GMM-based bandwidth extension using sub-band basis spectrum model

Yamato Ohtani, Masatsune Tamura, Masahiro Morita, Masami Akamine

Research output: Contribution to journalConference article

15 Citations (Scopus)

Abstract

This paper describes a novel GMM-based bandwidth extension (BWE) method based on a sub-band basis spectrum model (SBM), in which each dimensional component represents a specific acoustic space in the frequency domain. The proposed method can achieve the BWE from a speech data with an arbitrary frequency bandwidth while the conventional methods perform the conversion from a fixed narrowband data. In the proposed method, we train a GMM with SBM parameters extracted from wideband spectra in advance. An input signal with a limited frequency band is converted into a wideband signal by estimating high-band SBM components from low-band SBM components of the input signal based on the GMM. The results of some objective and subjective evaluations show that the proposed method extends bandwidth of speech data robustly.

Original languageEnglish
Pages (from-to)2489-2493
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publication statusPublished - 2014 Jan 1
Externally publishedYes
Event15th Annual Conference of the International Speech Communication Association: Celebrating the Diversity of Spoken Languages, INTERSPEECH 2014 - Singapore, Singapore
Duration: 2014 Sep 142014 Sep 18

Keywords

  • Bandwidth extension
  • Gaussian mixture model
  • Speech synthesis
  • Sub-band basis spectrum model
  • Voice conversion

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modelling and Simulation

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