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cs.SD2024

MAIN-VC: Lightweight Speech Representation Disentanglement for One-shot Voice Conversion

Pengcheng Li, Jianzong Wang, Xulong Zhang +3

One-shot voice conversion aims to change the timbre of any source speech to match that of the unseen target speaker with only one speech sample. Existing methods face difficulties…

cs.SD2024

RSET: Remapping-based Sorting Method for Emotion Transfer Speech Synthesis

Haoxiang Shi, Jianzong Wang, Xulong Zhang +3

Although current Text-To-Speech (TTS) models are able to generate high-quality speech samples, there are still challenges in developing emotion intensity controllable TTS. Most exi…

cs.SD2024

Learning Expressive Disentangled Speech Representations with Soft Speech Units and Adversarial Style Augmentation

Yimin Deng, Jianzong Wang, Xulong Zhang +2

Voice conversion is the task to transform voice characteristics of source speech while preserving content information. Nowadays, self-supervised representation learning models are…

cs.SD2024

EfficientASR: Speech Recognition Network Compression via Attention Redundancy and Chunk-Level FFN Optimization

Jianzong Wang, Ziqi Liang, Xulong Zhang +2

In recent years, Transformer networks have shown remarkable performance in speech recognition tasks. However, their deployment poses challenges due to high computational and storag…

cs.SD2024

EAD-VC: Enhancing Speech Auto-Disentanglement for Voice Conversion with IFUB Estimator and Joint Text-Guided Consistent Learning

Ziqi Liang, Jianzong Wang, Xulong Zhang +3

Using unsupervised learning to disentangle speech into content, rhythm, pitch, and timbre for voice conversion has become a hot research topic. Existing works generally take into a…

cs.SD2024

CONTUNER: Singing Voice Beautifying with Pitch and Expressiveness Condition

Jianzong Wang, Pengcheng Li, Xulong Zhang +2

Singing voice beautifying is a novel task that has application value in people's daily life, aiming to correct the pitch of the singing voice and improve the expressiveness without…