PDF-optimized LSF vector quantization based on beta mixture models
2010 (English)In: Proceedings of the 11th Annual Conference of the International Speech Communication Association, INTERSPEECH 2010, 2010, 2374-2377 p.Conference paper (Refereed)
The line spectral frequencies (LSF) are known to be the mostefficient representation of the linear predictive coding (LPC) parametersfrom both the distortion and perceptual point of view.By considering the bounded property of the LSF parameters,we apply beta mixture models (BMM) to model the distributionof the LSF parameters. Meanwhile, by following the principlesof probability density function (PDF) optimized vector quantization(VQ), we derive the bit allocation strategy for the BMM.The LSF parameters are obtained from the TIMIT database anda practical VQ is designed. By taking the Bayesian informationcriterion (BIC), the square error (SE) and the spectral distortion(SD) as the criteria, the BMM based VQ outperforms theGaussian mixture model based VQ with uncorrelated Gaussiancomponent (UGMVQ) by about 1-2 bits/vector.
Place, publisher, year, edition, pages
2010. 2374-2377 p.
speech coding, vector quantization, line spectral frequencies, beta mixture model, Gaussian mixture model
Other Electrical Engineering, Electronic Engineering, Information Engineering Computer Science
Research subject SRA - ICT
IdentifiersURN: urn:nbn:se:kth:diva-33678ISI: 000313086500206ScopusID: 2-s2.0-79959854021ISBN: 978-1-61782-123-3OAI: oai:DiVA.org:kth-33678DiVA: diva2:416996
11th Annual Conference of the International Speech Communication Association: Spoken Language Processing for All, INTERSPEECH 2010; Makuhari, Chiba; 26 September 2010 through 30 September 2010
QC 201111172011-05-132011-05-132014-01-09Bibliographically approved