Generating Phonetic Embeddings for Bulgarian Words with Neural Networks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A8FSVT5AL" target="_blank" >RIV/00216208:11320/25:8FSVT5AL - isvavai.cz</a>

Výsledek na webu

<a href="https://aclanthology.org/2024.clib-1.6" target="_blank" >https://aclanthology.org/2024.clib-1.6</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Generating Phonetic Embeddings for Bulgarian Words with Neural Networks

Popis výsledku v původním jazyce

Word embeddings can be considered the cornerstone of modern natural language processing. They are used in many NLP tasks and allow us to create models that can understand the meaning of words. Most word embeddings model the semantics of the words. In this paper, we create phoneme-based word embeddings, which model how a word sounds. This is accomplished by training a neural network that can automatically generate transcriptions of Bulgarian words. We used the Jaccard index and direct comparison metrics to measure the performance of neural networks. The models perform nearly perfectly with the task of generating transcriptions. The model's word embeddings offer versatility across various applications, with its application in automatic paronym detection being particularly notable, as well as the task of detecting the language of origin of a Bulgarian word. The performance of this paronym detection is measured with the standard classifier metrics - accuracy, precision, recall, and F1.

Název v anglickém jazyce

Generating Phonetic Embeddings for Bulgarian Words with Neural Networks

Popis výsledku anglicky

Word embeddings can be considered the cornerstone of modern natural language processing. They are used in many NLP tasks and allow us to create models that can understand the meaning of words. Most word embeddings model the semantics of the words. In this paper, we create phoneme-based word embeddings, which model how a word sounds. This is accomplished by training a neural network that can automatically generate transcriptions of Bulgarian words. We used the Jaccard index and direct comparison metrics to measure the performance of neural networks. The models perform nearly perfectly with the task of generating transcriptions. The model's word embeddings offer versatility across various applications, with its application in automatic paronym detection being particularly notable, as well as the task of detecting the language of origin of a Bulgarian word. The performance of this paronym detection is measured with the standard classifier metrics - accuracy, precision, recall, and F1.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)

ISBN

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ISSN

2367-5578

e-ISSN

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Počet stran výsledku

9

Strana od-do

71-79

Název nakladatele

Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences

Místo vydání

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Místo konání akce

Sofia, Bulgaria

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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