Investigation of effects caused by catastrophic forgetting in continual learning of end-to-end text-to-speech synthesis
Google slides: https://docs.google.com/presentation/d/1dj2eudW3MH1gh_M6ML0oPN8wHLGTtkSLJjCuboROfNY/edit?usp=sharing
Speech samples:
http://sarulab.sakura.ne.jp/ysaito/demo_continual.html
Investigation of effects caused by catastrophic forgetting in continual learning of end-to-end text-to-speech synthesis
Google slides: https://docs.google.com/presentation/d/1dj2eudW3MH1gh_M6ML0oPN8wHLGTtkSLJjCuboROfNY/edit?usp=sharing
Speech samples:
http://sarulab.sakura.ne.jp/ysaito/demo_continual.html
ICASSP 2019音声&音響論文読み会(https://connpass.com/event/128527/)での発表資料です。
AASP (Audio and Acoustic Signal Processing) 分野の紹介と、ICASSP 2019での動向を紹介しています。#icassp2019jp
音源分離における音響モデリング(Acoustic modeling in audio source separation)Daichi Kitamura
北村大地, "音源分離における音響モデリング," 日本音響学会 サマーセミナー 招待講演, September 11th, 2017.
Daichi Kitamura, "Acoustic modeling in audio source separation," The Acoustical Society of Japan, Summer Seminar Invited Talk, September 11th, 2017.
ICASSP 2019音声&音響論文読み会(https://connpass.com/event/128527/)での発表資料です。
AASP (Audio and Acoustic Signal Processing) 分野の紹介と、ICASSP 2019での動向を紹介しています。#icassp2019jp
音源分離における音響モデリング(Acoustic modeling in audio source separation)Daichi Kitamura
北村大地, "音源分離における音響モデリング," 日本音響学会 サマーセミナー 招待講演, September 11th, 2017.
Daichi Kitamura, "Acoustic modeling in audio source separation," The Acoustical Society of Japan, Summer Seminar Invited Talk, September 11th, 2017.
The document describes a real-time DNN voice conversion system with feedback to acquire character traits. It proposes a method to provide real-time feedback of the converted voice to the speaker to encourage speech modification (prosody and emphasis) towards the target speaker's character. Subjective evaluations from the first-person (user) perspective and third-person perspective found that the system improved the reproduction of the target speaker's character, especially for inexperienced users. Providing only pitch feedback was already quite effective.
1. Department of Computer Science and Electronic Engineering, National Institute of Technology, Tokuyama College
雑音環境下音声を用いたDNN音声合成の
ための雑音生成モデルの敵対的学習
宇根昌和(徳山高専,東大),
齋藤佑樹,高道慎之介,北村大地(東大)
宮崎亮一(徳山高専),猿渡洋(東大)