Journal ArticleDOI
Voice transformation using PSOLA technique
H. Valbret,Eric Moulines,J. P. Tubach +2 more
- Vol. 11, Iss: 2, pp 175-187
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TLDR
A new system for voice conversion is described that combines a PSOLA (Pitch Synchronous Overlap and Add)-derived synthesizer and a module for spectral transformation, which produces a satisfyingly natural “transformed” voice.Abstract:
In this contribution, a new system for voice conversion is described. The proposed architecture combines a PSOLA (Pitch Synchronous Overlap and Add)-derived synthesizer and a module for spectral transformation. The synthesizer based on the classical source-filter decomposition allows prosodic and spectral transformations to be performed independently. Prosodic modifications are applied on the excitation signal using the TD-PSOLA scheme; converted speech is then synthesized using the transformed spectral parameters. Two different approaches to derive spectral transformations, borrowed from the speech-recognition domain, are compared: Linear Multivariate Regression (LMR) and Dynamic Frequency Warping (DFW). Vector-quantization is carried out as a preliminary stage to render the spectral transformations dependent of the acoustical realization of sounds. A formal listening test shows that the synthesizer produces a satisfyingly natural “transformed” voice. LMR proves yet to allow a slightly better conversion than DFW. Still there is room for improvement in the spectral transformation stage.read more
Citations
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Journal ArticleDOI
Voice conversion system using salient sub-bands and radial basis function
TL;DR: A novel approach of voice conversion based on multi-scale wavelet packet transform in the framework of radial basis neural network is presented and it is revealed that the proposed algorithm performs better than the conventional wavelet-based voice morphing.
Voice Conversion Based on Weighted
TL;DR: Compared to standard probabilistic systems, Weighted Frequency Warping results in a significant increase in quality scores, whereas the conversion scores remain almost unaltered.
Proceedings Article
Speech Pitch Shifting using Complex Continuous Wavelet Transform
TL;DR: In this paper, the authors used complex wavelet transform to obtain and manipulate pitch of the signal, which correspond to average pitch value of signal's voiced frame, while the phase matrix corresponding to this scale is altered keeping modulus unchanged.
Book ChapterDOI
Speaker Variability and Specificity
TL;DR: This chapter introduces the variations dues to intra- and inter-speaker variability as well as the ones caused by the environment or the linguistic context and explores the advances made in finding phonetic features relatively insensitive to speech variability and robust to the presence of noise.
Dissertation
A Study on Articulatory Feature-based Phoneme Recognition and Voice Conversion
TL;DR: The behavior of articulatory feature (AF) as linguistic feature representation of the speech waveform in the task of both phoneme recognition (PR) and voice conversion (VC) is studied and VC based on AF to vocal-tract parameters (VTP) mapping is proposed.
References
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Journal ArticleDOI
Pitch-synchronous waveform processing techniques for text-to-speech synthesis using diphones
TL;DR: In a common framework several algorithms that have been proposed recently, in order to improve the voice quality of a text-to-speech synthesis based on acoustical units concatenation based on pitch-synchronous overlap-add approach are reviewed.
Proceedings ArticleDOI
Voice conversion through vector quantization
TL;DR: The authors propose a new voice conversion technique through vector quantization and spectrum mapping which makes it possible to precisely control voice individuality.