PPSpeech: Phrase based Parallel End-to-End TTS System

by   Yahuan Cong, et al.

Current end-to-end autoregressive TTS systems (e.g. Tacotron 2) have outperformed traditional parallel approaches on the quality of synthesized speech. However, they introduce new problems at the same time. Due to the autoregressive nature, the time cost of inference has to be proportional to the length of text, which pose a great challenge for online serving. On the other hand, the style of synthetic speech becomes unstable and may change obviously among sentences. In this paper, we propose a Phrase based Parallel End-to-End TTS System (PPSpeech) to address these issues. PPSpeech uses autoregression approach within a phrase and executes parallel strategies for different phrases. By this method, we can achieve both high quality and high efficiency. In addition, we propose acoustic embedding and text context embedding as the conditions of encoder to keep successive and prevent from abrupt style or timbre change. Experiments show that, the synthesis speed of PPSpeech is much faster than sentence level autoregressive Tacotron 2 when a sentence has more than 5 phrases. The speed advantage increases with the growth of sentence length. Subjective experiments show that the proposed system with acoustic embedding and context embedding as conditions can make the style transition across sentences gradient and natural, defeating Global Style Token (GST) obviously in MOS.


page 2

page 3

page 4


FPUAS : Fully Parallel UFANS-based End-to-End Acoustic System with 10x Speed Up

A lightweight end-to-end acoustic system is crucial in the deployment of...

Speaking Speed Control of End-to-End Speech Synthesis using Sentence-Level Conditioning

This paper proposes a controllable end-to-end text-to-speech (TTS) syste...

Towards Expressive Speaking Style Modelling with Hierarchical Context Information for Mandarin Speech Synthesis

Previous works on expressive speech synthesis mainly focus on current se...

An investigation of speaker independent phrase break models in End-to-End TTS systems

This paper presents our work on phrase break prediction in the context o...

Exploiting Syntactic Features in a Parsed Tree to Improve End-to-End TTS

The end-to-end TTS, which can predict speech directly from a given seque...

High Quality Streaming Speech Synthesis with Low, Sentence-Length-Independent Latency

This paper presents an end-to-end text-to-speech system with low latency...

Towards Controlled Transformation of Sentiment in Sentences

An obstacle to the development of many natural language processing produ...

Please sign up or login with your details

Forgot password? Click here to reset