Affectron: Emotional Speech Synthesis with Affective and Contextually Aligned Nonverbal Vocalizations

Fuente: arXiv
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Autori principali: Cho, Deok-Hyeon, Oh, Hyung-Seok, Kim, Seung-Bin, Lee, Seong-Whan
Natura: Preprint
Pubblicazione: 2026
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author Cho, Deok-Hyeon
Oh, Hyung-Seok
Kim, Seung-Bin
Lee, Seong-Whan
author_facet Cho, Deok-Hyeon
Oh, Hyung-Seok
Kim, Seung-Bin
Lee, Seong-Whan
contents Nonverbal vocalizations (NVs), such as laughter and sighs, are central to the expression of affective cues in emotional speech synthesis. However, learning diverse and contextually aligned NVs remains challenging in open settings due to limited NV data and the lack of explicit supervision. Motivated by this challenge, we propose Affectron as a framework for affective and contextually aligned NV generation. Built on a small-scale open and decoupled corpus, Affectron introduces an NV-augmented training strategy that expands the distribution of NV types and insertion locations. We further incorporate NV structural masking into a speech backbone pre-trained on purely verbal speech to enable diverse and natural NV synthesis. Experimental results demonstrate that Affectron produces more expressive and diverse NVs than baseline systems while preserving the naturalness of the verbal speech stream.
format Preprint
id arxiv_https___arxiv_org_abs_2603_14432
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Affectron: Emotional Speech Synthesis with Affective and Contextually Aligned Nonverbal Vocalizations
Cho, Deok-Hyeon
Oh, Hyung-Seok
Kim, Seung-Bin
Lee, Seong-Whan
Sound
Nonverbal vocalizations (NVs), such as laughter and sighs, are central to the expression of affective cues in emotional speech synthesis. However, learning diverse and contextually aligned NVs remains challenging in open settings due to limited NV data and the lack of explicit supervision. Motivated by this challenge, we propose Affectron as a framework for affective and contextually aligned NV generation. Built on a small-scale open and decoupled corpus, Affectron introduces an NV-augmented training strategy that expands the distribution of NV types and insertion locations. We further incorporate NV structural masking into a speech backbone pre-trained on purely verbal speech to enable diverse and natural NV synthesis. Experimental results demonstrate that Affectron produces more expressive and diverse NVs than baseline systems while preserving the naturalness of the verbal speech stream.
title Affectron: Emotional Speech Synthesis with Affective and Contextually Aligned Nonverbal Vocalizations
topic Sound
url https://arxiv.org/abs/2603.14432