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Changhao Pan

9 accepted papers

2026

S3Audio: Towards Streaming Synchronized Spatial Audio Generation via Autoregressive Diffusion Transformer

ICML 2026poster

Real-time and accurate spatial audio generation is pivotal for delivering an immersive experience. However, existing spatial audio synthesis technologies are often encumbered by a tradeoff between generation quality and high inference latency, as well as difficulty in capturing precise spatial infor…

Cited by 0SourcecodeScholar
2026

TMD-Bench: A Multi-Level Evaluation Paradigm for Music–Dance Co-Generation

ICML 2026poster

Unified audio--visual generation is rapidly gaining industrial and creative relevance, enabling applications in virtual production and interactive media. However, when moving from general audio--video synthesis to music–dance co-generation, the task becomes substantially harder: musical rhythm, phra…

Cited by 0SourceScholar
2025

MRSAudio: A Large-Scale Multimodal Recorded Spatial Audio Dataset with Refined Annotations

NeurIPS 2025poster

Humans rely on multisensory integration to perceive spatial environments, where auditory cues enable sound source localization in three-dimensional space. Despite the critical role of spatial audio in immersive technologies such as VR/AR, most existing multimodal datasets provide only monaural audi…

Cited by 0SourcecodeScholar
2025

STARS: A Unified Framework for Singing Transcription, Alignment, and Refined Style Annotation

ACL 2025finding

Recent breakthroughs in singing voice synthesis (SVS) have heightened the demand for high-quality annotated datasets, yet manual annotation remains prohibitively labor-intensive and resource-intensive. Existing automatic singing annotation (ASA) methods, however, primarily tackle isolated aspects of…

2025

TCSinger 2: Customizable Multilingual Zero-shot Singing Voice Synthesis

ACL 2025finding

Customizable multilingual zero-shot singing voice synthesis (SVS) has various potential applications in music composition and short video dubbing. However, existing SVS models overly depend on phoneme and note boundary annotations, limiting their robustness in zero-shot scenarios and producing poor…

2025

TechSinger: Technique Controllable Multilingual Singing Voice Synthesis via Flow Matching

AAAI 2025technical

Singing voice synthesis has made remarkable progress in generating natural and high-quality voices. However, existing methods rarely provide precise control over vocal techniques such as intensity, mixed voice, falsetto, bubble, and breathy tones, thus limiting the expressive potential of synthetic…

2025

Versatile Framework for Song Generation with Prompt-based Control

EMNLP 2025

Song generation focuses on producing controllable high-quality songs based on various prompts. However, existing methods struggle to generate vocals and accompaniments with prompt-based control and proper alignment. Additionally, they fall short in supporting various tasks. To address these challeng

2024

GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks

NeurIPS 2024spotlight

The scarcity of high-quality and multi-task singing datasets significantly hinders the development of diverse controllable and personalized singing tasks, as existing singing datasets suffer from low quality, limited diversity of languages and singers, absence of multi-technique information and real…

2024

TCSinger: Zero-Shot Singing Voice Synthesis with Style Transfer and Multi-Level Style Control

EMNLP 2024main

Zero-shot singing voice synthesis (SVS) with style transfer and style control aims to generate high-quality singing voices with unseen timbres and styles (including singing method, emotion, rhythm, technique, and pronunciation) from audio and text prompts. However, the multifaceted nature of singing…