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AI in Speech Synthesis: Techniques, Applications, and Future Trends
Abstract
Artificial Intelligence (AI) has significantly advanced the field of speech synthesis, transforming it from robotic and monotone outputs to highly realistic, natural-sounding speech. This article explores the evolution of AI in speech synthesis, detailing the shift from traditional concatenative and formant synthesis methods to state-of-the-art AI-driven approaches like WaveNet, Tacotron, and FastSpeech. These innovations have enhanced naturalness, contextual awareness, and scalability, enabling applications across virtual assistants, entertainment, education, and accessibility tools. The article also discusses emerging challenges, such as data scarcity, ethical concerns regarding voice cloning, and the complexities of prosody and emotional adaptation. Finally, it highlights future directions, focusing on multilingual and emotionally adaptive models that prioritize ethical development and safeguard against misuse, offering a roadmap for the future of AI-driven human-machine communication.
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