The AT&T WATSON Speech Recognizer
Vincent Goffin, Cyril Allauzen, Enrico Bocchieri, Dilek Zeynep Hakkani-Tür, Andrej Ljolje, Srinivas Parthasarathy, Mohammad Asifur Rahim, Giuseppe Riccardi, Murat Saraçlar · 2006
This paper describes the AT&T WATSON real-time speech recognizer, the product of several decades of research at AT&T. The recognizer handles a wide range of vocabulary sizes and is based on continuous-density hidden Markov models for acoustic modeling and finite state networks for language modeling. The recognition network is optimized for efficient search. We identify the algorithms used for high-accuracy, real-time and low-latency recognition. We present results for small and large vocabulary tasks taken from the AT&T VoiceTone/sup /spl reg// service, showing word accuracy improvement of about 5% absolute and real-time processing speed-up by a factor between 2 and 3.