Making Machines Understand Us in Reverberant Rooms: Robustness Against Reverberation for Automatic Speech Recognition

Speech recognition technology has left the research laboratory and is increasingly coming into practical use, enabling a wide spectrum of innovative and exciting voice-driven applications that are radically changing our way of accessing digital services and information. Most of today's applicat...

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Bibliographic Details
Published in:IEEE signal processing magazine 2012-11, Vol.29 (6), p.114-126
Main Authors: Yoshioka, Takuya, Sehr, A., Delcroix, M., Kinoshita, K., Maas, R., Nakatani, T., Kellermann, W.
Format: Magazinearticle
Language:English
Subjects:
Automatic speech recognition
Excitation spectra
Hidden Markov models
Microphones
Reverberation
Robustness
Speech
Speech recognition
Talking
Television
Translations
Voice recognition
Voice response technology
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Summary:Speech recognition technology has left the research laboratory and is increasingly coming into practical use, enabling a wide spectrum of innovative and exciting voice-driven applications that are radically changing our way of accessing digital services and information. Most of today's applications still require a microphone located near the talker. However, almost all of these applications would benefit from distant-talking speech capturing, where talkers are able to speak at some distance from the microphones without the encumbrance of handheld or body-worn equipment [1]. For example, applications such as meeting speech recognition, automatic annotation of consumer-generated videos, speech-to-speech translation in teleconferencing, and hands-free interfaces for controlling consumer-products, like interactive TV, will greatly benefit from distant-talking operation. Furthermore, for a number of unexplored but important applications, distant microphones are a prerequisite. This means that distant talking speech recognition technology is essential for extending the availability of speech recognizers as well as enhancing the convenience of existing speech recognition applications.
ISSN:1053-5888
1558-0792
DOI:10.1109/MSP.2012.2205029