← Search

Detai Xin

5 accepted papers

2024

NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models

ICML 2024oral

While recent large-scale text-to-speech (TTS) models have achieved significant progress, they still fall shorts in speech quality, similarity, and prosody. Considering that speech intricately encompasses various attributes (e.g., content, prosody, timbre, and acoustic details) that pose significant…

Cited by 172SourcePDFScholar
2023

Duration-Aware Pause Insertion Using Pre-Trained Language Model for Multi-Speaker Text-To-Speech

ICASSP 2023accepted

Pause insertion, also known as phrase break prediction and phrasing, is an essential part of TTS systems because proper pauses with natural duration significantly enhance the rhythm and intelligibility of synthetic speech. However, conventional phrasing models ignore various speakers’ different styl…

Cited by 0SourceScholar
2023

Improving Speech Prosody of Audiobook Text-To-Speech Synthesis with Acoustic and Textual Contexts

ICASSP 2023accepted

We present a multi-speaker Japanese audiobook text-to-speech (TTS) system that leverages multimodal context information of preceding acoustic context and bilateral textual context to improve the prosody of synthetic speech. Previous work either uses unilateral or single-modality context, which does…

Cited by 0SourceScholar
2023

MID-Attribute Speaker Generation Using Optimal-Transport-Based Interpolation of Gaussian Mixture Models

ICASSP 2023accepted

In this paper, we propose a method for intermediating multiple speakers’ attributes and diversifying their voice characteristics in “speaker generation,” an emerging task that aims to synthesize a nonexistent speaker’s naturally sounding voice. The conventional TacoSpawn-based speaker generation met…

Cited by 0SourceScholar
2021

Disentangled Speaker and Language Representations Using Mutual Information Minimization and Domain Adaptation for Cross-Lingual TTS

ICASSP 2021accepted

We propose a method for obtaining disentangled speaker and language representations via mutual information minimization and domain adaptation for cross-lingual text-to-speech (TTS) synthesis. The proposed method extracts speaker and language embeddings from acoustic features by a speaker encoder and…

Cited by 0SourceScholar