Acoustic Modeling for Google Home

Li, Bo; Sainath, Tara N.; Narayanan, Arun; Caroselli, Joe; Bacchiani, Michiel; Misra, Ananya; Shafran, Izhak; Sak, Haşim; Pundak, Golan; Chin, Kean; Sim, Khe Chai; Weiss, Ron J.; Wilson, Kevin W.; Variani, Ehsan; Kim, Chanwoo; Siohan, Olivier; Weintraub, Mitchel; McDermott, Erik; Rose, Richard; Shannon, Matt

doi:10.21437/Interspeech.2017-234

Acoustic Modeling for Google Home

Bo Li, Tara N. Sainath, Arun Narayanan, Joe Caroselli, Michiel Bacchiani, Ananya Misra, Izhak Shafran, Haşim Sak, Golan Pundak, Kean Chin, Khe Chai Sim, Ron J. Weiss, Kevin W. Wilson, Ehsan Variani, Chanwoo Kim, Olivier Siohan, Mitchel Weintraub, Erik McDermott, Richard Rose, Matt Shannon

This paper describes the technical and system building advances made to the Google Home multichannel speech recognition system, which was launched in November 2016. Technical advances include an adaptive dereverberation frontend, the use of neural network models that do multichannel processing jointly with acoustic modeling, and Grid-LSTMs to model frequency variations. On the system level, improvements include adapting the model using Google Home specific data. We present results on a variety of multichannel sets. The combination of technical and system advances result in a reduction of WER of 8–28% relative compared to the current production system.