10th Annual Conference of the International Speech Communication Association

Brighton, United Kingdom
September 6-10, 2009

Differential Vector Quantization of Feature Vectors for Distributed Speech Recognition

Jose Enrique Garcia, Alfonso Ortega, Antonio Miguel, Eduardo Lleida

Universidad de Zaragoza, Spain

Distributed speech recognition arises for solving computational limitations of mobile devices like PDAs or mobile phones. Due to bandwidth restrictions, it is necessary to develop efficient transmission techniques of acoustic features in Automatic Speech Recognition applications. This paper presents a technique for compressing acoustic feature vectors based on Differential Vector Quantization. It is a combination of Vector Quantization and Differential encoding schemes. Recognition experiments have been carried out, showing that the proposed method outperforms the ETSI standard VQ system, and classical VQ schemes for different codebook lengths and situations. With the proposed scheme, bit rates as low as 2.1 kbps can be used without decreasing the performance of the ASR system in terms of WER compared with a system without quantization.

Full Paper

Bibliographic reference.  Garcia, Jose Enrique / Ortega, Alfonso / Miguel, Antonio / Lleida, Eduardo (2009): "Differential vector quantization of feature vectors for distributed speech recognition", In INTERSPEECH-2009, 2587-2590.