Attention-Based End-to-End Speech Recognition on Voice Search

Understand

Recently, there has been a growing interest in end-to-end speech recognition that directly transcribes speech to text without any predefined alignments.

• In this paper, we explore the use of attention-based encoder-decoder model for Mandarin speech recognition on a voice search task.
• Previous attempts have shown that applying attention-based encoder-decoder to Mandarin speech recognition was quite difficult due to the logographic orthography of Mandarin, the large vocabulary and the conditional dependency of the attention model.
• In this paper, we use character embedding to deal with the large vocabulary.