ReverBERT: A State Space Model for Efficient Text-Driven Speech Style Transfer

• URL: http://arxiv.org/abs/2503.20992v1
• Date: Wed, 26 Mar 2025 21:11:17 GMT
• Title: ReverBERT: A State Space Model for Efficient Text-Driven Speech Style Transfer
• Authors: Michael Brown, Sofia Martinez, Priya Singh,
• Abstract summary: We present emphReverBERT, an efficient framework for text-driven speech style transfer.<n>Unlike image domain techniques, our method operates in the speech space and integrates a discrete Fourier transform of latent speech features.<n>Experiments on benchmark speech corpora demonstrate that emphReverBERT significantly outperforms baselines in terms of naturalness, expressiveness, and computational efficiency.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Text-driven speech style transfer aims to mold the intonation, pace, and timbre of a spoken utterance to match stylistic cues from text descriptions. While existing methods leverage large-scale neural architectures or pre-trained language models, the computational costs often remain high. In this paper, we present \emph{ReverBERT}, an efficient framework for text-driven speech style transfer that draws inspiration from a state space model (SSM) paradigm, loosely motivated by the image-based method of Wang and Liu~\cite{wang2024stylemamba}. Unlike image domain techniques, our method operates in the speech space and integrates a discrete Fourier transform of latent speech features to enable smooth and continuous style modulation. We also propose a novel \emph{Transformer-based SSM} layer for bridging textual style descriptors with acoustic attributes, dramatically reducing inference time while preserving high-quality speech characteristics. Extensive experiments on benchmark speech corpora demonstrate that \emph{ReverBERT} significantly outperforms baselines in terms of naturalness, expressiveness, and computational efficiency. We release our model and code publicly to foster further research in text-driven speech style transfer.

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