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arXiv · 1610.03035

Latent Sequence Decompositions

William Chan·Yu Zhang·Quoc Le·Navdeep Jaitly
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Abstract

We present the Latent Sequence Decompositions (LSD) framework. LSD decomposes sequences with variable lengthed output units as a function of both the input sequence and the output sequence. We present a training algorithm which samples valid extensions and an approximate decoding algorithm. We experiment with the Wall Street Journal speech recognition task. Our LSD model achieves 12.9% WER compared to a character baseline of 14.8% WER. When combined with a convolutional network on the encoder, we achieve 9.6% WER.

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William Chan, Yu Zhang, Quoc Le, Navdeep Jaitly. 2017-02-07. Latent Sequence Decompositions. https://arxiv.org/abs/1610.03035

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