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pro vyhledávání: '"Ko, Yuka"'
With the strong representational power of large language models (LLMs), generative error correction (GER) for automatic speech recognition (ASR) aims to provide semantic and phonetic refinements to address ASR errors. This work explores how LLM-based
Externí odkaz:
http://arxiv.org/abs/2408.16180
Autor:
Ko, Yuka, Fukuda, Ryo, Nishikawa, Yuta, Kano, Yasumasa, Yanagita, Tomoya, Doi, Kosuke, Makinae, Mana, Tan, Haotian, Sakai, Makoto, Sakti, Sakriani, Sudoh, Katsuhito, Nakamura, Satoshi
This paper describes NAIST's submission to the simultaneous track of the IWSLT 2024 Evaluation Campaign: English-to-{German, Japanese, Chinese} speech-to-text translation and English-to-Japanese speech-to-speech translation. We develop a multilingual
Externí odkaz:
http://arxiv.org/abs/2407.00826
This paper analyzes the features of monotonic translations, which follow the word order of the source language, in simultaneous interpreting (SI). Word order differences are one of the biggest challenges in SI, especially for language pairs with sign
Externí odkaz:
http://arxiv.org/abs/2406.08940
Simultaneous speech translation (SimulST) translates partial speech inputs incrementally. Although the monotonic correspondence between input and output is preferable for smaller latency, it is not the case for distant language pairs such as English
Externí odkaz:
http://arxiv.org/abs/2306.08582
It remains a question that how simultaneous interpretation (SI) data affects simultaneous machine translation (SiMT). Research has been limited due to the lack of a large-scale training corpus. In this work, we aim to fill in the gap by introducing N
Externí odkaz:
http://arxiv.org/abs/2304.11766
Akademický článek
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