Voice metamorphosis retrieval-based

Abstract

Voice conversion is a sophisticated process that elegantly transposes the unique identity of one speaker onto another while meticulously preserving the original speech content. This transformative process relies on intricate algorithms that seamlessly integrate various speech processing techniques, including speech analysis, speaker classification, and vocoding, with deep neural networks at the forefront, adeptly disentangling a speaker’s vocal characteristics from their linguistic content. This study delves into the intricacies of Retrieval-Based Voice Conversion, comprehending its core concepts, demonstrating practical application, and conducting a preliminary perceptual evaluation, relying on neural networks, data embeddings, and voice characteristics to authentically transform voices. Central objectives involve acquiring a solid understanding of foundational principles underpinning retrieval-based techniques, showcasing practical applications through illustrative examples, and highlighting the potential of retrieval-based methods in real-world voice metamorphosis scenarios. To assess the perceptual impact, a limited-scale perceptual evaluation is conducted with human participants, collecting subjective opinions on the quality and authenticity of voices converted using retrievalbased methods. This exploration of ’Voice Metamorphosis: Retrieval-Based Voice Conversion’ offers insights into methodologies, experimental revelations, and the exciting potential to reshape voices in ways that transcend the ordinary.