Tencent Technology (Shenzhen) Company Limited

Huawei Technologies Co., Limited

Tencent Technology Company Limited

Min Luo

Dan Su

Meng Yu

Yi Gao

Lianwu Chen

Qi Chen

Xing Ji

Wei Dong Chen

Bin Huang

Yi Tong Wang

Jie Chen

Xiaolong Zhu

Zheng Zhou

Ke Lin

Jianchen Zhu

Yulu Zhang

Jingliang Bai

Xun Luo

Li Huang

Jie Fan

Yitong Wang

Lijian Mei

Yuan Fang

Yongsheng Liu

Shenghui Huang

Ian Ernan Liu

Caisheng Ouyang

Shanmin Tang

Tianxiao Fu

Bing Gong

Ji Meng Zheng

Xiao Long Zhu

Ren Jian Chen

Lin Luo

Haikang Liu

Wanyu Huang

Shao Bin Lin

Wu Chou

A data processing method based on simultaneous interpretation, applied to a server in a simultaneous interpretation system, including: obtaining audio transmitted by a simultaneous interpretation device; processing the audio by using a simultaneous interpretation model to obtain an initial text; transmitting the initial text to a user terminal; receiving a modified text fed back by the user terminal, the modified text being obtained after the user terminal modifies the initial text; and updating the simultaneous interpretation model according to the initial text and the modified text.

Data processing method based on simultaneous interpretation, computer device, and storage medium

A method for speech recognition based on language adaptivity comprises obtaining voice data of a user. The method also comprises extracting, based on the obtained voice data, a phoneme feature representing pronunciation phoneme information. The phoneme feature is input to a pre-trained language discrimination model that is pre-trained based on a multilingual corpus. A language discrimination result corresponding to the phoneme feature and in accordance with the language discrimination model is obtained. The method also comprises obtaining a speech recognition result of the voice data based on a language acoustic model of a language corresponding to the language discrimination result. The method further comprises determining a speech recognition result of the voice data based on a language acoustic model of a language corresponding to the language discrimination result.

Method for speech recognition based on language adaptivity and related apparatus

This application discloses a method for training a gaze tracking model, including: obtaining a training sample set; processing the eye sample images in the training sample set by using an initial gaze tracking model to obtain a predicted gaze vector of each eye sample image; determining a model loss according to a cosine distance between the predicted gaze vector and the labeled gaze vector for each eye sample image; and iteratively adjusting one or more reference parameters of the initial gaze tracking model until the model loss meets a convergence condition, to obtain a target gaze tracking model. According to the solution provided in this application, a gaze tracking procedure is simplified, a difference between a predicted value and a labeled value can be better represented by using the cosine distance as a model loss to train a model, to improve prediction accuracy of the gaze tracking model.

Method and apparatus for training gaze tracking model, and method and apparatus for gaze tracking

A keyword detection method includes: obtaining an enhanced speech signal of a to-be-detected speech signal, the enhanced speech signal corresponding to a target speech speed; performing speed adjustment on the enhanced speech signal to obtain a first speed-adjusted speech signal having a first speech speed, the first speech speed being different from the target speech speed; obtaining a first speech feature signal according to the first speed-adjusted speech signal; obtaining a detection result according to a first keyword detection result corresponding to the first speech feature signal, the detection result indicating whether a target keyword exists in the to-be-detected speech signal; and performing an operation corresponding to the target keyword in response to determining that the target keyword exists according to the detection result.

Keyword detection method and related apparatus

A video editing method, apparatus and storage medium are provided. The method includes obtaining an object, the object including one or more images; determining a content element of the object for video editing, the content element having a content type identifier; determining a material set identifier corresponding to the content type identifier according to a first behavior tree logic; determining a video editing material set corresponding to the material set identifier; and obtaining an edited video according to the content element and the video editing material set.

Video editing method, apparatus, and device, and storage medium

A method of generating content information that matches at least one stored keyword is described. At least one keyword associated with content information is stored. At least one previously searched keyword in a search record is matched with the at least one stored keyword associated with the content information. First-category mapping data is generated based on a first mapping between the matched at least one stored keyword and the at least one previously searched keyword. Second-category mapping data is generated based on the content information and the at least one stored keyword. A received target keyword is determined to be included in the first-category mapping data. In response to the received target keyword, which is included in the first-category mapping data, circuitry of a terminal searches for the content information associated with the target keyword in the second-category mapping data and displays the content information.

Information processing method and apparatus

The present disclosure describes a method, apparatus, and storage medium for performing speech recognition. The method includes acquiring, by an apparatus, first to-be-processed speech information. The apparatus includes a memory storing instructions and a processor in communication with the memory. The method includes acquiring, by the apparatus, a first pause duration according to the first to-be-processed speech information; and in response to the first pause duration being greater than or equal to a first threshold, performing, by the apparatus, speech recognition on the first to-be-processed speech information to obtain a first result of sentence segmentation of speech, the first result of sentence segmentation of speech being text information, the first threshold being determined according to speech information corresponding to a previous moment.

Method, apparatus, and storage medium for segmenting sentences for speech recognition

A method for detecting a keyword, applied to a terminal, includes: extracting a speech eigenvector of a speech signal; obtaining, according to the speech eigenvector, a posterior probability of each target character being a key character in any keyword in an acquisition time period of the speech signal; obtaining confidences of at least two target character combinations according to the posterior probability of each target character; and determining that the speech signal includes the keyword upon determining that all the confidences of the at least two target character combinations meet a preset condition. The target character is a character in the speech signal whose pronunciation matches a pronunciation of the key character. Each target character combination includes at least one target character, and a confidence of a target character combination represents a probability of the target character combination being the keyword or a part of the keyword.

Method for detecting keyword in speech signal, terminal, and storage medium

A speech recognition method, apparatus, a computer device and an electronic device for recognizing speech. The method includes receiving an audio signal obtained by a microphone array; performing a beamforming processing on the audio signal in a plurality of target directions to obtain a plurality of beam signals; performing a speech recognition on each of the plurality of beam signals to obtain a plurality of speech recognition results corresponding to the plurality of beam signals; and determining a speech recognition result of the audio signal based on the plurality of speech recognition results of the plurality of beam signals.

Method and apparatus for speech recognition, and electronic device

Embodiments of the present invention provide a speech signal processing model training method, an electronic device and a storage medium. The embodiments of the present invention determines a target training loss function based on a training loss function of each of one or more speech signal processing tasks; inputs a task input feature of each speech signal processing task into a starting multi-task neural network, and updates model parameters of a shared layer and each of one or more task layers of the starting multi-task neural network corresponding to the one or more speech signal processing tasks by minimizing the target training loss function as a training objective, until the starting multi-task neural network converges, to obtain a speech signal processing model.

Training method of speech signal processing model with shared layer, electronic device and storage medium

A method for data retrieval is described. Interface circuitry of an information processing apparatus receives a request for data retrieval from a database. The database stores content sharing information in a social network. The request includes a first user identifier and a first link identifier. The processing circuitry determines whether the first user identifier and the first link identifier are associated in the database as a consequence of a previous sharing of a first article corresponding to the first link identifier using the first user identifier. Further, when the first user identifier and the first link identifier are determined to be associated, the processing circuitry searches for a first message identifier in the database. The first message identifier identifies a first message that includes information of the previous sharing of the first article. The processing circuitry then retrieves the first message according to the first message identifier.

Data retrieval method and system

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Shenzhen, China

Min Luo