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New OscillaTTS system enhances expressive speech modeling in diffusion-based TTS

Researchers have developed a new text-to-speech system called OscillaTTS that improves the modeling of sharp prosodic transitions and rapid pitch variations in expressive speech. This system introduces an adaptive oscillatory nonlinearity, which allows for controllable periodic modulation while maintaining signal stability. Experiments on the LJSpeech and Emotional Speech Dataset demonstrated consistent improvements in objective and subjective evaluations, indicating better modeling of expressive prosodic dynamics compared to existing methods that use static nonlinearities like the Snake activation function. AI

IMPACT Enhances expressive speech capabilities in TTS systems, potentially leading to more natural and engaging synthetic voices.

RANK_REASON The cluster contains an academic paper detailing a new model/methodology for TTS.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New OscillaTTS system enhances expressive speech modeling in diffusion-based TTS

COVERAGE [2]

  1. arXiv cs.CL TIER_1 English(EN) · Sandipan Dhar, Nirmesh J. Shah, Ashishkumar P. Gudmalwar, Pankaj Wasnik ·

    Adaptive Oscillatory Inductive Bias for Modeling Sharp Prosodic Dynamics in Diffusion-Based TTS

    arXiv:2606.25424v1 Announce Type: cross Abstract: Diffusion-based text-to-speech (TTS) models have achieved significant improvements in speech quality. However, modeling sharp prosodic transitions and rapid pitch variations in expressive speech remains challenging. Existing diffu…

  2. arXiv cs.AI TIER_1 English(EN) · Pankaj Wasnik ·

    Adaptive Oscillatory Inductive Bias for Modeling Sharp Prosodic Dynamics in Diffusion-Based TTS

    Diffusion-based text-to-speech (TTS) models have achieved significant improvements in speech quality. However, modeling sharp prosodic transitions and rapid pitch variations in expressive speech remains challenging. Existing diffusion-based TTS decoders commonly utilize periodic …