Artificial intelligence (AI) has created a revolution in text-to-speech (TTS) technology. AI algorithms such as machine learning and deep learning allow the synthesis of artificial voices that are closer to real people than ever before.
Previously, TTS systems used rule-based aggregation methods. The machine will combine each individual syllable into words based on grammatical and phonetic rules. However, this method creates an unnatural voice that lacks emotion.
Since AI is applied in TTS, systems can learn from real human voice data to synthesize speech. The algorithm will analyze characteristics such as pitch, duration, and sound intensity and simulate them. Thanks to that, the synthesized sound becomes more natural and richer in emotion.
In addition, AI also helps improve the ability to recognize and analyze the context of text, thereby adjusting intonation and stress appropriately. AI natural language processing techniques such as BERT are also applied to improve TTS quality.
Thanks to the support of AI, large technology companies such as Google, Microsoft, and Amazon continuously release increasingly improved TTS versions, approaching real human voices. This opens up many opportunities to apply TTS in life, from supporting people with disabilities to creating high-quality entertainment products.
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In general, the combination of AI and TTS is an inevitable trend, promising to bring breakthroughs in artificial voice quality in the future. This will contribute to improving human experience when interacting with machines.