Grapheme Based Tigrinya Speech Synthesis Using Statistical Parametric Speech Synthesis
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Scientific Study from the year 2017 in the subject Speech Science / Linguistics, grade: very good, , course: Computer Science, language: English, abstract: In this study a model-based speech synthesis prototype for Tigrinya spoken language idiom is developed in an integrated speech synthesis framework (Festival speech synthesis system). While the frontend of the framework is Graphemebased synthesizer, the backend is CLUSTERGEN Synthesizer which is an instance of statistical parametric speech synthesis. The under resourced linguistic nature of the language was the main reason to choose this fra...
Scientific Study from the year 2017 in the subject Speech Science / Linguistics, grade: very good, , course: Computer Science, language: English, abstract: In this study a model-based speech synthesis prototype for Tigrinya spoken language idiom is developed in an integrated speech synthesis framework (Festival speech synthesis system). While the frontend of the framework is Graphemebased synthesizer, the backend is CLUSTERGEN Synthesizer which is an instance of statistical parametric speech synthesis. The under resourced linguistic nature of the language was the main reason to choose this framework. 249 Tigrinya graphemes were considered as phonemes independently; irrespective of its 32 phonological phonemes. For this study, 800 previously prepared sentences and rerecorded again in a recommended way is used as corpus. Amendments and additions to the adopted methodology was done. The whole prototype synthesis development was done automatically. A tenfold threshold method was usedfor training and testing of the prototype. The synthesized speech was android deployable prototype. This synthesized speech resulted a score of 5.82 using Mel Cepstral Distortion ( which is built-in objective measurement metric); while subjective evaluation resulted 4.5 and 4.3 out of 5 score, naturalness and intelligibility of the synthesized speech respectively. Both evaluations were interpreted as the synthesized speech was almost the same as natural human speech. Finally, future works were indicated.
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