Text-to-Speech (TTS) technology transforms written text into spoken audio. This process involves several key stages:
Text Normalization: Cleans and standardizes input text, expanding abbreviations, converting numbers to words, and resolving homographs.
Phonetic Transcription: Converts normalized text into phonemes (basic sound units) using grapheme-to-phoneme conversion, often employing machine learning.
Prosody Generation: Determines speech rhythm, stress, and intonation, influencing the emotional tone and naturalness of the output. Statistical models trained on human speech are common here.
Waveform Synthesis: Generates the final audio waveform. Methods include:
Machine learning, especially deep learning, is central to modern TTS, enabling models to learn from vast datasets and produce increasingly human-like voices.
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