Automatic Speech Recognition: A Review

Automatic speech recognition (ASR) has been extensively studied during the past few decades. Most of present systems are based on statistical modeling, both at the acoustic and linguistic levels, not only for recognition, but also for understanding. Speech recognition in adverse conditions has recently received increased attention since noise resistance has become one of the major bottlenecks for practical use of speech recognizers. After briefly recalling the basic principles of statistical approaches to ASR (especially in a Bayesian framework), we present the types of solutions that have been proposed so far in order to obtain good performance in real life conditions.