Papers with word error rate reduction

2 papers
KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos (D18-2)

Copied to clipboard

Challenge: KT-Speech-Crawler is an automated dataset building tool for speech recognition.
Approach: They propose an approach for automatic dataset construction for speech recognition by crawling YouTube videos.
Outcome: The proposed algorithm can obtain 150 hours of transcribed speech in a day with an estimated 3.5% word error rate.
Non-Autoregressive Chinese ASR Error Correction with Phonological Training (2022.naacl-main)

Copied to clipboard

Challenge: Existing methods to correct ASR errors focus on fixed-length corrections, but rarely consider variable-length ones.
Approach: They propose a non-autoregressive method to correct Chinese ASR errors . they use phonological tokens to extend the source sentence for variable-length correction .
Outcome: The proposed method improves word error rate and speeds up inference by 6.2 times compared with the autoregressive model.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations