Lightly Supervised Acoustic Model Training

By Lori Faith Lamel, Jean-Luc Gauvain, Gilles Adda. 2000

58 citations recorded by the source corpus.

Subfields: Speech & Audio

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Speech & Audio

1. Yu Zhang
2. Yonghui Wu
3. Chung-Cheng Chiu
4. Jinyu Li
5. Ye Jia
6. Ruoming Pang
7. Wei Han
8. James Qin

Citations in the corpus

• Pushing the Limits of Semi-Supervised Learning for Automatic Speech Recognition (2020, methodology): “Self-training has been a popular technique in ASR studied extensively in the literature [25–33].”
• Improved Noisy Student Training for Automatic Speech Recognition (2020, background): “Gradational growth of the labelled dataset in self-training has been used in [21].”
• Unsupervised training of acoustic models for large vocabulary continuous speech recognition (2005, background): “In [4], [5], and [6], closed captions are used instead of confidence measures to filter the recognized transcriptions.”