Using Contextual Information in View of Formant Speech Analysis Improvement

Abstract

Parallel formant synthesis of speech is a well known technique used in building performant synthesis systems. The fact that the synthesizer parameters can be closely controlled permits to obtain very high quality synthetic speech. However, the extraction of the parameters is not an easy task, usually semi-automatic methods are used for this purpose.

Our aim is to extract these parameters as automatically as possible. Hence, we use suitable signal processing procedures, together with a-priori and context knowledge on speech in order to guide the analysis and correct eventual errors where the automatic procedures are unable to give the correct results. The fact that we already have a whole French diphone dictionary, analysed by an operator-controlled semiautomatic method will help us to gather the necessary a-priori knowledge of speech analysis. This analysis parameters are smoothed for all the diphones and then they are stored in a data-base form, we can then study the parameters’ behavior and integrate them in the analysis system, the long term object being synthesis by rule.