Efficient vector quantisation of line spectral frequencies using the switched split vector quantiser
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| Title | Efficient vector quantisation of line spectral frequencies using the switched split vector quantiser |
|---|---|
| Author | So, Stephen; Paliwal, Kuldip Kumar |
| Publication Title | Interspeech 2004 (ICSLP) |
| Editor | Soon Hyob Kim and Dae Hee Youn |
| Year Published | 2004 |
| Place of publication | Korea |
| Publisher | Sunjin Printing Co. |
| Abstract | In this paper, we investigate the use of a switched split vector quantiser (SSVQ) for coding linear predictive coding (LPC) parameters. The SSVQ is applied to quantise the LPC parameters in terms of line spectral frequencies from the TIMIT database and its performance is compared with the split vector quantiser. Experimental results show that the SSVQ provides a better trade-off between bit-rate and distortion performance than the split VQ. In addition, the SSVQ has a lower computational (search) complexity than the split VQ, though this is attained at the expense of an increase in memory requirements. In order to achieve a spectral distortion of 1 dB, the three-part SSVQ with an 8 directional switch requires 23 bits/frame, 4.41 kflops/frame of computations and 8272 floats of memory, while the corresponding values for a traditional three-part split VQ are 25 bits/frame, 13.3 kflops/frame and 3328 floats, respectively. |
| Peer Reviewed | Yes |
| Published | Yes |
| Publisher URI | http://www.isca-speech.org/index.php |
| Alternative URI | http://www.isca-speech.org/archive/interspeech_2004/ |
| ISBN | 1225-441X |
| Conference name | 8th International Conference on Spoken Language Processing |
| Location | Jeju Island, Korea |
| Date From | 2004-10-04 |
| Date To | 2004-10-08 |
| URI | http://hdl.handle.net/10072/2124 |
| Date Accessioned | 2005-03-31 |
| Date Available | 2009-09-21T05:51:33Z |
| Language | en_AU |
| Research Centre | Institute for Integrated and Intelligent Systems |
| Faculty | Faculty of Engineering and Information Technology |
| Subject | PRE2009-Speech Recognition |
| Publication Type | Conference Publications (Full Written Paper - Refereed) |
| Publication Type Code | e1 |
Please use this identifier to cite this record: http://hdl.handle.net/10072/2124
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