Signal and feature domain enhancement approaches for robust speech recognition

Jinkyu Lee, Soonho Baek, Hong Goo Kang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This paper analyzes the impact of various preprocessing modules to improve the performance of automatic speech recognition system (ASR) in noisy environment. After choosing the state-of-the-art algorithms designed in the signal domain and feature domain, their performances in various noise conditions are thoroughly evaluated. Since the enhancement has been directly made to the features that are actually used for recognition, the feature domain approach is more appropriate than the signal domain approach. Experimental results show that the noise reduction in the feature domain gives the best performance.

Original languageEnglish
Title of host publicationICICS 2011 - 8th International Conference on Information, Communications and Signal Processing
DOIs
Publication statusPublished - 2011 Dec 1
Event8th International Conference on Information, Communications and Signal Processing, ICICS 2011 - Singapore, Singapore
Duration: 2011 Dec 132011 Dec 16

Publication series

NameICICS 2011 - 8th International Conference on Information, Communications and Signal Processing

Other

Other8th International Conference on Information, Communications and Signal Processing, ICICS 2011
CountrySingapore
CitySingapore
Period11/12/1311/12/16

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All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

Cite this

Lee, J., Baek, S., & Kang, H. G. (2011). Signal and feature domain enhancement approaches for robust speech recognition. In ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing [6173538] (ICICS 2011 - 8th International Conference on Information, Communications and Signal Processing). https://doi.org/10.1109/ICICS.2011.6173538