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cs.CL2024
Error Correction by Paying Attention to Both Acoustic and Confidence References for Automatic Speech Recognition
Yuchun Shu, Bo Hu, Yifeng He +3
Accurately finding the wrong words in the automatic speech recognition (ASR) hypothesis and recovering them well-founded is the goal of speech error correction. In this paper, we p…
cs.CL2024
An Initial Investigation of Language Adaptation for TTS Systems under Low-resource Scenarios
Cheng Gong, Erica Cooper, Xin Wang +9
Self-supervised learning (SSL) representations from massively multilingual models offer a promising solution for low-resource language speech tasks. Despite advancements, language…