3 citations · 6 across the 9 of their papers we have counts for
10 papers
Breaking the Curse of Multilinguality in Many-to-Many Speech-to-Text Translation via a Resource-Aware Mixture of Speech Encoders
Yexing Du, Kaiyuan Liu, Youcheng Pan +4
Multimodal large language models (MLLMs) have achieved significant success in speech-to-text translation (S2TT). However, when processing multilingual speech inputs, a single speec…
Parameter- and Bandwidth-Efficient Edge--cloud Many-to-Many Speech-to-Text Translation
Yexing Du, Kaiyuan Liu, Youcheng Pan +5
Multimodal large language models (MLLMs) have demonstrated significant potential for speech-to-text translation (S2TT). However, existing deployment paradigms face critical challen…
Scalable Multilingual Multimodal Machine Translation with Speech-Text Fusion
Yexing Du, Youcheng Pan, Zekun Wang +7
Multimodal Large Language Models (MLLMs) have achieved notable success in enhancing translation performance by integrating multimodal information. However, existing research primar…
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…
MCGA: A Multi-task Classical Chinese Literary Genre Audio Corpus
Yexing Du, Kaiyuan Liu, Bihe Zhang +9
With the rapid advancement of Multimodal Large Language Models (MLLMs), their potential has gained significant attention in Chinese Classical Studies (CCS). While existing research…
MCAT: Scaling Many-to-Many Speech-to-Text Translation with MLLMs to 70 Languages
Yexing Du, Kaiyuan Liu, Youcheng Pan +7
Multimodal Large Language Models (MLLMs) have achieved great success in Speech-to-Text Translation (S2TT) tasks. However, current research is constrained by two key challenges: lan…
CCFQA: A Benchmark for Cross-Lingual and Cross-Modal Speech and Text Factuality Evaluation
Yexing Du, Kaiyuan Liu, Youcheng Pan +5
As Large Language Models (LLMs) are increasingly popularized in the multilingual world, ensuring hallucination-free factuality becomes markedly crucial. However, existing benchmark…
ProjectEval: A Benchmark for Programming Agents Automated Evaluation on Project-Level Code Generation
Kaiyuan Liu, Youcheng Pan, Yang Xiang +4
Recently, LLM agents have made rapid progress in improving their programming capabilities. However, existing benchmarks lack the ability to automatically evaluate from users' persp…
Making LLMs Better Many-to-Many Speech-to-Text Translators with Curriculum Learning
Yexing Du, Youcheng Pan, Ziyang Ma +7
Multimodal Large Language Models (MLLMs) have achieved significant success in Speech-to-Text Translation (S2TT) tasks. While most existing research has focused on English-centric t…
GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement
Yifan Yang, Zheshu Song, Jianheng Zhuo +13
The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, w…