1 citations · 4 across the 21 of their papers we have counts for
23 papers
JoyAI-Talker: Full-Duplex Speech Interactive Large Model Built for Empathetic Voice Agents
Yinhao Bai, Jinming Chen, Yafeng Chen +26
We present JoyAI-Talker, a full-duplex speech dialogue system that delivers robust foundation model capabilities while empowering empathetic interaction and voice agent intelligenc…
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…
HumDial-EIBench: A Human-Recorded Multi-Turn Emotional Intelligence Benchmark for Audio Language Models
Shuiyuan Wang, Zhixian Zhao, Hongfei Xue +5
Evaluating the emotional intelligence (EI) of audio language models (ALMs) is critical. However, existing benchmarks mostly rely on synthesized speech, are limited to single-turn i…
FastTurn: Unifying Acoustic and Streaming Semantic Cues for Low-Latency and Robust Turn Detection
Chengyou Wang, Hongfei Xue, Mingchen Shao +9
Recent advances in AudioLLMs have enabled spoken dialogue systems to move beyond turn-based interaction toward real-time full-duplex communication, where the agent must decide when…
OSUM-Pangu: An Open-Source Multidimension Speech Understanding Foundation Model Built upon OpenPangu on Ascend NPUs
Yujie Liao, Xuelong Geng, Hongfei Xue +2
Recent advancements in Speech Large Language Models have significantly enhanced multi-dimensional speech understanding. However, the majority of high-performance frameworks are pre…
The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Era
Zhixian Zhao, Shuiyuan Wang, Guojian Li +12
Driven by the rapid advancement of Large Language Models (LLMs), particularly Audio-LLMs and Omni-models, spoken dialogue systems have evolved significantly, progressively narrowin…
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…
Easy Turn: Integrating Acoustic and Linguistic Modalities for Robust Turn-Taking in Full-Duplex Spoken Dialogue Systems
Guojian Li, Chengyou Wang, Hongfei Xue +8
Full-duplex interaction is crucial for natural human-machine communication, yet remains challenging as it requires robust turn-taking detection to decide when the system should spe…
WenetSpeech-Chuan: A Large-Scale Sichuanese Corpus with Rich Annotation for Dialectal Speech Processing
Yuhang Dai, Ziyu Zhang, Shuai Wang +13
The scarcity of large-scale, open-source data for dialects severely hinders progress in speech technology, a challenge particularly acute for the widely spoken Sichuanese dialects…
WenetSpeech-Yue: A Large-scale Cantonese Speech Corpus with Multi-dimensional Annotation
Longhao Li, Zhao Guo, Hongjie Chen +15
The development of speech understanding and generation has been significantly accelerated by the availability of large-scale, high-quality speech datasets. Among these, ASR and TTS…
OSUM-EChat: Enhancing End-to-End Empathetic Spoken Chatbot via Understanding-Driven Spoken Dialogue
Xuelong Geng, Qijie Shao, Hongfei Xue +20
Empathy is crucial in enabling natural interactions within spoken dialogue systems, allowing machines to recognize and respond appropriately to paralinguistic cues such as age, gen…
Hearing More with Less: Multi-Modal Retrieval-and-Selection Augmented Conversational LLM-Based ASR
Bingshen Mu, Hexin Liu, Hongfei Xue +2
Automatic Speech Recognition (ASR) aims to convert human speech content into corresponding text. In conversational scenarios, effectively utilizing context can enhance its accuracy…
The TEA-ASLP System for Multilingual Conversational Speech Recognition and Speech Diarization in MLC-SLM 2025 Challenge
Hongfei Xue, Kaixun Huang, Zhikai Zhou +2
This paper presents the TEA-ASLP's system submitted to the MLC-SLM 2025 Challenge, addressing multilingual conversational automatic speech recognition (ASR) in Task I and speech di…
Delayed-KD: Delayed Knowledge Distillation based CTC for Low-Latency Streaming ASR
Longhao Li, Yangze Li, Hongfei Xue +4
CTC-based streaming ASR has gained significant attention in real-world applications but faces two main challenges: accuracy degradation in small chunks and token emission latency.…
Selective Invocation for Multilingual ASR: A Cost-effective Approach Adapting to Speech Recognition Difficulty
Hongfei Xue, Yufeng Tang, Jun Zhang +2
Although multilingual automatic speech recognition (ASR) systems have significantly advanced, enabling a single model to handle multiple languages, inherent linguistic differences…
Enhancing Non-Core Language Instruction-Following in Speech LLMs via Semi-Implicit Cross-Lingual CoT Reasoning
Hongfei Xue, Yufeng Tang, Hexin Liu +3
Large language models have been extended to the speech domain, leading to the development of speech large language models (SLLMs). While existing SLLMs demonstrate strong performan…
Ideal-LLM: Integrating Dual Encoders and Language-Adapted LLM for Multilingual Speech-to-Text
Hongfei Xue, Wei Ren, Xuelong Geng +6
Integrating audio encoders with LLMs through connectors has enabled these models to process and comprehend audio modalities, significantly enhancing speech-to-text tasks, including…
Findings of the 2024 Mandarin Stuttering Event Detection and Automatic Speech Recognition Challenge
Hongfei Xue, Rong Gong, Mingchen Shao +10
The StutteringSpeech Challenge focuses on advancing speech technologies for people who stutter, specifically targeting Stuttering Event Detection (SED) and Automatic Speech Recogni…
AS-70: A Mandarin stuttered speech dataset for automatic speech recognition and stuttering event detection
Rong Gong, Hongfei Xue, Lezhi Wang +11
The rapid advancements in speech technologies over the past two decades have led to human-level performance in tasks like automatic speech recognition (ASR) for fluent speech. Howe…
Unveiling the Potential of LLM-Based ASR on Chinese Open-Source Datasets
Xuelong Geng, Tianyi Xu, Kun Wei +9
Large Language Models (LLMs) have demonstrated unparalleled effectiveness in various NLP tasks, and integrating LLMs with automatic speech recognition (ASR) is becoming a mainstrea…
E-chat: Emotion-sensitive Spoken Dialogue System with Large Language Models
Hongfei Xue, Yuhao Liang, Bingshen Mu +4
This study focuses on emotion-sensitive spoken dialogue in human-machine speech interaction. With the advancement of Large Language Models (LLMs), dialogue systems can handle multi…
BA-MoE: Boundary-Aware Mixture-of-Experts Adapter for Code-Switching Speech Recognition
Peikun Chen, Fan Yu, Yuhao Lian +5
Mixture-of-experts based models, which use language experts to extract language-specific representations effectively, have been well applied in code-switching automatic speech reco…
SSHR: Leveraging Self-supervised Hierarchical Representations for Multilingual Automatic Speech Recognition
Hongfei Xue, Qijie Shao, Kaixun Huang +3
Multilingual automatic speech recognition (ASR) systems have garnered attention for their potential to extend language coverage globally. While self-supervised learning (SSL) model…