14thAnnual Conference of the International Speech Communication Association

Lyon, France
August 25-29, 2013

Accurate and Compact Large Vocabulary Speech Recognition on Mobile Devices

Xin Lei, Andrew Senior, Alexander Gruenstein, Jeffrey Sorensen

Google, USA

In this paper we describe the development of an accurate, smallfootprint, large vocabulary speech recognizer for mobile devices. To achieve the best recognition accuracy, state-of-the-art deep neural networks (DNNs) are adopted as acoustic models. A variety of speedup techniques for DNN score computation are used to enable real-time operation on mobile devices. To reduce the memory and disk usage, on-the-fly language model (LM) rescoring is performed with a compressed n-gram LM. We were able to build an accurate and compact system that runs well below real-time on a Nexus 4 Android phone.

Full Paper

Bibliographic reference.  Lei, Xin / Senior, Andrew / Gruenstein, Alexander / Sorensen, Jeffrey (2013): "Accurate and compact large vocabulary speech recognition on mobile devices", In INTERSPEECH-2013, 662-665.