Transformer Based Mel Spectrogram Generation With Attention Based Alignment

via “real-time mel-spectrogram generation with attention-based alignment”

text-to-speech model by undefined. 17,45,116 downloads.

Unique: Uses learned attention alignment rather than explicit duration prediction models, reducing model complexity and enabling end-to-end training without duration annotations. Attention weights are computed dynamically at inference time, allowing the model to adapt alignment to input length without retraining.

vs others: Simpler than duration-based models (e.g., FastSpeech) because it avoids explicit duration prediction, but potentially less controllable because speech rate and pause length cannot be adjusted per-token at inference time.