Voice conversion techniques typically require source-target parallel speech data for model training. Such parallel data may not be available always in practice.
Figures · 1. Introduction. Voice conversion (VC) aims to modify the one's voice (source). to sound like that of another (target). · 2. Phonetic PosteriorGrams ...
A non-parallel data approach that makes use of a multi-speaker average model that maps speaker-independent linguistic features to speaker dependent acoustic ...
The proposed voice conversion pipeline, DeepConversion, leverages a large amount of non-parallel data, but requires only a small amount of parallel training ...
This paper provides a comprehensive summary and analysis of recent developments in non-parallel voice conversion.Firstly, we outline the early voice conversion ...
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What is non parallel voice conversion?
What is parallel voice conversion?
Average Modeling Approach for Non-Parallel Data Voice Conversion not be available in practice. In previous studies, there were mainly three ways to perform.
Nov 17, 2020 · We propose a novel loss function, cycle consistency loss, to improve the speaker identity conversion for average model voice conversion. PPG ...
Figure 3: Block diagram of feature-based average modeling approach... Average Modeling Approach to Voice Conversion with Non-Parallel Data. Conference Paper.
The proposed approach makes use of a multi-speaker average model that maps speaker independent linguistic features to speaker dependent acoustic features.
In non-parallel data voice conversion with the provided text, a simple method is to produce parallel audios from the text-to-speech model. As shown in Fig ...
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