Speech recognition by machines and humans
Speech Communication
Statistical methods for speech recognition
Statistical methods for speech recognition
Speaker normalization on conversational telephone speech
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
Maximum likelihood discriminant feature spaces
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
The VI framework program in Europe: some thoughts about speech to speech translation research
S2S '02 Proceedings of the ACL-02 workshop on Speech-to-speech translation: algorithms and systems - Volume 7
Multimodal Human Machine Interactions in Virtual and Augmented Reality
Multimodal Signals: Cognitive and Algorithmic Issues
The potential of dwell-free eye-typing for fast assistive gaze communication
Proceedings of the Symposium on Eye Tracking Research and Applications
Integration of multiple acoustic and language models for improved Hindi speech recognition system
International Journal of Speech Technology
| Hi-index | 4.10 |
Providing the computer with a natural interface, including the ability to understand human speech, has been a research goal for almost 40 years. Practical versions of such systems have become moderately usable and commercially successful only in the past few years, however. To date, statistical modeling techniques trained from hundreds of hours of speech have provided most speech recognition advancements. Although it may appear that we have far to go before these systems can match human performance, if researchers maintain the cur-rent rate of yearly progress in reducing word error rates, that objective should be within reach in less than a decade.