6 papers · 1 filter
ZipVoice-Dialog: Non-Autoregressive Spoken Dialogue Generation with Flow Matching
Han Zhu, Wei Kang, Liyong Guo +11
Generating spoken dialogue is inherently more complex than monologue text-to-speech (TTS), as it demands both realistic turn-taking and the maintenance of distinct speaker timbres.…
Flow2GAN: Hybrid Flow Matching and GAN with Multi-Resolution Network for Few-step High-Fidelity Audio Generation
Zengwei Yao, Wei Kang, Han Zhu +8
Existing dominant methods for audio generation include Generative Adversarial Networks (GANs) and diffusion-based methods like Flow Matching. GANs suffer from slow convergence duri…
ZipVoice: Fast and High-Quality Zero-Shot Text-to-Speech with Flow Matching
Han Zhu, Wei Kang, Zengwei Yao +6
Existing large-scale zero-shot text-to-speech (TTS) models deliver high speech quality but suffer from slow inference speeds due to massive parameters. To address this issue, this…
k2SSL: A Faster and Better Framework for Self-Supervised Speech Representation Learning
Yifan Yang, Jianheng Zhuo, Zengrui Jin +9
Self-supervised learning (SSL) has achieved great success in speech-related tasks. While Transformer and Conformer architectures have dominated SSL backbones, encoders like Zipform…
CR-CTC: Consistency regularization on CTC for improved speech recognition
Zengwei Yao, Wei Kang, Xiaoyu Yang +7
Connectionist Temporal Classification (CTC) is a widely used method for automatic speech recognition (ASR), renowned for its simplicity and computational efficiency. However, it of…
Zipformer: A faster and better encoder for automatic speech recognition
Zengwei Yao, Liyong Guo, Xiaoyu Yang +6
The Conformer has become the most popular encoder model for automatic speech recognition (ASR). It adds convolution modules to a transformer to learn both local and global dependen…