ZAEBUC-Spoken: A Multilingual Multidialectal Arabic-English Speech Corpus

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Hamed, Injy, Eryani, Fadhl, Palfreyman, David, Habash, Nizar
Natura: Preprint
Pubblicazione: 2024
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866909152281886720
author Hamed, Injy
Eryani, Fadhl
Palfreyman, David
Habash, Nizar
author_facet Hamed, Injy
Eryani, Fadhl
Palfreyman, David
Habash, Nizar
contents We present ZAEBUC-Spoken, a multilingual multidialectal Arabic-English speech corpus. The corpus comprises twelve hours of Zoom meetings involving multiple speakers role-playing a work situation where Students brainstorm ideas for a certain topic and then discuss it with an Interlocutor. The meetings cover different topics and are divided into phases with different language setups. The corpus presents a challenging set for automatic speech recognition (ASR), including two languages (Arabic and English) with Arabic spoken in multiple variants (Modern Standard Arabic, Gulf Arabic, and Egyptian Arabic) and English used with various accents. Adding to the complexity of the corpus, there is also code-switching between these languages and dialects. As part of our work, we take inspiration from established sets of transcription guidelines to present a set of guidelines handling issues of conversational speech, code-switching and orthography of both languages. We further enrich the corpus with two layers of annotations; (1) dialectness level annotation for the portion of the corpus where mixing occurs between different variants of Arabic, and (2) automatic morphological annotations, including tokenization, lemmatization, and part-of-speech tagging.
format Preprint
id arxiv_https___arxiv_org_abs_2403_18182
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle ZAEBUC-Spoken: A Multilingual Multidialectal Arabic-English Speech Corpus
Hamed, Injy
Eryani, Fadhl
Palfreyman, David
Habash, Nizar
Computation and Language
We present ZAEBUC-Spoken, a multilingual multidialectal Arabic-English speech corpus. The corpus comprises twelve hours of Zoom meetings involving multiple speakers role-playing a work situation where Students brainstorm ideas for a certain topic and then discuss it with an Interlocutor. The meetings cover different topics and are divided into phases with different language setups. The corpus presents a challenging set for automatic speech recognition (ASR), including two languages (Arabic and English) with Arabic spoken in multiple variants (Modern Standard Arabic, Gulf Arabic, and Egyptian Arabic) and English used with various accents. Adding to the complexity of the corpus, there is also code-switching between these languages and dialects. As part of our work, we take inspiration from established sets of transcription guidelines to present a set of guidelines handling issues of conversational speech, code-switching and orthography of both languages. We further enrich the corpus with two layers of annotations; (1) dialectness level annotation for the portion of the corpus where mixing occurs between different variants of Arabic, and (2) automatic morphological annotations, including tokenization, lemmatization, and part-of-speech tagging.
title ZAEBUC-Spoken: A Multilingual Multidialectal Arabic-English Speech Corpus
topic Computation and Language
url https://arxiv.org/abs/2403.18182