no code implementations • 8 Jun 2023 • Zhiyi Wang, Shaoguang Mao, Wenshan Wu, Yan Xia, Yan Deng, Jonathan Tien
To leverage NLP models, speech input is first force-aligned with texts, and then pre-processed into a token sequence, including words and phrase break information.
1 code implementation • 17 May 2023 • Chenshuo Wang, Shaoguang Mao, Tao Ge, Wenshan Wu, Xun Wang, Yan Xia, Jonathan Tien, Dongyan Zhao
The training dataset comprises over 3. 7 million sentences and 12. 7 million suggestions generated through rules.
2 code implementations • 17 Apr 2023 • Yuzhe Cai, Shaoguang Mao, Wenshan Wu, Zehua Wang, Yaobo Liang, Tao Ge, Chenfei Wu, Wang You, Ting Song, Yan Xia, Jonathan Tien, Nan Duan, Furu Wei
By introducing this framework, we aim to bridge the gap between humans and LLMs, enabling more effective and efficient utilization of LLMs for complex tasks.
no code implementations • 14 Oct 2021 • Wenxuan Ye, Shaoguang Mao, Frank Soong, Wenshan Wu, Yan Xia, Jonathan Tien, Zhiyong Wu
These embeddings, when used as implicit phonetic supplementary information, can alleviate the data shortage of explicit phoneme annotations.
no code implementations • 26 Oct 2020 • Bin Su, Shaoguang Mao, Frank Soong, Yan Xia, Jonathan Tien, Zhiyong Wu
Traditional speech pronunciation assessment, based on the Goodness of Pronunciation (GOP) algorithm, has some weakness in assessing a speech utterance: 1) Phoneme GOP scores cannot be easily translated into a sentence score with a simple average for effective assessment; 2) The rank ordering information has not been well exploited in GOP scoring for delivering a robust assessment and correlate well with a human rater's evaluations.