Abstract

A new label smoothing method that makes use of prior knowledge of a language at human level, homophone, is proposed in this paper for automatic speech recognition (ASR). Compared with its forerunners, the proposed method uses pronunciation knowledge of homophones in a more complex way. End-to-end ASR models that learn acoustic model and language model jointly and modelling units of characters are necessary conditions for this method. Experiments with hybrid CTC sequence-to-sequence model show that the new method can reduce character error rate (CER) by 0.4% absolutely.

Authors

(none)

Tags

  • Speech Recognition
  • Speech Translation

Stats

  • citations0
  • S2 citationsβ€”
  • github stars0
  • HF likes0
  • heat score0.00
  • arxiv keyzheng2020homophone

Related papers