PhD Seminar • Natural Language Processing • Alignment-aware Acoustic and Text Pretraining for Speech Synthesis and Editing

Please note: This PhD seminar will take place online.

He (Richard) Bai, PhD candidate
David R. Cheriton School of Computer Science

Supervisor: Professor Ming Li

Recently, speech representation learning has improved many speech-related tasks such as speech recognition, speech classification, and speech-to-text translation. However, all the above tasks are in the direction of speech understanding, but for the inverse direction, speech synthesis, the potential of representation learning is yet to be realized, due to the challenging nature of generating high-quality speech.

To address this problem, we propose our framework, Alignment-Aware Acoustic-Text Pretraining (A3T), which reconstructs masked acoustic signals with text input and acoustic-text alignment during training. In this way, the pretrained model can generate high quality reconstructed spectrogram, which can be applied to the speech editing and unseen speaker TTS directly. Experiments show A3T outperforms SOTA models on speech editing, and improves multi-speaker speech synthesis without the external speaker verification model.

Paper link: https://proceedings.mlr.press/v162/bai22d.html

To join this PhD seminar on Zoom, please go to https://uwaterloo.zoom.us/j/9968684700.