ISCA Archive Interspeech 2009
ISCA Archive Interspeech 2009

Differential vector quantization of feature vectors for distributed speech recognition

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

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.


doi: 10.21437/Interspeech.2009-681

Cite as: Garcia, J.E., Ortega, A., Miguel, A., Lleida, E. (2009) Differential vector quantization of feature vectors for distributed speech recognition. Proc. Interspeech 2009, 2587-2590, doi: 10.21437/Interspeech.2009-681

@inproceedings{garcia09b_interspeech,
  author={Jose Enrique Garcia and Alfonso Ortega and Antonio Miguel and Eduardo Lleida},
  title={{Differential vector quantization of feature vectors for distributed speech recognition}},
  year=2009,
  booktitle={Proc. Interspeech 2009},
  pages={2587--2590},
  doi={10.21437/Interspeech.2009-681}
}