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Robust Speech Recognition in Embedded Systems and PC Applications pp 37–73Cite as

Environment-Independent Adaptive Speech Recognition: A Review of the State of the Art

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Part of the book series: The International Series in Engineering and Computer Science ((SECS,volume 563))

Summary

While in the last decade most of the research focused on how to develop environment-independent automatic speech recognition, recently environment-adaptive systems have attracted much interest. Adaptive systems have been studied to compensate for a large variety of problems: speaking style, speaking rate, non-native speakers, transducers and transmission channels, noise, language, task, etc. In this chapter, we contrast environment-indepenent and environment-adaptive systems. We study environment-independent approaches from two perspectives 1) speech analysis and, feature extraction, and 2) acoustic modeling. We also present a front-end, called phoneme similarity front-end, which is relatively insensitive to speaker variations. Then, we review adaptation/compensation techniques that have been successful at improving ASR robustness by being applicable to a wide range of problems. Finally, we focus on the mainstream methods applicable to noise robust speech recognition with an emphasis on noise-adaptive techniques. While this chapter emphasizes state-of-the-art technology in the domain of robust and adaptive speech recognition, exciting new developments in this area are also discussed in Chapter 5.

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(2002). Environment-Independent Adaptive Speech Recognition: A Review of the State of the Art. In: Robust Speech Recognition in Embedded Systems and PC Applications. The International Series in Engineering and Computer Science, vol 563. Springer, Boston, MA. https://doi.org/10.1007/0-306-47027-6_2

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