5 accepted papers
With the rapid advancement of large language models (LLMs), discrete speech representations have become crucial for integrating speech into LLMs. Existing methods for speech representation discretization rely on a predefined codebook size and Euclidean distance-based quantization. However, 1) the si…
Recent advancements in end-to-end text-to-speech models have made significant progress. However, these approaches based on high-resource languages, are inapplicable for low-resource languages, and existing low-resource speech synthesis methods are typically specific to single languages. Consequently…
Voice conversion (VC) aims to transform a person’s voice to resemble that of another person while maintaining the original linguistic content. Existing methods suffer from the blurring of speech representations and the leakage of prosody information. To address this issue, this study introduces SEVC…
End-to-end single-stage text-to-speech models have garnered significant attention in recent research, surpassing the performance of conventional two-stage pipeline systems. While prior single-stage models have made substantial advancements, there remains room for improvement in addressing intermitte…
Existing accent transfer works rely on parallel data or speech recognition models. This paper focuses on the practical application of accent transfer and aims to implement accent transfer using non-parallel datasets. The study has encountered the challenge of speech representation disentanglement an…