Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Data

Fuente: arXiv
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Hauptverfasser: Lertpetchpun, Thanathai, Trachu, Thanapat, Lee, Jihwan, Feng, Tiantian, Byrd, Dani, Narayanan, Shrikanth
Format: Preprint
Veröffentlicht: 2026
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author Lertpetchpun, Thanathai
Trachu, Thanapat
Lee, Jihwan
Feng, Tiantian
Byrd, Dani
Narayanan, Shrikanth
author_facet Lertpetchpun, Thanathai
Trachu, Thanapat
Lee, Jihwan
Feng, Tiantian
Byrd, Dani
Narayanan, Shrikanth
contents Accent is an integral part of society, reflecting multiculturalism and shaping how individuals express identity. The majority of English speakers are non-native (L2) speakers, yet current Text-To-Speech (TTS) systems primarily model American-accented English due limited accented data. We propose \textit{Accent Vector}, a controllable representation that enables accent manipulation in multilingual TTS without requiring accented training data. \textit{Accent Vector} is derived by fine-tuning a TTS system on native speech of a different language (i.e. non-English) and computing task vectors capturing accent characteristics (i.e. in English). By scaling and interpolating the vector, we achieve fine-grained control over accent strength and generate mixed-accent speech. In addition, it generalizes beyond English, enabling accent control across multiple languages. Objective and human evaluations confirm the effectiveness of Accent Vector for fine-grained and compositional accent control.
format Preprint
id arxiv_https___arxiv_org_abs_2603_07534
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Data
Lertpetchpun, Thanathai
Trachu, Thanapat
Lee, Jihwan
Feng, Tiantian
Byrd, Dani
Narayanan, Shrikanth
Computation and Language
Accent is an integral part of society, reflecting multiculturalism and shaping how individuals express identity. The majority of English speakers are non-native (L2) speakers, yet current Text-To-Speech (TTS) systems primarily model American-accented English due limited accented data. We propose \textit{Accent Vector}, a controllable representation that enables accent manipulation in multilingual TTS without requiring accented training data. \textit{Accent Vector} is derived by fine-tuning a TTS system on native speech of a different language (i.e. non-English) and computing task vectors capturing accent characteristics (i.e. in English). By scaling and interpolating the vector, we achieve fine-grained control over accent strength and generate mixed-accent speech. In addition, it generalizes beyond English, enabling accent control across multiple languages. Objective and human evaluations confirm the effectiveness of Accent Vector for fine-grained and compositional accent control.
title Accent Vector: Controllable Accent Manipulation for Multilingual TTS Without Accented Data
topic Computation and Language
url https://arxiv.org/abs/2603.07534