Non-Parallel Whisper-to-Normal Speaking Style Conversion Using Auxiliary Classifier Variational Autoencoder
This paper is concerned with non-parallel whisper-to-normal speaking-style conversion (W2N-SC), which converts whispered speech into normal speech without using parallel training data. Most relevant to this task is voice conversion (VC), which converts one speaker’s voice to another. Howe...
Main Authors: | Shogo Seki, Hirokazu Kameoka, Takuhiro Kaneko, Kou Tanaka |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2023-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10109017/ |
Similar Items
-
Machine Learning Approaches for Whisper to Normal Speech Conversion
by: Marco A. Oliveira
Published: (2022-04-01) -
Streaming ASR Encoder for Whisper-to-Speech Online Voice Conversion
by: Anastasia Avdeeva, et al.
Published: (2024-01-01) -
Perturbation AUTOVC: Voice Conversion From Perturbation and Autoencoder Loss
by: Hwa-Young Park, et al.
Published: (2023-01-01) -
Whisper to Normal Speech Conversion Using Sequence-to-Sequence Mapping Model With Auditory Attention
by: Hailun Lian, et al.
Published: (2019-01-01) -
Whispered Speech Conversion Based on the Inversion of Mel Frequency Cepstral Coefficient Features
by: Qiang Zhu, et al.
Published: (2022-02-01)