Abstract
Speech synthesis is the technique of artificially generating human speech. A text-to-speech system converts ordinary (raw) text of any language for which it is designed into speech signal. In this era, people are more interested to listen their native language. So, there is need for text-to-speech system (TTS) that will give automatic transformation of raw text into speech that looks like a native speaker of the language reading the raw text. So far, successful research has not been done in generating a speech signal. We have been only able to extract parameters from recorded speech and synthesize the original signal from it. Hence, the speech synthesis term is more appropriate than speech generation. Synthesized speech is generated by many concatenation algorithms. The goal of this paper is to give concise idea about different engineering approaches for talking machines that use sequence of word units that provides flexibility for arbitrary vocabularies as required in many application such as ultimate conversion from written text-to-speech signal.
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Gujarathi, P., Patil, S.R. (2021). Review on Unit Selection-Based Concatenation Approach in Text to Speech Synthesis System. In: Gunjan, V.K., Suganthan, P.N., Haase, J., Kumar, A. (eds) Cybernetics, Cognition and Machine Learning Applications. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-33-6691-6_22
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DOI: https://doi.org/10.1007/978-981-33-6691-6_22
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