AccentBox: Towards High-Fidelity Zero-Shot Accent Generation

• URL: http://arxiv.org/abs/2409.09098v1
• Date: Fri, 13 Sep 2024 06:05:10 GMT
• Title: AccentBox: Towards High-Fidelity Zero-Shot Accent Generation
• Authors: Jinzuomu Zhong, Korin Richmond, Zhiba Su, Siqi Sun,
• Abstract summary: We propose zero-shot accent generation that unifies Foreign Accent Conversion (FAC), accented TTS, and ZS-TTS. In the first stage, we achieve state-of-the-art (SOTA) on Accent Identification (AID) with 0.56 f1 score on unseen speakers. In the second stage, we condition ZS-TTS system on the pretrained speaker-agnostic accent embeddings extracted by the AID model.
• Score: 20.40688498862892
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: While recent Zero-Shot Text-to-Speech (ZS-TTS) models have achieved high naturalness and speaker similarity, they fall short in accent fidelity and control. To address this issue, we propose zero-shot accent generation that unifies Foreign Accent Conversion (FAC), accented TTS, and ZS-TTS, with a novel two-stage pipeline. In the first stage, we achieve state-of-the-art (SOTA) on Accent Identification (AID) with 0.56 f1 score on unseen speakers. In the second stage, we condition ZS-TTS system on the pretrained speaker-agnostic accent embeddings extracted by the AID model. The proposed system achieves higher accent fidelity on inherent/cross accent generation, and enables unseen accent generation.

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