiving circuitry configured to receive a user input; and a sound apparatus comprising circuitry configured to receive the user input from the receiving apparatus and perform an operation based on the user input received from the receiving apparatus. The sound apparatus may include a sound outputter comprising sound output circuitry; a first communicator comprising communication circuitry configured to communicate with the receiving apparatus; and a controller configured to control the sound apparatus to perform the operation based on a command received from the receiving apparatus through the first communicator. The receiving apparatus is removably attachable to the sound apparatus. The sound apparatus is configured to perform different operations depending on different attachment positions of the receiving apparatus, in response to the same user input.

Abstract: The invention provides a decoder being configured for processing an encoded audio bitstream, wherein the decoder includes: a bitstream decoder configured to derive a decoded audio signal from the bitstream, wherein the decoded audio signal includes at least one decoded frame; a noise estimation device configured to produce a noise estimation signal containing an estimation of the level and/or the spectral shape of a noise in the decoded audio signal; a comfort noise generating device configured to derive a comfort noise signal from the noise estimation signal; and a combiner configured to combine the decoded frame of the decoded audio signal and the comfort noise signal in order to obtain an audio output signal.

Abstract: A system includes network interface, processor operatively connected to the network interface, and memory operatively connected to the processor. The memory stores a plurality of language models of a first language. The plurality of language models be different from one another. Each of the plurality of language models is provided for speakers whose native language is different from the first language. The memory further stores instructions that cause the processor to receive a user's speech data associated with a plurality of sample texts from an external electronic device, to perform automatic speech recognition (ASR) on the speech data using the plurality of language models, to select one language model from the plurality of language models based on results from the performed ASR, and to use the selected one language model as a default language model for speech of the user.

Abstract: A method and device for automatic data correction using context and semantic aware learning techniques is disclosed. The method includes extracting data within a document as machine readable text in a predefined format. The method further includes encoding each word of each line in the machine readable text to a multi-dimension word vector. The method includes generating a context word vector for each word in each line based on multi-dimension vectors associated with words succeeding and preceding the word in a line comprising the word. The method further includes decoding the context word vector associated with each word in each line to generate a corrected context word vector for each word. The method includes validating the corrected context word vector associated with each word in each line.

Abstract: There is provision of an information presentation device including a displaying unit, an input receiving unit configured to receive an input from a user, an answer generating unit configured to generate an answer sentence in response to the input received by the input receiving unit, an additional information acquiring unit configured to acquire additional information related to a word contained in the answer sentence generated by the answer generating unit, a voice outputting unit configured to output the answer sentence by sound, and an information outputting unit configured to output the additional information on the displaying unit.

Abstract: A modular controller may be mounted in an opening, such as a standard single wide or double wide electrical junction box, in a wall or other surface. The modular controller may include a power module and a front module. The power module may be mounted in the opening of the surface, and may be configured to provide electrical power to the front module. The front module may be detachably coupleable to the power module. The front module may be configured to receive audio commands, gesture commands, and/or presence input corresponding to a desired action, and may cause the action to be performed by a device of the front module and/or an external device. The front module may include various devices (e.g., components) capable of providing various functionalities, and may be selected for coupling to a power module in a particular location based at least in part on the functionalities.

Abstract: Methods and systems are described herein for generating an audible presentation of a communication received from a remote server. A presentation of a media asset on a user equipment device is generated for a first user. A textual-based communication is received, at the user equipment device from the remote server. The textual-based communication is transmitted to the remote server by a second user and the remote server transmits the textual-based communication to the user equipment device responsive to determining that the second user is on a list of users associated with the first user. An engagement level of the first user with the user equipment device is determined. Responsive to determining that the engagement level does not exceed a threshold value, a presentation of the textual-based communication is generated in audible form.

Abstract: Disclosed is an artificial intelligence voice recognition apparatus including: an audio input unit configured to receive a voice; a communication module configured to transmit voice data received from the audio input unit to a server system, which performs voice recognition processing, and receive recognition result data on the voice data from the server system; and a controller configured to control the audio input unit and the communication module, wherein, when a voice command in the voice data corresponds to a pre-stored keyword command, the controller performs control to perform an operation corresponding to the keyword command, and wherein when the voice command in the voice data does not correspond to the pre-stored keyword command, the controller performs control to transmit the voice data including the voice command to the server system. Accordingly, voice recognition may be performed efficiently.

Abstract: In one embodiment, a method includes receiving a request to generate a visualization of public sentiments regarding a particular subject by a plurality of clusters, where each cluster includes a plurality of words semantically close to each other, constructing a first corpus of text by collecting text containing the input n-gram from a plurality of user-created content objects in the online social network, identifying a list of unique n-grams appearing in the first corpus of text, generating a table comprising unique n-grams in the list and their corresponding word vectors using a word embedding model, classifying word vectors in the table into a plurality of clusters based on semantic similarities of the word vectors, and sending, as a response to the request, instructions to display n-grams in the table in a two-dimensional display space, where n-grams corresponding to word vectors that belong to a cluster are displayed together.

Abstract: A computer-implemented method includes identifying a first set of utterances from a plurality of utterances. The plurality of utterances is associated with a conversation and transmitted via a plurality of audio signals. The computer-implemented method further includes mining the first set of utterances for a first context. The computer-implemented method further includes determining that the first context associated with the first set of utterances is not relevant to a second context associated with the conversation. The computer-implemented method further includes dynamically muting, for at least a first period of time, a first audio signal in the plurality of audio signals corresponding to the first set of utterances. A corresponding computer system and computer program product are also disclosed.

Abstract: Certain aspects produce a scoring model that can automatically classify future text samples. In some examples, a processing device perform operations for producing a scoring model using active learning. The operations includes receiving existing text samples and searching a stored, pre-trained corpus defining embedding vectors for selected words, phrases, or documents to produce nearest neighbor vectors for each embedding vector. Nearest neighbor selections are identified based on distance between each nearest neighbor vector and the embedding vector for each selection to produce a text cloud. Text samples are selected from the text cloud to produce seed data that is used to train a text classifier. A scoring model can be produced based on the text classifier. The scoring model can receive a plurality of new text samples and provide a score indicative of a likelihood of being a member of a selected class.

Abstract: The present teaching relates to facilitating a guided dialog with a user. In one example, an input utterance is obtained from the user. One or more task sets are estimated based on the input utterance. Each of the one or more task sets includes a plurality of tasks estimated to be requested by the user via the input utterance and is associated with a confidence score computed based on statistics with respect to the plurality of tasks in the task set. At least one of the one or more task sets is selected based on their respective confidence scores. A response is generated based on the tasks in the selected at least one task set. The response is provided to the user.

Abstract: Described systems and methods allow an automatic translation from a natural language (e.g., English) into an artificial language such as a structured query language (SQL). In some embodiments, a translator module includes an encoder component and a decoder component, both components comprising recurrent neural networks. Training the translator module comprises two stages. A first stage trains the translator module to produce artificial language (AL) output when presented with an AL input. For instance, the translator is first trained to reproduce an AL input. A second stage of training comprises training the translator to produce AL output when presented with a natural language (NL) input.

Abstract: The present invention is related to an information extraction method. The information extraction method may comprise providing r semantic relationships, acquiring entity pairs corresponding to the semantic relationships, acquiring first instances based on the entity pairs, and eliminating instances that do not have the semantic relationships from the first instances to obtain second instances. r is a positive integer. Each of the entity pairs contains a pair of named entities. The first instances are sentences containing the entity pairs.

Abstract: An identity verification method and an identity verification apparatus based on a voiceprint are provided. The identity verification method based on a voiceprint includes: receiving an unknown voice; extracting a voiceprint of the unknown voice using a neural network-based voiceprint extractor which is obtained through pre-training; concatenating the extracted voiceprint with a pre-stored voiceprint to obtain a concatenated voiceprint; and performing judgment on the concatenated voiceprint using a pre-trained classification model, to verify whether the extracted voiceprint and the pre-stored voiceprint are from a same person. With the identity verification method and the identity verification apparatus, a holographic voiceprint of the speaker can be extracted from a short voice segment, such that the verification result is more robust.

Abstract: Disclosed is an artificial intelligence voice recognition apparatus including: a microphone configured to receive a voice command; a memory configured to store a first voice recognition algorithm; a communication module configured to transmit the voice command to a server system and receive first voice recognition algorithm-related update data from the server system; and a controller configured to perform control to update the first voice recognition algorithm, which is stored in the memory, based on the first voice recognition algorithm-related update data. Accordingly, the voice recognition apparatus is able to provide a voice recognition algorithm fitting to a user's characteristics.