Frequency Domain Prediction of Tonal Signals With Time-Varying Pitches

In this letter, we propose an Extended Frequency Domain Joint Harmonics Prediction (EFDJHP) algorithm, which does long term prediction directly in the transform domain on tonal signals with time-varying pitches for transform speech and audio coding. EFDJHP is an algorithm extension of a previously proposed Frequency Domain Joint Harmonics Prediction (FDJHP) algorithm where a constant pitch between neighboring frames was assumed (Guo and Edler, 2021). A linearly changing pitch between adjacent frames is assumed in EFDJHP, where the linearity can be assumed to be local and updated across frames. EFDJHP works in a backward prediction fashion without additional algorithmic delay, and needs very few side information for the forward adaption of the predictor coefficients. Bitrate saving analysis and a listening test show that EFDJHP can improve the coding efficiency on tonal signals with frequent pitch variations such as singing voices and speech.

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Publication Details

Journal
IEEE Signal Processing Letters
Published
2024-11-04
DOI
https://doi.org/10.1109/lsp.2024.3491033
Primary Topic
Speech and Audio Processing
Type
article
Field-Weighted Citation Impact
0.00
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article

Frequency Domain Prediction of Tonal Signals With Time-Varying Pitches

Bernd Edler, Ning Guo
IEEE Signal Processing Letters
Speech and Audio Processing
article

Frequency Domain Prediction of Tonal Signals With Time-Varying Pitches

Bernd Edler, Ning Guo
article en

Abstract

In this letter, we propose an Extended Frequency Domain Joint Harmonics Prediction (EFDJHP) algorithm, which does long term prediction directly in the transform domain on tonal signals with time-varying pitches for transform speech and audio coding. EFDJHP is an algorithm extension of a previously proposed Frequency Domain Joint Harmonics Prediction (FDJHP) algorithm where a constant pitch between neighboring frames was assumed (Guo and Edler, 2021). A linearly changing pitch between adjacent frames is assumed in EFDJHP, where the linearity can be assumed to be local and updated across frames. EFDJHP works in a backward prediction fashion without additional algorithmic delay, and needs very few side information for the forward adaption of the predictor coefficients. Bitrate saving analysis and a listening test show that EFDJHP can improve the coding efficiency on tonal signals with frequent pitch variations such as singing voices and speech.

IEEE Signal Processing LettersVol. 32
International Audio Laboratories Erlangen (DE), Fraunhofer Institute for Integrated Circuits (DE)
Openalex Percentile: Top 79%
Speech and Audio Processing
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Frequency Domain Prediction of Tonal Signals With Time-Varying Pitches — Bernd Edler, Ning Guo · IEEE Signal Processing Letters (2024) | TGRS Research Map | TGRS