An application of discriminative feature extraction to filter-bank-based speech recognition

By A. Biem, Shigeru Katagiri, Erik McDermott, Biing-Hwang Fred Juang. 2001

98 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Signal Processing

How researchers see this paper

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

In Artificial Intelligence

1. Li Deng
2. Xiao Li
3. Dong Yu
4. Jonathan Le Roux
5. Erik McDermott
6. Xiaodong He
7. Atsushi Nakamura
8. Tara N. Sainath

In Signal Processing

1. Xiao Li
2. Li Deng
3. Dong Yu
4. Erik McDermott
5. Jonathan Le Roux
6. Jinyu Li
7. Shigeru Katagiri
8. Atsushi Nakamura

Citations in the corpus

• Discriminative Training for Large-Vocabulary Speech Recognition Using Minimum Classification Error (2007, methodology): “Still within speech recognition, there has been significant work applying MCE to feature extraction [35], [36].”
• Machine Learning Paradigms for Speech Recognition: An Overview (2013, methodology): “This approach was later extended to use filter-bank parameters, also jointly with the HMM parameters, with similar success [126].”