activity
20242026
collaborators
Showing 2026Show all

10 papers · 1 filter

cs.SD2026

The NVVSpeech Challenge 2026: Overview and Lessons for Speech Understanding and Generation with Nonverbal Vocalizations

Liumeng Xue, Yuang Cao, Jingbin Hu +12

Nonverbal vocalizations (NVVs), such as laughter and sighs, convey meaning alongside words. NVV-aware speech systems must recognize and generate these events while preserving lexic…

cs.CL2026

COT-TTS: Audio Context-Aware Text-to-Speech with Chain-of-Thought Reasoning

Weizhen Bian, Sitong Cheng, Rongxiu Zhong +9

Recently, text-to-speech systems have made significant progress in speech expressiveness and controllability. However, the speaking style of generated speech typically relies on cl…

cs.SD2026

Qwen-Music Technical Report

Jin Xu, Kangdi Wang, Ruibin Yuan +24

We introduce Qwen-Music, a music generation model that produces high-fidelity songs with complete vocals. It supports text-to-music generation from descriptions, lyrics, and musica…

cs.LG2026

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning

Evan Ning, Wei Xue, Dong Lou +1

Weight-space regularization methods such as Elastic Weight Consolidation (EWC) are the standard approach to catastrophic forgetting in continual learning. However, those methods te…

cs.SD2026

STEB: A Speech-to-Speech Translation Expressiveness Benchmark for Evaluating Beyond Translation Fidelity

Sitong Cheng, Weizhen Bian, Songjun Cao +9

Speech-to-speech translation (S2ST) should preserve not only lexical meaning, but also expressive attributes: emotion, scenario style (e.g., news reporting vs. dramatic dialogue),…

eess.AS2026

AudioCALM: Continuous Autoregressive Language Modeling for Universal Audio Generation

Huadai Liu, Kaicheng Luo, Wen Wang +4

Unifying speech, sound, and music generation in one model is hindered by tradeoffs between fidelity, end-to-end training, in-context conditioning, and variable-length synthesis tha…

eess.AS2026

STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation

Huadai Liu, Wen Wang, Kaicheng Luo +3

Continuous Variational Autoencoders (VAEs) serve as the fundamental continuous tokenizer for modern neural audio generation systems, enabling high-fidelity reconstruction while pro…

cs.SD2026

ISCSLP 2026 CoT-TTS Challenge: Chain-of-Thought Reasoning for Context-Aware Text-to-Speech

Wei Xue, Junlan Feng, Shilei Zhang +9

Recent advances in text-to-speech (TTS) have greatly improved speech naturalness, speaker similarity, and controllability. However, most existing controllable TTS systems still rel…

eess.AS2026

Which Speech Representation Better Matches Text-Native Reasoning? A Study of Speech-Text Alignment on Frame Rate and Representation

Zhen Ye, Xu Tan, Yiming Li +10

Spoken dialogue models typically start from text LLM backbones, yet reasoning often degrades when conditioning on speech instead of text. We attribute part of this modality gap to…

cs.CV2026

Talker-T2AV: Joint Talking Audio-Video Generation with Autoregressive Diffusion Modeling

Zhen Ye, Xu Tan, Aoxiong Yin +8

Joint audio-video generation models have shown that unified generation yields stronger cross-modal coherence than cascaded approaches. However, existing models couple modalities th…