Speech Recognition Leaps Forward

During Interspeech 2011, the 12th annual
Conference of the International Speech Communication Association being held in
Florence, Italy, from Aug. 28 to 31, researchers from Microsoft Research will
present work that dramatically improves the potential of real-time,
speaker-independent, automatic speech recognition.
Dong
Yu, researcher at Microsoft
Research Redmond, and Frank Seide,
senior researcher and research manager with Microsoft
Research Asia, have been spearheading this work, and their teams have
collaborated on what has developed into a research breakthrough in the use of
artificial neural networks for large-vocabulary speech recognition.
The Holy Grail of Speech Recognition
Commercially available speech-recognition technology is behind applications
such as voice-to-text software and automated phone services. Accuracy is
paramount, and voice-to-text typically achieves this by having the user “train�
the software during setup and by adapting more closely to the user’s speech
patterns over time. Automated voice services that interact with multiple
speakers do not allow for speaker training because they must be usable instantly
by any user. To cope with the lower accuracy, they either handle only a small
vocabulary or strongly restrict the words or patterns that users can say.
The ultimate goal of automatic speech recognition is to deliver
out-of-the-box, speaker-independent speech-recognition services—a system that
does not require user training to perform well for all users under all
conditions. Full Story At Source
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