Abstract: A transcription of a query for content discovery is generated, and a context of the query is identified, as well as a first plurality of candidate entities to which the query refers. A search is performed based on the context of the query and the first plurality of candidate entities, and results are generated for output. A transcription of a second voice query is then generated, and it is determined whether the second transcription includes a trigger term indicating a corrective query. If so, the context of the first query is retrieved. A second term of the second query similar to a term of the first query is identified, and a second plurality of candidate entities to which the second term refers is determined. A second search is performed based on the second plurality of candidates and the context, and new search results are generated for output.

Abstract: Hardware and/or software systems, devices, networks, and methods of the present invention enable ornamental devices, and interactive electronic devices in general, to generate and react to stimulus from other devices. In various embodiments electronic devices generate one or more pseudo-stimuli and stimuli and/or react to the stimuli generated by other devices mimicking fireflies, other bioluminescent organisms, and other interacting organisms. Pseudo-stimuli generally simulates the physical stimulus of the organism. Whereas the stimulus may include naturally-occurring stimulus, as well as technology generated stimuli to increase system robustness. When a stimulus generated by a first electronic device is detected by one or more second electronic devices, the second devices may react in one or more different methods.

Abstract: A method of generating an editable translated electronic document from an input image of an original document with a first layout includes: segmenting the input image to generate a first region including first untranslated text; extracting, from the first region, the first untranslated text and a first layout information; generating an editable output data including the first untranslated text and the first layout information; translating the first untranslated text into a translated text; editing the output data to include the translated text; and generating, using the first layout information, the translated electronic document including the translated text and a second layout that is identical to the first layout.

Abstract: Embodiments of the present invention provide a system that that can be used to determine whether a sentiment analysis model is portable between two data sets. During operation, the system analyzes the text of a respective review in a data set (e.g., a set of reviews) using the sentiment analysis model to determine a sentiment expressed in the review. The system then computes a confidence score, which indicates the accuracy of a respective sentiment. The system subsequently determines a confidence score distribution for various sentiments, as determined by the sentiment analysis model. The system determines the significance of changes between the confidence score distribution and a benchmark confidence score distribution, which is associated with a benchmark data set for which the sentiment analysis model yields a high accuracy. The system can then determine whether the sentiment analysis model is portable to the data set based on the significance of changes.

Abstract: An acoustic signal processing device calculates a signal waveform that a microphone receives when at least one of a sound source and the microphone is moving. The acoustic signal processing device includes a coefficient calculation unit configured to model a steering coefficient gk,m representing how much an amplitude of a sound source signal emitted at an mth discrete time, where m is an integer between 1 and M and M is a length of the sound source signal, is transferred to an amplitude of a signal that the microphone receives at a kth discrete time, where k is an integer between 1 and K and K is a length of a recording signal, using N-order Fourier series expansion where N is an integer of 1 or more, and a recording signal calculation unit configured to calculate the signal waveform that the microphone receives using the modeled steering coefficient gk,m.

Abstract: An electronic device is provided. The electronic device includes a memory configured to store at least one instruction, and at least one processor where the at least one processor is configured to execute the instruction to obtain voice data from a conversation of at least one user, convert the voice data to text data, determine at least one parameter indicating characteristic of the conversation based on at least one of the voice data or the text data, adjust a condition for triggering intervention in the conversation based on the determined at least one parameter, and output a feedback based on the text data when the adjusted condition is satisfied, wherein the adjustment of the condition includes adjusting a first and a second threshold based on change of the at least one parameter.

Abstract: Provided are a speech translation method and apparatus, an electronic device and a storage medium. The method includes: acquiring a source speech corresponding to a to-be-translated language; acquiring a specified target language; inputting the source speech and indication information matched with the target language into a pre-trained speech translation model, where the speech translation model is configured to translate a language in a first language set into a language in a second language set, the first language set includes a plurality of languages, the first language set includes the to-be-translated language, the second language set includes a plurality of languages, and the second language set includes the target language; and acquiring a translated speech corresponding to the target language and output by the speech translation model; where the to-be-translated language is different from the target language.

Abstract: According to one embodiment, a signal processing apparatus correlates a plurality of communication terminals as a group and enables one-to-many communications in the group. The signal processing apparatus includes processing circuitry. The processing circuitry assigns a transmission right to one of the communication terminals in the group. The processing circuitry generates text data based on voice data from said one of the communication terminals in possession of the transmission right. The processing circuitry gives a texting completion notice indicative of completion of texting processing to the communication terminals in the group. The processing circuitry transmits, after the texting completion notice is given, the generated text data to at least one of the communication terminals in the group.

Abstract: One or more embodiments include an emotion analysis system for computing and analyzing emotional state of a user. The emotion analysis system acquires, via at least one sensor, sensor data associated with a user. The emotion analysis system determines, based on the sensor data, an emotional state associated with a user. The emotion analysis system determines a first component of the emotional state that corresponds to media content being accessed by the user. The emotion analysis system applies a first function to the emotional state to remove the first component from the emotional state.

Abstract: A lip-language identification method and an apparatus thereof, an augmented reality device and a storage medium. The lip-language identification method includes: acquiring a sequence of face images for an object to be identified; performing lip-language identification based on a sequence of face images so as to determine semantic information of speech content of the object to be identified corresponding to lip actions in a face image; and outputting the semantic information.

Abstract: An apparatus for encoding an audio signal includes: a core encoder for core encoding first audio data in a first spectral band; a parametric coder for parametrically coding second audio data in a second spectral band being different from the first spectral band, wherein the parametric coder includes: an analyzer for analyzing first audio data in the first spectral band to obtain a first analysis result and for analyzing second audio data in the second spectral band to obtain a second analysis result; a compensator for calculating a compensation value using the first analysis result and the second analysis result; and a parameter calculated for calculating a parameter from the second audio data in the second spectral band using the compensation value.

Abstract: In some examples, a server may receive an utterance from a customer. The utterance may be included in a conversation between the artificial intelligence engine and the customer. The server may convert the utterance to text and determine a customer intent based on the text and a user history. The server may determine a user model of the customer based on the text and the customer intent. The server may update a conversation state associated with the conversation based on the customer intent and the user model. The server may determine a user state based on the user model and the conversation state. The server may select, using a reinforcement learning based module, a particular action from a set of actions, the particular action including a response and provide the response to the customer.

Abstract: An electronic device and a method for controlling the electronic device thereof are provided. The electronic device includes a memory storing instructions, and a processor configured to control the electronic device by executing the instructions stored in the memory, and the processor is configured to, based on a user's speech being input, acquire a first sentence in a first language corresponding to the user's speech through a speech recognition model corresponding to a language of the user's speech, acquire a second sentence in a second language corresponding to the first sentence in the first language through a machine translation model trained to translate a plurality of languages into the predefined second language, and acquire a control instruction of the electronic device corresponding to the acquired second sentence or acquire a response to the second sentence through a natural language understanding model trained based on the second language.

Abstract: A lip language recognition method, applied to a mobile terminal having a sound mode and a silent mode, includes: training a deep neural network in the sound mode; collecting a user's lip images in the silent mode; and identifying content corresponding to the user's lip images with the deep neural network trained in the sound mode. The method further includes: switching from the sound mode to the silent mode when a privacy need of the user arises.

Abstract: According to one embodiment, a system for creating a speaker model includes one or more processors. The processors change a part of network parameters from an input layer to a predetermined intermediate layer based on a plurality of patterns and inputs a piece of speech into each of neural networks so as to obtain a plurality of outputs from the intermediate layer. The part of network parameters of the each of the neural networks is changed based on one of the plurality of patterns. The processors create a speaker model with respect to one or more words detected from the speech based on the outputs.

Abstract: Provided are an apparatus and a method for integrally encoding and decoding a speech signal and a audio signal. The encoding apparatus may include: an input signal analyzer to analyze a characteristic of an input signal; a first conversion encoder to convert the input signal to a frequency domain signal, and to encode the input signal when the input signal is a audio characteristic signal; a Linear Predictive Coding (LPC) encoder to perform LPC encoding of the input signal when the input signal is a speech characteristic signal; and a bitstream generator to generate a bitstream using an output.

Abstract: The system trains a model to provide information used to provide a synthesized speech response to a voice input. The model takes as input prosodic information that may include pitch, note, duration, prominence, timbre, rate, and rhythm, for example. The system receives a plurality of voice inputs, each associated with prosodic metric, as well as a plurality of responses, each also associated with prosodic metrics. The system trains the model based on the plurality of voice inputs, the plurality of responses, the prosodic metrics of the voice inputs, and the prosodic metrics of the responses such that the model outputs information used to generate the response. The model may also take as input user profile information, emotion metrics, and transition information to generate output. The output of the training model may be used by the system to provide synthesized speech responses having relevant prosodic character to received voice inputs.

Abstract: The system provides a synthesized speech response to a voice input, based on the prosodic character of the voice input. The system receives the voice input and calculates at least one prosodic metric of the voice input. The at least one prosodic metric can be associated with a word, phrase, grouping thereof, or the entire voice input. The system also determines a response to the voice input, which may include the sequence of words that form the response. The system generates the synthesized speech response, by determining prosodic characteristics based on the response, and on the prosodic character of the voice input. The system outputs the synthesized speech response, which includes a more natural, relevant, or both answer to the call of the voice input. The prosodic character of the voice input and/or response may include pitch, note, duration, prominence, timbre, rate, and rhythm, for example.

Abstract: A device to process an audio signal representing input sound includes a hand detector configured to generate a first indication responsive to detection of at least a portion of a hand over at least a portion of the device. The device also includes an automatic speech recognition system configured to be activated, responsive to the first indication, to process the audio signal.

Abstract: Systems and methods for handling away messages with intelligent assistance using voice services. In some embodiments, an Information Handling System (IHS) may include: a processor; and a memory coupled to the processor, the memory having program instructions stored thereon that, upon execution, cause the IHS to: detect the presence of a person; output an audio greeting in response to the detection; receive an audio instruction in response to the audio greeting; transmit the audio instruction to a voice service provider, the voice service provider configured to: (i) convert the audio instruction into a text instruction, and (ii) transmit the text instruction to an intelligent assistance provider; receive a command from the intelligent assistance provider, the intelligent assistance provider configured to generate the command based upon the text instruction; and execute the command.