works on

From the 1 of 8 linked papers with an AI index.

activity
20242026
collaborators

8 papers

cs.AI2026

AgenticASR: Refining Speech Recognition in Real-World Scenarios via an Agentic Approach

Zixuan Jiang, Binghao Qiang, Jiaying Chi +3

The paper introduces AgenticASR, an architecture that continuously refines speech recognition output to remove disfluencies and preserve speaker intent during live audio streams.

eess.AS2026

X-Translator: A Real-Time Multilingual Speaker-Aware Speech-to-Speech Translation System

Yuxiang Zhao, Yichi Zhang, Yanjie An +10

Real-time speech-to-speech translation (S2ST) systems must balance translation quality, latency, speech naturalness, and speaker consistency. Publicly documented S2ST systems have…

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…

cs.AI2026

Towards Human-Like Interactive Speech Recognition With Agentic Correction and Semantic Evaluation

Zixuan Jiang, Yanqiao Zhu, Peng Wang +8

Automatic speech recognition (ASR) is a core component of human--computer interaction and an increasingly important front-end for LLM-based assistants and agents. However, most cur…

cs.CL2026

Interactive ASR: Towards Human-Like Interaction and Semantic Coherence Evaluation for Agentic Speech Recognition

Peng Wang, Yanqiao Zhu, Zixuan Jiang +8

Recent years have witnessed remarkable progress in automatic speech recognition (ASR), driven by advances in model architectures and large-scale training data. However, two importa…

cs.SD2026

SLAM-LLM: A Modular, Open-Source Multimodal Large Language Model Framework and Best Practice for Speech, Language, Audio and Music Processing

Ziyang Ma, Guanrou Yang, Wenxi Chen +19

The recent surge in open-source Multimodal Large Language Models (MLLM) frameworks, such as LLaVA, provides a convenient kickoff for artificial intelligence developers and research…