The disclosure provides a method for locating a video playing node, and relates to fields of big data and video processing. The method includes: selecting a target video out from a plurality of videos; and sending the target video, a plurality of subtitle text segments of the target video and start time information of each of the plurality of subtitle text segments to a client, to cause the client to display the plurality of subtitle text segments, and determine, in response to a trigger operation on an any subtitle text segment of the plurality of subtitle text segments, a start playing node of the target video based on the start time information of the any subtitle text segment. The disclosure further provides an apparatus for locating a video playing node, an electronic device and a storage medium.

Sign language information processing method and apparatus, an electronic device and a readable storage medium provided by the present disclosure, achieve real-time collection of language data in a current communication of a user by obtaining voice information and video information collected by a user terminal in real time; and then match a speaking person with his or her speaking content by determining, in the video information, a speaking object corresponding to the voice information; and finally, make it possible for the user to clarify the corresponding speaking object when the user sees AR sign language animation in a sign language video by superimposing and displaying an augmented reality AR sign language animation corresponding to the voice information on a gesture area corresponding to the speaking object to obtain a sign language video. Therefore, it is possible to provide a higher user experience.

Systems and methods for privacy-protecting hybrid cloud and premise stream processing are disclosed. In one embodiment, in an information processing device comprising at least one computer processor, a method for processing a voice communication including restricted content may include: (1) receiving from an electronic device, a customer communication; (2) identifying restricted content in the customer communication; (3) masking or marking the restricted content in the customer communication; (4) communicating the customer communication with the masked or marked restricted content to a cloud processor; (5) receiving a processed responsive communication comprising the masked or marked restricted content from the cloud processor; (6) unmasking or unmarking the restricted content in the processed responsive communication; and (7) communicating the processed responsive communication comprising the unmasked or unmarked restricted content to the electronic device.

In some embodiments, methods and systems for pushing audiovisual playlists based on a text-attentional convolutional neural network include a local voice interactive terminal, a dialog system server and a playlist recommendation engine, where the dialog system server and the playlist recommendation engine are respectively connected to the local voice interactive terminal. In some embodiments, the local voice interactive terminal includes a microphone array, a host computer connected to the microphone array, and a voice synthesis chip board connected to the microphone array. In some embodiments, the playlist recommendation engine obtains rating data based on a rating predictor constructed by the neural network; the host computer parses the data into recommended playlist information; and the voice terminal synthesizes the results and pushes them to a user in the form of voice.

Embodiments for delay-induced miscommunication reduction are provided. The embodiment may include capturing data streams transmitted between participants in an A/V exchange; translating, on a sender device prior to transmission to a recipient device, an audio stream within the data streams to text; timestamping, on a sender device prior to transmission to the recipient device, each word in the translated audio stream; transmitting the audio stream and the sender-side translated and timestamped audio stream to the recipient device; translating, on the recipient device, the transmitted audio stream to text; timestamping, on the recipient device, each word in the translated audio stream; determining a lag exists in the A/V exchange based on a comparison of each timestamp for corresponding words on the sender-side translated and timestamped audio stream and the recipient-side translated and timestamped audio stream; and generating a true transcript of an intended exchange between the participants based on the comparison.

Implementations can reduce the time required to obtain responses from an automated assistant by, for example, obviating the need to provide an explicit invocation to the automated assistant, such as by saying a hot-word/phrase or performing a specific user input, prior to speaking a command or query. In addition, the automated assistant can optionally receive, understand, and/or respond to the command or query without communicating with a server, thereby further reducing the time in which a response can be provided. Implementations only selectively initiate on-device speech recognition responsive to determining one or more condition(s) are satisfied. Further, in some implementations, on-device NLU, on-device fulfillment, and/or resulting execution occur only responsive to determining, based on recognized text form the on-device speech recognition, that such further processing should occur. Thus, through selective activation of on-device speech processing, and/or selective activation of on-device NLU and/or on-device fulfillment, various client device resources are conserved.

A skill dispatching method for a speech dialogue platform including: receiving, by a central control dispatching service, a semantic result of recognizing a user's voice sent by a data distribution service; dispatching, by the central control dispatching service, a plurality of skill services related to the semantic result in parallel, and obtaining skill parsing results from the plurality of skill services; sorting the skill parsing results based on priorities of the skill services, and exporting a result with the highest priority to a skill realization discrimination service; when failure in realization, selecting a result with the highest priority among the rest of skill parsing results and exporting the same to the skill realization discrimination service, and when success in realization, sending the result with the highest priority to the data distribution service for feedback to the user. The method improves skill dispatching efficiency, reduces delay, and improves user experience.

A method implemented by a processor of a computing device, comprising: receiving an image from a camera; using a machine vision process to recognize the at least one real-world object in the image; displaying on a screen an augmented reality (AR) scene containing the at least one real-world object and a virtual agent; receiving user input; deriving a simplified user intent from the user input; and in response to the user input, animating the virtual agent within the AR scene, the animating being dependent on the simplified user intent. Deriving a simplified user intent from the user input may include converting the user input into a user phrase, determining at least one semantic element in the user phrase, and converting the at least one semantic element into the simplified user intent.

Some implementations process, using warm word model(s), a stream of audio data to determine a portion of the audio data that corresponds to particular word(s) and/or phrase(s) (e.g., a warm word) associated with an assistant command, process, using an automatic speech recognition (ASR) model, a preamble portion of the audio data (e.g., that precedes the warm word) and/or a postamble portion of the audio data (e.g., that follows the warm word) to generate ASR output, and determine, based on processing the ASR output, whether a user intended the assistant command to be performed. Additional or alternative implementations can process the stream of audio data using a speaker identification (SID) model to determine whether the audio data is sufficient to identify the user that provided a spoken utterance captured in the stream of audio data, and determine if that user is authorized to cause performance of the assistant command.

Implementations relate to techniques for providing context-dependent search results. A computer-implemented method includes receiving an audio stream at a computing device during a time interval, the audio stream comprising user speech data and background audio, separating the audio stream into a first substream that includes the user speech data and a second substream that includes the background audio, identifying concepts related to the background audio, generating a set of terms related to the identified concepts, influencing a speech recognizer based on at least one of the terms related to the background audio, and obtaining a recognized version of the user speech data using the speech recognizer.