Publications (5)
Self-Training Large Language Models for Tool-Use Without Demonstrations
Ne Luo, Aryo Pradipta Gema, Xuanli He +3
Large language models (LLMs) remain prone to factual inaccuracies and computational errors, including hallucinations and mistakes in mathematical reasoning. Recent work augmented L…
A Further Study of Unsupervised Pre-training for Transformer Based Speech Recognition
Dongwei Jiang, Wubo Li, Ruixiong Zhang +5
Building a good speech recognition system usually requires large amounts of transcribed data, which is expensive to collect. To tackle this problem, many unsupervised pre-training…
Towards End-to-End Code-Switching Speech Recognition
Ne Luo, Dongwei Jiang, Shuaijiang Zhao +3
Code-switching speech recognition has attracted an increasing interest recently, but the need for expert linguistic knowledge has always been a big issue. End-to-end automatic spee…
Improving Transformer-based Speech Recognition Using Unsupervised Pre-training
Dongwei Jiang, Xiaoning Lei, Wubo Li +4
Speech recognition technologies are gaining enormous popularity in various industrial applications. However, building a good speech recognition system usually requires large amount…
DiDiSpeech: A Large Scale Mandarin Speech Corpus
Tingwei Guo, Cheng Wen, Dongwei Jiang +8
This paper introduces a new open-sourced Mandarin speech corpus, called DiDiSpeech. It consists of about 800 hours of speech data at 48kHz sampling rate from 6000 speakers and the…