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cs.CL2024
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…
eess.AS2024★ 2 cited
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…