Diffusion Based Waveform Generation With Conditional Synthesis

via “diffusion-based waveform generation with conditional synthesis”

text-to-speech model by undefined. 3,08,930 downloads.

Unique: Uses diffusion-based waveform generation instead of vocoder-based approaches, eliminating the need for separate vocoder models and enabling end-to-end differentiable synthesis. The conditional diffusion architecture allows simultaneous conditioning on linguistic content and speaker identity through cross-attention, producing more coherent speaker-consistent speech than cascade approaches.

vs others: More unified than Tacotron2+Vocoder pipelines (eliminates vocoder mismatch); produces more natural prosody than autoregressive models due to diffusion's global context; more flexible than flow-based models for future prosody control extensions, though slower than both alternatives.

via “diffusion-based audio synthesis and variation”