Transformers Used in Text-to-Speech Synthesis

Transformers can generate high-quality speech from text using attention-based alignment.

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🤯 Did You Know (click to read)

Transformers in TTS allow for real-time synthesis with prosody control and expressive intonation.

Models like Transformer-TTS use self-attention to learn relationships between input text and output audio features. Positional encodings allow proper sequencing, while attention layers ensure alignment between phonemes and speech frames. This results in natural and intelligible synthesized voices.

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💥 Impact (click to read)

Text-to-speech systems benefit from more expressive, natural-sounding voices and faster training and inference.

Applications include accessibility tools, virtual assistants, and audiobook generation, expanding AI-enabled communication.

Source

Li et al., 2019 - Neural Speech Synthesis with Transformers

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