Hierarchical Representation of Prosody for Statistical Speech Synthesis

10/07/2015
by   Antti Suni, et al.
0

Prominences and boundaries are the essential constituents of prosodic structure in speech. They provide for means to chunk the speech stream into linguistically relevant units by providing them with relative saliences and demarcating them within coherent utterance structures. Prominences and boundaries have both been widely used in both basic research on prosody as well as in text-to-speech synthesis. However, there are no representation schemes that would provide for both estimating and modelling them in a unified fashion. Here we present an unsupervised unified account for estimating and representing prosodic prominences and boundaries using a scale-space analysis based on continuous wavelet transform. The methods are evaluated and compared to earlier work using the Boston University Radio News corpus. The results show that the proposed method is comparable with the best published supervised annotation methods.

READ FULL TEXT

page 3

page 7

page 8

research
04/06/2022

Simple and Effective Unsupervised Speech Synthesis

We introduce the first unsupervised speech synthesis system based on a s...
research
08/23/2019

VOP Detection for Read and Conversation Speech using CWT Coefficients and Phone Boundaries

In this paper, we propose a novel approach for accurate detection of the...
research
10/06/2022

Are word boundaries useful for unsupervised language learning?

Word or word-fragment based Language Models (LM) are typically preferred...
research
07/06/2021

Location, Location: Enhancing the Evaluation of Text-to-Speech Synthesis Using the Rapid Prosody Transcription Paradigm

Text-to-Speech synthesis systems are generally evaluated using Mean Opin...
research
07/16/2019

RadioTalk: a large-scale corpus of talk radio transcripts

We introduce RadioTalk, a corpus of speech recognition transcripts sampl...
research
07/04/2021

EditSpeech: A Text Based Speech Editing System Using Partial Inference and Bidirectional Fusion

This paper presents the design, implementation and evaluation of a speec...
research
12/23/2018

Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching

We consider the problem of training speech recognition systems without u...

Please sign up or login with your details

Forgot password? Click here to reset