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TrimTail: Low-Latency Streaming ASR with Simple but Effective Spectrogram-Level Length Penalty. (arXiv:2211.00522v1 [cs.SD])
Nov. 2, 2022, 1:15 a.m. | Xingchen Song, Di Wu, Zhiyong Wu, Binbin Zhang, Yuekai Zhang, Zhendong Peng, Wenpeng Li, Fuping Pan, Changbao Zhu
cs.CL updates on arXiv.org arxiv.org
In this paper, we present TrimTail, a simple but effective emission
regularization method to improve the latency of streaming ASR models. The core
idea of TrimTail is to apply length penalty (i.e., by trimming trailing frames,
see Fig. 1-(b)) directly on the spectrogram of input utterances, which does not
require any alignment. We demonstrate that TrimTail is computationally cheap
and can be applied online and optimized with any training loss or any model
architecture on any dataset without any extra …
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