Abstract: Embodiments for providing data content consumption support by a processor. Data from one or more data sources may be captured and received by one or more data capturing devices while a user is consuming the data on the one or more data sources. A domain knowledge may be automatically updated with the data. A response may be provided to one or more queries based upon information accessed from the knowledge domain.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for detecting an end of a query are disclosed. In one aspect, a method includes the actions of receiving audio data that corresponds to an utterance spoken by a user. The actions further include applying, to the audio data, an end of query model. The actions further include determining the confidence score that reflects a likelihood that the utterance is a complete utterance. The actions further include comparing the confidence score that reflects the likelihood that the utterance is a complete utterance to a confidence score threshold. The actions further include determining whether the utterance is likely complete or likely incomplete. The actions further include providing, for output, an instruction to (i) maintain a microphone that is receiving the utterance in an active state or (ii) deactivate the microphone that is receiving the utterance.

Abstract: Techniques and mechanisms for performing a Bayesian inference with a spiking neural network. In an embodiment, a parent node of the spiking neural network receives a first bias signal which is periodic. The parent node communicates a likelihood signal to a child node, wherein the parent node and the child node correspond to a first condition and a second condition, respectively. Based on a phase change which is applied to the first bias signal, the likelihood signal indicates a probability of the first condition. The child node also receives a signal which indicates an instance of the second condition. Based on the indication and a second bias signal, the child node signals to the first node that an adjustment is to be made to the phase change applied to the first bias signal. After the adjustment, the likelihood signal indicates an updated probability of the first condition.

Abstract: The present disclosure provides a pre-training method for a sentiment analysis model and an electronic device, which relates to a field of artificial intelligence technologies. The method includes: based on a given seed sentiment dictionary, performing sentimental knowledge detection on a training corpus in a training corpus set, and determining a detection sentiment word and a detection word pair of the training corpus; according to preset mask processing rules, performing mask process on the training corpus to generate a masked corpus; performing encoding and decoding on the masked corpus by using a preset encoder and decoder to determine the detection sentiment word and the detection word pair of the training corpus; and updating the preset encoder and decoder according to a difference between prediction sentiment word and the detection sentiment word, and a difference between prediction word pair and the detection word pair.

Abstract: A method, computer program product, and a system where a processor(s), monitors multilingual switches performed on a client on behalf of a given user. Based on the monitoring, the processor(s) identifies switch patterns of the given user to generate a service profile for the user of machine learned multilingual switch patterns for the given user. The processor(s) determines a priority order for languages comprising the voice input streams, for the given user. The processor(s) obtains a new translation request initiated by the client, on behalf of the given user and applies the priority order to identify one or more languages spoken in a voice input stream of the new translation request. The processor(s) transmits indicators of the identified one or more languages to the client, where upon receiving the indicators, the client translates the voice input stream from the identified one or more languages to one or more target languages.

Abstract: Provided are a method and device for processing a music file, a terminal and a storage medium. The method comprises: in response to a received sound effect adjustment instruction, acquiring a music file, the adjustment of which is indicated by the sound effect adjustment instruction; carrying out vocals and accompaniment separation on the music file to obtain vocal data and accompaniment data in the music file; carrying out first sound effect processing on the vocal data to obtain target vocal data, and carrying out second sound effect processing on the accompaniment data to obtain target accompaniment data; and synthesizing the target vocal data and the target accompaniment data to obtain a target music file.

Abstract: Methods, apparatus, and processor-readable storage media for artificial intelligence-based redundancy management are provided herein. An example computer-implemented method includes obtaining telemetry data from one or more client devices within at least one system; predicting one or more hardware component failures in at least a portion of the one or more client devices within the at least one system by processing at least a portion of the telemetry data using a first set of one or more artificial intelligence techniques; determining, using a second set of one or more artificial intelligence techniques, one or more redundant hardware components for implementation in connection with the one or more predicted hardware component failures; and performing at least one automated action based at least in part on the one or more redundant hardware components.

Abstract: An arousal support device including a processor programmed to output a dialogue speech in a form of a question, and obtain response speech which is a response of a driver to the dialogue speech; measure a response time from when the dialogue speech is output till the response speech is obtained; store the measured response time in a database; derive an estimated value of wakefulness of the driver based on the measured response time and a plurality of response times previously stored in the database; and output a signal corresponding to the estimated value to provide arousal support.

Abstract: Examples described herein provide a computer-implemented method that includes training, by one or more processing devices, a first neural network for classification based on training data in accordance with a first learning objective, the first neural network producing an intermediate feature function and a final feature function as outputs. The computer-implemented method further includes training, by the one or more processing devices, a second neural network for classification based on the intermediate feature function and the final feature function and further based at least in part on target task samples in accordance with a second learning objective. Training the second neural network includes computing maximal correlation functions of each of the intermediate feature function, the final feature function, and the target task samples.

Abstract: In order to address a conventional problem that there is no information processing apparatus for simulating processing in the brain, an information processing apparatus is configured such that one or more pieces of feature information are transferred between somas, each soma may fire using one or more pieces of accepted feature information, a firing pattern, which is a pattern of firing of one or more somas, is acquired, and output information corresponding to the firing pattern is acquired and output. Accordingly, it is possible to realize information processing for simulating processing in the brain. Also, it is possible to realize information processing for simulating processing in the brain, such as growth processing, apoptosis processing, and learning processing of elements such as somas.

Abstract: One embodiment provides a method, comprising: receiving, at a digital assistant of an information handling device, a query from a user; providing, using the digital assistant, a response to the query; determining, during provision of the response, interest of the user in a topic contained within the response; and providing, based on the interest, extended information related to the topic. Other aspects are described and claimed.

Abstract: A method to present communications is provided. The method may include obtaining, at a device, a request from a user to play back a stored message that includes audio. In response to obtaining the request, the method may include directing the audio of the message to a transcription system from the device. In these and other embodiments, the transcription system may be configured to generate text that is a transcription of the audio in real-time. The method may further include obtaining, at the device, the text from the transcription system and presenting, by the device, the text generated by the transcription system in real-time. In response to obtaining the text from the transcription system, the method may also include presenting, by the device, the audio such that the text as presented is substantially aligned with the audio.

Abstract: A method of generating a digital audio-visual sequence comprising one or more three-dimensional structures and an audio stream in real time is disclosed, comprising the steps of capturing and processing vocal input from a user, identifying at least one semantic construct from the captured vocal input, matching identified semantic construct with at least one structure tag and at least one case tag, wherein the structure tag is associated with a three-dimensional structure and the case tag is associated with an alphanumerical description of the three-dimensional structure, and generating a sequence based on one or more matched structure tag(s) and one or more matched case tag(s). Generating comprises scheduling synchronous rendering of the three-dimensional structure in a user interface and voice synthesising of the alphanumerical description.

Abstract: Systems and processes for operating an intelligent automated assistant are provided. In one example process, a first input including activation of an affordance is received. A domain associated with the affordance is determined. A second input including user speech is received, where a user intent is determined based on the domain and the user speech. A determination is made whether the user intent includes a command associated with the affordance. In accordance with a determination that the user intent includes a command associated with the affordance, a task in furtherance of the command is performed.

Abstract: A method includes generating style values and experiential language tags (ELTs) for a plurality of books based on retrieved book content and reader reviews, respectively. The method further includes generating an ELT prediction model based on the style values and the ELTs. The ELT prediction model is configured to receive a set of style values for a new book and output a set of predicted ELTs for the new book, the set of predicted ELTs indicating predicted reader experiences with the new book. The method further includes receiving user-submitted book content from a remote user device, determining style values for the user-submitted book content, and determining a list of predicted ELTs for the user-submitted book content using the style values for the user-submitted book content and the ELT prediction model. Additionally, the method includes transmitting, to the user device, the list of predicted ELTs for the user-submitted book content.

Abstract: A method and system of reducing noise associated with telephony-based activities occurring in shared workspaces is provided. An end-user may lower their own voice to a whisper or other less audible or intelligible utterances and submit such low-quality audio signals to an automated speech recognition system via a microphone. The words identified by the automated speech recognition system are provided to a speech synthesizer, and a synthesized audio signal is created artificially that carries the content of the original human-produced utterances. The synthesized audio signal is significantly more audible and intelligible than the original audio signal. The method allows customer support agents to speak at barely audible levels yet be heard clearly by their customers.

Abstract: A natural language processing (NLP) apparatus includes a housing, a built-in voice input interface; a built-in data communication interface configured to establish data communication with multiple types of appliances; a built-in NLP module, and a built-in control device. A first voice input is received through the built-in voice input interface; if the target appliance is a first appliance of a first appliance type, the first voice input is processed using a first NLP model of the built-in NLP module to obtain a first machine command, and the first machine command is sent via the built-in data communication interface to the first appliance; and if the target appliance is a second appliance of a second appliance type, the first voice input is processed using a second NLP model of the built-in NLP module, and the second machine command is sent via the built-in data communication interface to the second appliance.

Abstract: Coordinated operation of a voice-controlled device and an accessory device in an environment is described. A remote system processes audio data it receives from the voice-controlled device in the environment to identify a first intent associated with a first domain, a second intent associated with a second domain, and a named entity associated with the audio data. The remote system sends, to the voice-controlled device, first information for accessing main content associated with the named entity, and a first instruction corresponding to the first intent. The remote system also sends, to the accessory device, second information for accessing control information or supplemental content associated with the main content, and a second instruction corresponding to the second intent. The first and second instructions, when processed by the devices in the environment, cause coordinated operation of the voice-controlled device and the accessory device.

Abstract: A communication robot capable of communicating with other electronic devices and an external server in a 5G communication environment by performing artificial intelligence (AI) algorithms and/or machine learning algorithms to be loaded and performing a speech recognition, and a driving method thereof are disclosed. The method for driving a communication robot according to an exemplary embodiment of the present disclosure may include receiving an utterance speech uttered by a user who has approached within a predetermined distance from the communication robot, and selecting any one ASR module capable of processing the uttered speech among plural ASR modules as an optimized ASR module. According to the present disclosure, it is possible to improve user's satisfaction with the use of the communication robot by reducing the inconvenience that the user has to manually set a first language in the preprocessing operation in order to receive a service from the communication robot.

Abstract: A decoder for generating an audio output signal having one or more audio output channels is provided, having a receiving interface for receiving an audio input signal having a plurality of audio object signals, for receiving loudness information on the audio object signals, and for receiving rendering information indicating whether one or more of the audio object signals shall be amplified or attenuated, further having a signal processor for generating the one or more audio output channels of the audio output signal, configured to determine a loudness compensation value depending on the loudness information and depending on the rendering information, and configured to generate the one or more audio output channels of the audio output signal from the audio input signal depending on the rendering information and depending on the loudness compensation value. One or more by-pass audio object signals are employed for generating the audio output signal. Moreover, an encoder is provided.