2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSPE-13.5
Paper Title Focus on the present: a regularization method for the ASR source-target attention layer
Authors Nanxin Chen, Piotr Zelasko, Jesús Villalba, Najim Dehak, Johns Hopkins University, United States
SessionSPE-13: Speech Recognition 5: New Algorithms
LocationGather.Town
Session Time:Wednesday, 09 June, 13:00 - 13:45
Presentation Time:Wednesday, 09 June, 13:00 - 13:45
Presentation Poster
Topic Speech Processing: [SPE-LVCR] Large Vocabulary Continuous Recognition/Search
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
Abstract This paper introduces a novel method to diagnose the source-target attention in state-of-the-art end-to-end speech recognition models with joint connectionist temporal classification (CTC) and attention training. Our method is based on the fact that both, CTC and source-target attention, are acting on the same encoder representations. To understand the functionality of the attention, CTC is applied to compute the token posteriors given the attention outputs. We found that the source-target attention heads are able to predict several tokens ahead of the current one. Inspired by the observation, a new regularization method is proposed which leverages CTC to make source-target attention more focused on the frames corresponding to the output token being predicted by the decoder. Experiments reveal stable improvements up to 7% and 13% relatively with the proposed regularization on TED-LIUM 2 and Librispeech.