Compression of line spectral frequency parameters with asynchronous interpolation

Rachel Moldover, Alexander Kain

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

TTS systems require a trade-off between size and speech quality. A larger acoustic inventory allows synthesis of speech that sounds more natural. The Asynchronous Interpolation Model improves the quality to size ratio, allowing better compression of large acoustic inventories, as well as better quality speech from a small system. At maximum compression, our method represents most phonemes by a single frame of data. Coarticulation effects are specified as contextspecific non-linear interpolation functions. Dividing the speech features into multiple data streams allows asynchronous interpolation. In this study, AIM was applied to LSF parameters. Varying the number of streams allows for variable amount of compression. We used three different objective measures to investigate the effect of number and partitioning of streams. The first few weight functions (and the last one) seem to offer the most error reduction. Partitions separating the first 6 LSFs score well with all three measures.

Original languageEnglish (US)
Title of host publication2009 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings, ICASSP 2009
Pages3789-3792
Number of pages4
DOIs
StatePublished - 2009
Event2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009 - Taipei, Taiwan, Province of China
Duration: Apr 19 2009Apr 24 2009

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2009 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2009
Country/TerritoryTaiwan, Province of China
CityTaipei
Period4/19/094/24/09

Keywords

  • Acoustic inventory
  • Compression
  • Speech synthesis
  • TTS
  • Temporal decomposition

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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