PWESuite: Phonetic Word Embeddings and Tasks They Facilitate

Fuente: arXiv
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Auteurs principaux: Zouhar, Vilém, Chang, Kalvin, Cui, Chenxuan, Carlson, Nathaniel, Robinson, Nathaniel, Sachan, Mrinmaya, Mortensen, David
Format: Preprint
Publié: 2023
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author Zouhar, Vilém
Chang, Kalvin
Cui, Chenxuan
Carlson, Nathaniel
Robinson, Nathaniel
Sachan, Mrinmaya
Mortensen, David
author_facet Zouhar, Vilém
Chang, Kalvin
Cui, Chenxuan
Carlson, Nathaniel
Robinson, Nathaniel
Sachan, Mrinmaya
Mortensen, David
contents Mapping words into a fixed-dimensional vector space is the backbone of modern NLP. While most word embedding methods successfully encode semantic information, they overlook phonetic information that is crucial for many tasks. We develop three methods that use articulatory features to build phonetically informed word embeddings. To address the inconsistent evaluation of existing phonetic word embedding methods, we also contribute a task suite to fairly evaluate past, current, and future methods. We evaluate both (1) intrinsic aspects of phonetic word embeddings, such as word retrieval and correlation with sound similarity, and (2) extrinsic performance on tasks such as rhyme and cognate detection and sound analogies. We hope our task suite will promote reproducibility and inspire future phonetic embedding research.
format Preprint
id arxiv_https___arxiv_org_abs_2304_02541
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle PWESuite: Phonetic Word Embeddings and Tasks They Facilitate
Zouhar, Vilém
Chang, Kalvin
Cui, Chenxuan
Carlson, Nathaniel
Robinson, Nathaniel
Sachan, Mrinmaya
Mortensen, David
Computation and Language
Mapping words into a fixed-dimensional vector space is the backbone of modern NLP. While most word embedding methods successfully encode semantic information, they overlook phonetic information that is crucial for many tasks. We develop three methods that use articulatory features to build phonetically informed word embeddings. To address the inconsistent evaluation of existing phonetic word embedding methods, we also contribute a task suite to fairly evaluate past, current, and future methods. We evaluate both (1) intrinsic aspects of phonetic word embeddings, such as word retrieval and correlation with sound similarity, and (2) extrinsic performance on tasks such as rhyme and cognate detection and sound analogies. We hope our task suite will promote reproducibility and inspire future phonetic embedding research.
title PWESuite: Phonetic Word Embeddings and Tasks They Facilitate
topic Computation and Language
url https://arxiv.org/abs/2304.02541