collaborators
Showing eess.ASShow all

6 papers · 1 filter

eess.AS2026

The SLT 2026 SmartGlasses Challenge: Benchmarking Egocentric Multi-Talker Speech Recognition and Understanding with Audio-Language Models

Dehui Gao, Zhixian Zhao, Zhennan Lin +14

Recent advances in large language models (LLMs) and multimodal LLMs (MLLMs) have created new opportunities for wearable speech interfaces, with smart glasses providing an egocentri…

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

Towards Fine-Grained Multi-Dimensional Speech Understanding: Data Pipeline, Benchmark, and Model

Guojian Li, Zhixian Zhao, Zhennan Lin +9

While speech Large Language Models (LLMs) excel at conventional tasks like basic speech recognition, they lack fine-grained, multi-dimensional perception. This deficiency is eviden…

eess.AS2025

DiffRhythm 2: Efficient and High Fidelity Song Generation via Block Flow Matching

Yuepeng Jiang, Huakang Chen, Ziqian Ning +7

Generating full-length, high-quality songs is challenging, as it requires maintaining long-term coherence both across text and music modalities and within the music modality itself…

eess.AS2025

EchoFree: Towards Ultra Lightweight and Efficient Neural Acoustic Echo Cancellation

Xingchen Li, Boyi Kang, Ziqian Wang +4

In recent years, neural networks (NNs) have been widely applied in acoustic echo cancellation (AEC). However, existing approaches struggle to meet real-world low-latency and comput…

eess.AS2025

REF-VC: Robust, Expressive and Fast Zero-Shot Voice Conversion with Diffusion Transformers

Yuepeng Jiang, Ziqian Ning, Shuai Wang +5

In real-world voice conversion applications, environmental noise in source speech and user demands for expressive output pose critical challenges. Traditional ASR-based methods ens…