activity
20242026
collaborators

10 papers

eess.AS2026

MSVAE: Rethinking Musical Semantics in Continuous Latent Spaces

Guobin Ma, Yuepeng Jiang, Dake Guo +15

Continuous latent representations underlie recent diffusion-based lyrics-to-song and text-to-music systems, yet aligning lyric conditions with these latents remains difficult: exis…

eess.AS2026

StreamTN: A Low-Latency Streaming Chinese Text Normalization Model for Streaming TTS in Dialogue Systems

Wenhao Li, Jinrui Liang, Haoyu Zhang +11

Text-to-Speech (TTS) is an essential module that provides spoken responses in a spoken dialogue system (SDS) centered on a large language model (LLM). To ensure accurate TTS synthe…

eess.AS2026

Rethinking Music Tokenization: A Semantic Codec toward High-Fidelity LLM Music Generation

Huakang Chen, Guobin Ma, Yuepeng Jiang +10

Discrete audio tokenization has become the critical interface between raw waveforms and autoregressive modeling in recent music generation. As a result, music tokenizers must simul…

eess.AS2026

SphereVAE: Hyperspherical Latent Autoencoders for Robust Autoregressive Speech Representation Modeling

Haoyu Zhang, Jingbin Hu, Hanke Xie +8

With the rapid development of speech generation technology, discrete codec representations have been widely used because they provide a stable prediction paradigm. In expressive sp…

eess.AS2026

SemBridge: Semantic Token Anchoring for Continuous-Latent Autoregressive Speech Generation

Hanke Xie, Haopeng Lin, Jiale Qian +13

Continuous-latent autoregressive speech generation has emerged as a promising alternative to discrete-token modeling by avoiding quantization loss and preserving richer acoustic in…

eess.AS2026

FlashTTS: Fast Streaming TTS with MTP Acceleration and X-pred Mean Flow Distillation

Hanke Xie, Xiaming Ren, Dake Guo +10

Recent progress in speech dialogue systems requires Text-to-Speech (TTS) models to be faster and more responsive. Modern speech dialogue systems impose two primary requirements on…

eess.AS2026

MINT-Bench: A Comprehensive Multilingual Benchmark for Instruction-Following Text-to-Speech

Huakang Chen, Jingbin Hu, Liumeng Xue +12

Instruction-following text-to-speech (TTS) has emerged as an important capability for controllable and expressive speech generation, yet its evaluation remains underdeveloped due t…

eess.AS2026

VoiceSculptor: Your Voice, Designed By You

Jingbin Hu, Huakang Chen, Linhan Ma +19

Despite rapid progress in text-to-speech (TTS), open-source systems still lack truly instruction-following, fine-grained control over core speech attributes (e.g., pitch, speaking…

cs.AI2025

HiStyle: Hierarchical Style Embedding Predictor for Text-Prompt-Guided Controllable Speech Synthesis

Ziyu Zhang, Hanzhao Li, Jingbin Hu +2

Controllable speech synthesis refers to the precise control of speaking style by manipulating specific prosodic and paralinguistic attributes, such as gender, volume, speech rate,…

eess.AS2024

KALL-E:Autoregressive Speech Synthesis with Next-Distribution Prediction

Kangxiang Xia, Xinfa Zhu, Jixun Yao +3

We introduce KALL-E, a novel autoregressive (AR) language model for text-to-speech (TTS) synthesis that operates by predicting the next distribution of continuous speech frames. Un…