Abstract:

Our daily lives are impacted by the use of digital signal processing in speech processing. Many applications, such as automation, audio recording, and audio-based help systems, can benefit from text to speech conversion (TTS). Transcribing TTS is possible for many different languages, including those that are not widely spoken. Text-to-speech (TTS) systems generate spoken equivalents from text input. Though the creation of speech is rather complex, introducing naturalness to the speaker's expression is a major challenge in TTS. This paper proposes an efficient TTS conversion with high accuracy for the Tamil language. The deep learning technique called Deep Quality Speech Recognition (DQSR) is developed in this research study for Tamil language TTS. This is due to the fact that the method used for other languages like English will not work when used in Tamil due to adaptable pronunciations that are fully dependent on the language constructs. When compared to the traditional system, the proposed solution improves the framework's precision by 5%.

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