HMM-Based Distributed Text-to-Speech Synthesis Incorporating Speaker-Adaptive Training

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Provided by: Science & Engineering Research Support soCiety (SERSC)
Topic: Enterprise Software
Format: PDF
In this paper, a Hidden Markov Model (HMM) based distributed Text-To-Speech (TTS) system is proposed to synthesize the voices of various speakers in a client-server framework. The proposed system is based on speaker-adaptive training for constructing HMMs corresponding to a target speaker, and its computational complexity is balanced by distributing the processing modules of the TTS system at both the client and server to achieve a real-time operation. In other words, fewer complex operations, such as text inputs and HMM-based speech synthesis, are conducted by the client, while speaker-adaptive training, which is a very complex operation, is assigned to the server.
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