A novel text to speech technique for tamil language using hidden Markov models (HMM)

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Abstract

Application of digital signal processing in speech processing plays a major part in our everyday life. Text to speech system lets people to see and read out loud consecutively. Text-to-speech synthesizers use synthesis techniques that require good quality speech. Text to speech conversion (TTS) can apply to many applications such as automation, audio recording and audio-based assistance system. Text to speech conversion can be applied for various multinational language as well as for a number of local languages. An efficient text to speech conversion for Tamil language with extreme accuracy is proposed in this work. Multi feature, with a Hidden Markov Model (HMM) predictor is used to convert text to speech efficiently. By using the proposed method, the precision of the framework is enhanced by a factor of 6% when contrasted with the traditional system.

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Femina Jalin, A., & Jaya Kumari, J. (2019). A novel text to speech technique for tamil language using hidden Markov models (HMM). International Journal of Innovative Technology and Exploring Engineering, 8(10), 38–47. https://doi.org/10.35940/ijitee.I8589.0881019

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