Recognition of Multilingual Speech in Mobile Applications
Venue
ICASSP (2012)
Publication Year
2012
Authors
Hui Lin, Jui-Ting Huang, Francoise Beaufays, Brian Strope, Yun-hsuan Sung
BibTeX
Abstract
We evaluate different architectures to recognize multilingual speech for real-time
mobile applications. In particular, we show that combining the results of several
recognizers greatly outperforms other solutions such as training a single large
multilingual system or using an explicit language identification system to select
the appropriate recognizer. Experiments are conducted on a trilingual
English-French-Mandarin mobile speech task. The data set includes Google searches,
Maps queries, as well as more general inputs such as email and short message
dictation. Without pre-specifying the input language, the combined system achieves
comparable accu- racy to that of the monolingual systems when the input language is
known. The combined system is also roughly 5% absolute better than an explicit
language identification approach, and 10% better than a single large multilingual
system.
