Kwai Inc.

Heng Liu

Yang Liu

Lingzhi Liu

Yongxiong Ren

Qiang Li

Xiaorui Wang

Yuanyuan Zhao

Kaituo Xu

Systems and methods are provided for automatic speech recognition. In the method, the system obtains a padded sequence by processing a plurality of acoustic signals. The system compresses the padded sequence by reducing the size of the padded sequence to obtain a compressed sequence. The system inputs the compressed sequence into a pre-trained encoder neural network to obtain an encoded sequence and then decompresses the encoded sequence by recovering the encoded sequence to an original sequential ordering. The system inputs the encoded sequence to a decoding module to obtain recognition texts.

Systems and methods for accelerating automatic speech recognition based on compression and decompression

An automatic speech recognition system and a method thereof are provided. The system includes an encoder and a decoder. The encoder comprises a plurality of encoder layers. At least one encoder layer includes a plurality of encoder sublayers fused into one or more encoder kernels. The system further comprises a first pair of ping-pong buffers communicating with the one or more encoder kernels. The decoder comprises a plurality of decoder layers. At least one decoder layer includes a plurality of decoder sublayers fused into one or more decoder kernels. The decoder receives a decoder output related to the encoder output and generates a decoder output. The encoder sends the decoder output to a beam search kernel.

Systems and methods for automatic speech recognition based on graphics processing units

The present disclosure relates to an automatic speech recognition system and a method thereof. The system includes a conformer encoder and a pair of ping-pong buffers. The encoder includes a plurality of encoder layers sequentially executed by one or more graphic processing units. At least one encoder layer includes a first feed forward module, a multi-head self-attention module, a convolution module, and a second feed forward module. The convolution module and the multi-head self-attention module are sandwiched between the first feedforward module and the second feed forward module. The four modules respectively include a plurality of encoder sublayers fused into one or more encoder kernels. The one or more encoder kernels respectively read from one of the pair of ping-pong buffers and write into the other of the pair of ping-pong buffers.

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Tucson, AZ, United States of America

Heng Liu