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eess.AS2024
CTC-Assisted LLM-Based Contextual ASR
Guanrou Yang, Ziyang Ma, Zhifu Gao +2
Contextual ASR or hotword customization holds substantial practical value. Despite the impressive performance of current end-to-end (E2E) automatic speech recognition (ASR) systems…
eess.AS2024
Enhancing Low-Resource ASR through Versatile TTS: Bridging the Data Gap
Guanrou Yang, Fan Yu, Ziyang Ma +4
While automatic speech recognition (ASR) systems have achieved remarkable performance with large-scale datasets, their efficacy remains inadequate in low-resource settings, encompa…
eess.AS2024
TacoLM: GaTed Attention Equipped Codec Language Model are Efficient Zero-Shot Text to Speech Synthesizers
Yakun Song, Zhuo Chen, Xiaofei Wang +3
Neural codec language model (LM) has demonstrated strong capability in zero-shot text-to-speech (TTS) synthesis. However, the codec LM often suffers from limitations in inference s…