Wav2Gloss: Generating Interlinear Glossed Text from Speech

Fuente: arXiv
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Hauptverfasser: He, Taiqi, Choi, Kwanghee, Tjuatja, Lindia, Robinson, Nathaniel R., Shi, Jiatong, Watanabe, Shinji, Neubig, Graham, Mortensen, David R., Levin, Lori
Format: Preprint
Veröffentlicht: 2024
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author He, Taiqi
Choi, Kwanghee
Tjuatja, Lindia
Robinson, Nathaniel R.
Shi, Jiatong
Watanabe, Shinji
Neubig, Graham
Mortensen, David R.
Levin, Lori
author_facet He, Taiqi
Choi, Kwanghee
Tjuatja, Lindia
Robinson, Nathaniel R.
Shi, Jiatong
Watanabe, Shinji
Neubig, Graham
Mortensen, David R.
Levin, Lori
contents Thousands of the world's languages are in danger of extinction--a tremendous threat to cultural identities and human language diversity. Interlinear Glossed Text (IGT) is a form of linguistic annotation that can support documentation and resource creation for these languages' communities. IGT typically consists of (1) transcriptions, (2) morphological segmentation, (3) glosses, and (4) free translations to a majority language. We propose Wav2Gloss: a task in which these four annotation components are extracted automatically from speech, and introduce the first dataset to this end, Fieldwork: a corpus of speech with all these annotations, derived from the work of field linguists, covering 37 languages, with standard formatting, and train/dev/test splits. We provide various baselines to lay the groundwork for future research on IGT generation from speech, such as end-to-end versus cascaded, monolingual versus multilingual, and single-task versus multi-task approaches.
format Preprint
id arxiv_https___arxiv_org_abs_2403_13169
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Wav2Gloss: Generating Interlinear Glossed Text from Speech
He, Taiqi
Choi, Kwanghee
Tjuatja, Lindia
Robinson, Nathaniel R.
Shi, Jiatong
Watanabe, Shinji
Neubig, Graham
Mortensen, David R.
Levin, Lori
Computation and Language
Thousands of the world's languages are in danger of extinction--a tremendous threat to cultural identities and human language diversity. Interlinear Glossed Text (IGT) is a form of linguistic annotation that can support documentation and resource creation for these languages' communities. IGT typically consists of (1) transcriptions, (2) morphological segmentation, (3) glosses, and (4) free translations to a majority language. We propose Wav2Gloss: a task in which these four annotation components are extracted automatically from speech, and introduce the first dataset to this end, Fieldwork: a corpus of speech with all these annotations, derived from the work of field linguists, covering 37 languages, with standard formatting, and train/dev/test splits. We provide various baselines to lay the groundwork for future research on IGT generation from speech, such as end-to-end versus cascaded, monolingual versus multilingual, and single-task versus multi-task approaches.
title Wav2Gloss: Generating Interlinear Glossed Text from Speech
topic Computation and Language
url https://arxiv.org/abs/2403.13169