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Abstract

In this paper we present work on creating and evaluating a Text-to-Speech system for the Albanian language to be used in the BabelDr medical speech translation system. Its quality was assessed by twelve native speakers who provided feedback on 60 prompts generated by the synthesizer and on 60 real human recordings across three dimensions, namely comprehensibility, naturalness and likeability. The results suggest that the newly created voice can be incorporated in the content creation pipeline of the BabelDr platform.

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... For this reason, we have investigated the option of building our own TTS for those languages from scratch. In a previous study, positive feedback in terms of comprehensibility was (Tsourakis et al., 2020), after building a synthetic female voice for the Albanian language based on Tacotron 2, a neural network architecture for speech synthesis directly from text (Shen et al., 2017). Among the target languages supported by BabelDr, Tigrinya is one for which no public TTS is available. ...
... This allowed us to create a corpus with 18 hours of speech that we exploit in order to create the Tigrinya synthesized voice. The training process is similar to the one found in (Tsourakis et al., 2020). As new content is constantly added to the system, new recordings of the translations are requested. ...
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