Glottal vocoding with frequency-warped time-weighted linear prediction

Manu Airaksinen*, Bajibabu Bollepalli, Jouni Pohjalainen, Paavo Alku

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

4 Citations (Scopus)


Linear prediction (LP) is a prevalent source-filter separation method of speech production. One of the drawbacks of conventional LP-based approaches is the biasing of estimated formants by harmonic peaks. Methods such as discrete all-pole modeling and weighted LP have been proposed to overcome this problem, but they all use a linear frequency scale. This study proposes a new LP technique, frequency-warped time-weighted linear prediction (WWLP), to provide spectral envelope estimates robust to harmonic peaks that work on a warped frequency scale that approximates the sensitivities of the human auditory system. Experiments are performed within the context of vocoding in statistical parametric speech synthesis. Subjective listening test results show that WWLP-based spectral envelope modeling increases quality over previously developed methods.

Original languageEnglish
Article number7847373
Pages (from-to)446-450
Number of pages5
JournalIEEE Signal Processing Letters
Issue number4
Publication statusPublished - 1 Apr 2017
MoE publication typeA1 Journal article-refereed


  • Frequency warping
  • linear prediction (LP)
  • source-filter model
  • speech synthesis


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