Tencent Technology (shenzhen) Company Limited

Tencent Technology Company Limited

Xilin Zhang

Bo Dong Liu

Li Hui Lu

Shuo Liu

Bo Liu

Jianxiong Ma

Haipeng Wang

Shilun Lin

Xinhui Li

Xiucai Jiang

Ping Zheng

Wenhua Ma

A computer device acquires speech content. The device performs feature extraction on the speech content to obtain an intermediate feature. The intermediate feature is used for indicating an audio expression characteristic of the speech content. The device decodes the intermediate feature based on an attention mechanism to obtain a first word graph network. The device performs feature mapping on the intermediate feature based on pronunciation of the speech content to obtain a second word graph network. The device determines a recognition result of the speech content according to candidate word connection relationships indicated by the first word graph network and the second word graph network.

Speech recognition method and apparatus, device, storage medium, and program product

A speech recognition method includes: obtaining speech data; performing feature extraction on speech data, to obtain speech features of at least two speech segments; inputting the speech features of the at least two speech segments into the speech recognition model, and processing the speech features of the speech segments by using cascaded hidden layers in the speech recognition model, to obtain hidden layer features of the speech segments, a hidden layer feature of an ispeech segment being determined based on speech features of n speech segments located after the ispeech segment in a time sequence and a speech feature of the ispeech segment; and obtaining text information corresponding to the speech data based on the hidden layer features of the speech segments.

Speech recognition method and apparatus with cascaded hidden layers and speech segments, computer device, and computer-readable storage medium

A speech recognition method includes: obtaining speech information; and determining beginning and ending positions of a candidate speech segment in the speech information by using a weighted finite state transducer (WFST) network. The candidate speech segment is identified as corresponding to a preset keyword. The method also includes clipping the candidate speech segment from the speech information according to the beginning and ending positions of the candidate speech segment; detecting whether the candidate speech segment includes a preset keyword by using a machine learning model; and determining, upon determining that the candidate speech segment comprises the preset keyword, that the speech information comprises the preset keyword.

Speech recognition method, apparatus, and device, and storage medium

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Shenzhen, China

Xilin Zhang