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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AKPN45TQ2" target="_blank" >RIV/00216208:11320/25:KPN45TQ2 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195962730&partnerID=40&md5=ad103ca911e138ea333820b268b32c30" target="_blank" >https://www.scopus.com/inward/record.uri?eid=2-s2.0-85195962730&partnerID=40&md5=ad103ca911e138ea333820b268b32c30</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

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

Result continuities

  • Project

  • Continuities

Others

  • Publication year

    2024

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Jt. Int. Conf. Comput. Linguist., Lang. Resour. Eval., LREC-COLING - Main Conf. Proc.

  • ISBN

    978-249381410-4

  • ISSN

  • e-ISSN

  • Number of pages

    13

  • Pages from-to

    17770-17782

  • Publisher name

    European Language Resources Association (ELRA)

  • Place of publication

  • Event location

    Torino, Italia

  • Event date

    Jan 1, 2025

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article