Implementing a Text-to-Speech synthesis model on a Raspberry Pi for Industrial Applications

Mandeel, Ali Raheem and Aggar, Ammar Abdullah and Al-Radhi, Mohammed Salah and Csapó, Tamás Gábor (2023) Implementing a Text-to-Speech synthesis model on a Raspberry Pi for Industrial Applications. In: Proceedings of the 1st Workshop on Intelligent Infocommunication Networks, Systems and Services (WI2NS2). Budapesti Műszaki és Gazdaságtudományi Egyetem, Villamosmérnöki és Informatikai Kar, Budapest, pp. 77-81. ISBN 9789634219026

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Abstract

Text-to-Speech (TTS) technology produces human-like speech from input text. It has recently acquired prominence by applying deep neural networks. Nowadays, endto-end TTS models produce highly natural synthesized speech but require extremely high computational resources. Deploying such high-quality TTS models in a real-time environment has been a challenging problem due to the limited resources of embedding systems and cell phones. This paper demonstrated the implementation of an end-to-end TTS model (FastSpeech 2) in an embedded device (Raspberry Pi4 B+). The objective experimental results showed that the TTS model is compatible with the Raspberry Pi (RPi) with high-quality synthesized speech and acceptable performance in terms of processing speed. Our proposed model could be used in many real-life applications if used together with a mechanism for caching, such as railway announcements and industrial purposes.

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