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HQSTS

High-Quality voice model for STatistical parametric speech Synthesis

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EC-Contrib. €

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Project "HQSTS" data sheet

The following table provides information about the project.

Coordinator
THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE 

Organization address
address: TRINITY LANE THE OLD SCHOOLS
city: CAMBRIDGE
postcode: CB2 1TN
website: www.cam.ac.uk

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Project website http://gillesdegottex.eu/Demos/HQSTS/
 Total cost 183˙454 €
 EC max contribution 183˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2014
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2015
 Duration (year-month-day) from 2015-10-01   to  2017-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    THE CHANCELLOR MASTERS AND SCHOLARSOF THE UNIVERSITY OF CAMBRIDGE UK (CAMBRIDGE) coordinator 183˙454.00

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 Project objective

A speech analysis/synthesis method aims at representing a speech waveform, produced by a person speaking, as a time sequence of parameters. Based on this time sequence, the speech waveform can be resynthesized. The analysis/synthesis methods are cornerstones for many speech technologies (e.g. text-to-speech, telecommunications, voice restoration). For the majority of applications, these methods need to have two key properties: (i) a high perceived quality of the speech sound, and, (ii) a statistical characterization of the parameters' sequence necessary for statistical approaches, which have attracted great interest during the last decades in speech technologies. The current analysis/synthesis methods that provide a statistical characterization exhibit however a lack of perceived quality. This issue does not pose a problem in applications designed for noisy environments (e.g. navigation devices, smart-phone applications, announcements in train stations). On the contrary, it prohibits the use of statistical approaches in quiet environments, e.g. in the music, cinema and video game industries, where the listener is fully aware of all the details of the sound. This problem is mainly due to the lack of an accurate representation of the phase information and its correlation with the amplitude information. Indeed, recent phase processing tools allowed the description of the phase spectrum properties in a way that shows the drawbacks and limits of current analysis/synthesis methods. Additionally, these same tools are also promising means for modeling the phase information, which is paramount for good quality. The primary goal of the HQSTS project is to create a high-quality analysis/synthesis method that will broaden the applications of statistical approaches of speech technologies in quiet environments, where a high-quality is an absolute necessity.

 Publications

year authors and title journal last update
List of publications.
2018 Gilles Degottex, Pierre Lanchantin, Mark Gales
A Log Domain Pulse Model for Parametric Speech Synthesis
published pages: 57-70, ISSN: 2329-9290, DOI: 10.1109/TASLP.2017.2761546
IEEE/ACM Transactions on Audio, Speech, and Language Processing 26/1 2019-06-17
2017 Gilles Degottex Pierre Lanchantin Mark Gales
Light Supervised Data Selection, Voice Quality Normalized Training and Log Domain Pulse Synthesis
published pages: , ISSN: , DOI:
Proc. Blizzard Challenge 2017 2019-06-17
2017 Moquan Wan Gilles Degottex Mark Gales
Integrated speaker-adaptive speech synthesis
published pages: , ISSN: , DOI:
Proc. IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU) 2019-06-17
2016 Gilles Degottex Pierre Lanchantin Mark Gales
A Pulse Model in Log-domain for a Uniform Synthesizer
published pages: , ISSN: , DOI:
Proc. 9th Speech Synthesis Workshop (SSW9) 2019-06-17

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