Papers

Adversarial Learning of Intermediate Acoustic Feature for End-to-End Lightweight Text-to-Speech

International Conference
2021~
작성자
dsp
작성일
2023-08-11 11:10
조회
779
Authors : Hyungchan Yoon, Seyun Um, Changhwan Kim, Hong-Goo Kang

Year : 2023

Publisher / Conference : INTERSPEECH

Research area : Speech Signal Processing, Text-to-Speech

Presentation : Oral

To simplify the generation process, several text-to-speech (TTS) systems implicitly learn intermediate latent representations instead of relying on predefined features (e.g., mel-spectrogram). However, their generation quality is unsatisfactory as these representations lack speech variances. In this paper, we improve TTS performance by adding prosody embeddings to the latent representations. During training, we extract reference prosody embeddings from mel-spectrograms, and during inference, we estimate these embeddings from text using generative adversarial networks (GANs). Using GANs, we reliably estimate the prosody embeddings in a fast way, which have complex distributions due to the dynamic nature of speech. We also show that the prosody embeddings work as efficient features for learning a robust alignment between text and acoustic features. Our proposed model surpasses several publicly available models with less parameters and computational complexity in comparative experiments.
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