16 citations · 27 across the 21 of their papers we have counts for
10 papers · 1 filter
PhiNet: Speaker Verification with Phonetic Interpretability
Yi Ma, Shuai Wang, Tianchi Liu +1
Despite remarkable progress, automatic speaker verification (ASV) systems typically lack the transparency required for high-accountability applications. Motivated by how human expe…
Controllable Accent Normalization via Discrete Diffusion
Qibing Bai, Yuhan Du, Tom Ko +3
Existing accent normalization methods do not typically offer control over accent strength, yet many applications-such as language learning and dubbing-require tunable accent retent…
G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition
Jing Peng, Ziyi Chen, Haoyu Li +7
We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting, chunk-wise inference must preserve me…
CosyAccent: Duration-Controllable Accent Normalization Using Source-Synthesis Training Data
Qibing Bai, Shuhao Shi, Shuai Wang +3
Accent normalization (AN) systems often struggle with unnatural outputs and undesired content distortion, stemming from both suboptimal training data and rigid duration modeling. I…
Direct Preference Optimization for Speech Autoregressive Diffusion Models
Zhijun Liu, Dongya Jia, Xiaoqiang Wang +4
Autoregressive diffusion models (ARDMs) have recently been applied to speech generation, achieving state-of-the-art (SOTA) performance in zero-shot text-to-speech. By autoregressiv…
Accent Normalization Using Self-Supervised Discrete Tokens with Non-Parallel Data
Qibing Bai, Sho Inoue, Shuai Wang +3
Accent normalization converts foreign-accented speech into native-like speech while preserving speaker identity. We propose a novel pipeline using self-supervised discrete tokens a…
SpeechRefiner: Towards Perceptual Quality Refinement for Front-End Algorithms
Sirui Li, Shuai Wang, Zhijun Liu +3
Speech pre-processing techniques such as denoising, de-reverberation, and separation, are commonly employed as front-ends for various downstream speech processing tasks. However, t…
M-Vec: Matryoshka Speaker Embeddings with Flexible Dimensions
Shuai Wang, Pengcheng Zhu, Haizhou Li
Fixed-dimensional speaker embeddings have become the dominant approach in speaker modeling, typically spanning hundreds to thousands of dimensions. These dimensions are hyperparame…
E1 TTS: Simple and Fast Non-Autoregressive TTS
Zhijun Liu, Shuai Wang, Pengcheng Zhu +2
This paper introduces Easy One-Step Text-to-Speech (E1 TTS), an efficient non-autoregressive zero-shot text-to-speech system based on denoising diffusion pretraining and distributi…
Autoregressive Diffusion Transformer for Text-to-Speech Synthesis
Zhijun Liu, Shuai Wang, Sho Inoue +2
Audio language models have recently emerged as a promising approach for various audio generation tasks, relying on audio tokenizers to encode waveforms into sequences of discrete s…