2024/09/13 by Jinzuomu Zhong, Korin Richmond, Zhong, Jinzuomu +5 · 3 citations
Computer Science · Engineering · Physics and Astronomy · #Advanced Optical Sensing Technologies #Audio and Speech Processing (eess.AS) #CCD and CMOS Imaging Sensors #Computation and Language (cs.CL) #FOS: Computer and information sciences #FOS: Electrical engineering #Neural Networks and Reservoir Computing #Sound (cs.SD) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2409.09098
openalex publication_date 2024/09/13 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
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 a 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.