IPA CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling

In this paper, we introduce two resources: (i) G2P+, a tool for converting orthographic datasets to a consistent phonemic representation; and (ii) IPA CHILDES, a phonemic dataset of child-directed and child-produced speech across 31 languages.Prior tools for grapheme-to-phoneme conversion result in phonemic vocabularies that are inconsistent with established phonemic inventories, an issue which G2P+ addresses by leveraging the inventories in the Phoible database (Moran and McCloy, 2019).Using this tool, we augment CHILDES (MacWhinney and Snow, 1985) with phonemic transcriptions to produce IPA CHILDES.This new resource fills several gaps in existing phonemic datasets, which often lack multilingual coverage, spontaneous speech, and a focus on child-directed language.We demonstrate the utility of this dataset for phonological research by training phoneme language models on 11 languages and probing them for distinctive features, finding that the distributional properties of phonemes are sufficient to learn major class and place features cross-lingually.phonemetransformers/ipa-childes

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Published
2025-01-01
DOI
https://doi.org/10.18653/v1/2025.conll-1.33
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

IPA CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling

Paula Buttery, Zébulon Goriely
1 links
Natural Language Processing Techniques
article

IPA CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling

Paula Buttery, Zébulon Goriely
article en

Abstract

In this paper, we introduce two resources: (i) G2P+, a tool for converting orthographic datasets to a consistent phonemic representation; and (ii) IPA CHILDES, a phonemic dataset of child-directed and child-produced speech across 31 languages.Prior tools for grapheme-to-phoneme conversion result in phonemic vocabularies that are inconsistent with established phonemic inventories, an issue which G2P+ addresses by leveraging the inventories in the Phoible database (Moran and McCloy, 2019).Using this tool, we augment CHILDES (MacWhinney and Snow, 1985) with phonemic transcriptions to produce IPA CHILDES.This new resource fills several gaps in existing phonemic datasets, which often lack multilingual coverage, spontaneous speech, and a focus on child-directed language.We demonstrate the utility of this dataset for phonological research by training phoneme language models on 11 languages and probing them for distinctive features, finding that the distributional properties of phonemes are sufficient to learn major class and place features cross-lingually.phonemetransformers/ipa-childes

University of Cambridge (GB), Bridge University (SS)
Dell EMC, Engineering and Physical Sciences Research Council, Science and Technology Facilities Council
Quality Education
Openalex Percentile: Top 90%
Natural Language Processing Techniques
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