Phonetic Modeling of Dialectal Variation in Vietnamese Speech

Fuente: arXiv
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Autores principales: Hoang, Quan Ngoc, Nguyen, Long Hoang Huu, Nguyen, Nghia Hieu, Van Nguyen, Kiet, Nguyen, Ngan Luu-Thuy
Formato: Preprint
Publicado: 2026
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author Hoang, Quan Ngoc
Nguyen, Long Hoang Huu
Nguyen, Nghia Hieu
Van Nguyen, Kiet
Nguyen, Ngan Luu-Thuy
author_facet Hoang, Quan Ngoc
Nguyen, Long Hoang Huu
Nguyen, Nghia Hieu
Van Nguyen, Kiet
Nguyen, Ngan Luu-Thuy
contents Vietnamese exhibits substantial dialectal phonetic variation across Northern, Central, and Southern regions, where identical lexical items may be realized with markedly different pronunciations. Such variation poses challenges for automatic speech recognition (ASR) and remains difficult to model computationally due to the complex relationship between Vietnamese orthography and phonology. Existing approaches typically address dialect variability at the word level, assuming dialect-invariant mappings between spelling and pronunciation, which limits their ability to capture systematic phonetic differences. We propose a dialect-aware phonetic framework that explicitly models Vietnamese phonological structure and dialectal variation at both the vocabulary and decoding levels. The framework introduces a phonetic vocabulary that decomposes each syllable into structured phonetic components and maps them to dialect-specific IPA representations, together with a phonetic-structure decoder that jointly predicts these components. Experiments on the UIT-ViMD, a only-available dataset for multi-dialect in Vietnamese, show that the proposed approach outperforms various pre-trained baselines, \textbf{especially matches the performance of the strongest pretrained wav2ve2-base-vi-250h} across dialects while \textbf{using substantially fewer parameters and no external pretraining}. Code for experimental reproducibility will be publicly available upon the acceptance of this paper.
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spellingShingle Phonetic Modeling of Dialectal Variation in Vietnamese Speech
Hoang, Quan Ngoc
Nguyen, Long Hoang Huu
Nguyen, Nghia Hieu
Van Nguyen, Kiet
Nguyen, Ngan Luu-Thuy
Computation and Language
Vietnamese exhibits substantial dialectal phonetic variation across Northern, Central, and Southern regions, where identical lexical items may be realized with markedly different pronunciations. Such variation poses challenges for automatic speech recognition (ASR) and remains difficult to model computationally due to the complex relationship between Vietnamese orthography and phonology. Existing approaches typically address dialect variability at the word level, assuming dialect-invariant mappings between spelling and pronunciation, which limits their ability to capture systematic phonetic differences. We propose a dialect-aware phonetic framework that explicitly models Vietnamese phonological structure and dialectal variation at both the vocabulary and decoding levels. The framework introduces a phonetic vocabulary that decomposes each syllable into structured phonetic components and maps them to dialect-specific IPA representations, together with a phonetic-structure decoder that jointly predicts these components. Experiments on the UIT-ViMD, a only-available dataset for multi-dialect in Vietnamese, show that the proposed approach outperforms various pre-trained baselines, \textbf{especially matches the performance of the strongest pretrained wav2ve2-base-vi-250h} across dialects while \textbf{using substantially fewer parameters and no external pretraining}. Code for experimental reproducibility will be publicly available upon the acceptance of this paper.
title Phonetic Modeling of Dialectal Variation in Vietnamese Speech
topic Computation and Language
url https://arxiv.org/abs/2605.24451