| 研究実績の概要 |
In FY2020, I focus on accent speech recognition (English and Chinese), cross-language family speech recognition. Multilingual speech recognition technologies have also been applied to language identification, speaker recognition, disordered speech recognition, and more complex tasks, such as speech translation and adversarial attack.Achievements are as follows:
1. This year's investigation of multilingual modeling technology has been applied to speaker modeling (1 domestic presentation: IEICE-SP)， low-resource transfer learning (1 Interspeech SLIMT2020), and speech translation (NLP2021 presentation), language identification (1 journal paper of IEEE-TASLP), and disordered speech recognition (1 Interspeech2020 with grant honor, 1 O-COCOSDA).
2. I also find the acoustic modeling unit selection technology can enhance single-language speech recognition with multi-unit (1 invited full paper on 1 Interspeech SLIMT2020, 1 ICASSP2021) and code-switched speech synthesis (1 Interspeech SLIMT2020, 1 ICONIP paper).
3. Following researches also benefit with the multilingual modeling technologies: speech separation (1 Interspeech2020 with grant honor), adversarial attack (1 IEEE-SLT demo paper), voice-privacy (1 invited report on Interspeech SLIMT2020, 1 Interspeech challenge, 1 ACM-CCS demo), voice activity detection (1 ICASSP2021), Mandarin tone modeling (1 ICASSP2021)
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