2nd Workshop on Spoken Language Technologies for Under-Resourced Languages

Universiti Sains, Penang, Malaysia
May 3-5, 2010

Optimization on Vietnamese Large Vocabulary Speech Recognition

Ngoc Thang Vu, Tanja Schultz

Cognitive Systems Lab (CSL), Institute for Anthropomatics, Karlsruhe Institute of Technology (KIT), Germany

This paper summarizes our latest efforts toward a large vocabulary speech recognition system for Vietnamese. We describe the Vietnamese text and speech database which we collected as part of our GlobalPhone corpus. Based on these data we improve our initial Vietnamese recognition system [1] by applying various state-of-the art techniques such as semi-tied covariance and discriminative training. Furthermore, we achieve significant improvements by building two systems based on different tone modeling approaches and then apply system cross-adaptation and confusion networks combination. The best Vietnamese speech recognition system employs a 3-pass decoding strategy and achieves a syllablebased error rate of 7.9% on read newspaper speech. In addition, we perform initial experiments on the Voice of Vietnam (VOV) speech corpus [2] and achieve a syllable error rate of 16.5%.

Index Terms: Vietnamese speech recognition, data collection, discriminative training, system combination

References

  1. Ngoc Thang Vu and Tanja Schultz. Vietnamese Large Vocabulary Continuous Speech Recognition. In: ASRU, Italy 2009.
  2. Thang Tat Vu, Dung Tien Nguyen, Mai Chi Luong and John-Paul Hosom. Vietnamese Large Vocabulary Continuous Speech Recognition. In: 9th European Conference on Speech Communication and Technology, Lisbon, Portugal, 2005.

Full Paper

Bibliographic reference.  Vu, Ngoc Thang / Schultz, Tanja (2010): "Optimization on Vietnamese large vocabulary speech recognition", In SLTU-2010, 104-110.