works on

From the 1 of 10 linked papers with an AI index.

collaborators

10 papers

eess.AS2026

On-Policy Self-Distillation for Multi-Dialect ASR: Mastering Dialects, Retaining Mandarin

Shuiyuan Wang, Bingshen Mu, Pengshen Zhang +6

Recent large-scale ASR models already achieve strong Mandarin recognition accuracy and have some ability to recognize Chinese dialects. However, their dialect recognition accuracy…

eess.AS2026

SLT 2026 REAL-TSE Challenge: Real-world Target Speaker Extraction from Conversational Recordings

Shuai Wang, Zihan Qian, Ke Zhang +9

The paper presents the REAL‑TSE Challenge, a benchmark for extracting a target speaker’s voice from real conversational recordings in Mandarin and English, with both online low‑lat…

eess.AS2026

GigaSpeechBench: A Real-World Multilingual Speech-to-Text Benchmark

Yujie Tu, Yifan Yang, Tianrui Wang +36

While modern ASR systems achieve low error rates on high-resource benchmarks, such performance often overestimates real-world robustness. Existing evaluations address challenges in…

eess.AS2026

Full-Duplex Interaction in Spoken Dialogue Systems: A Comprehensive Study from the ICASSP 2026 HumDial Challenge

Chengyou Wang, Hongfei Xue, Guojian Li +6

Full-duplex interaction, where speakers and listeners converse simultaneously, is a key element of human communication often missing from traditional spoken dialogue systems. These…

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.SD2026

WenetSpeech-Wu: Datasets, Benchmarks, and Models for a Unified Chinese Wu Dialect Speech Processing Ecosystem

Chengyou Wang, Mingchen Shao, Jingbin Hu +11

Speech processing for low-resource dialects remains a fundamental challenge in developing inclusive and robust speech technologies. Despite its linguistic significance and large sp…