Work

Computational Benchmarks for Egyptian Arabic Child Directed Speech

Year: 2026

Type: conference-paper

Abstract: We present ARABABYTALK-EGY, an enriched release of the Egyptian Arabic CHILDES corpus, that opens the child-adult interactions genre to modern Arabic NLP research.Starting from the original CHILDES recordings and IPA transcriptions of caregiver-child sessions, we (i) map each IPA token to fully diacritized Arabic script, and (ii) add core part-of-speech tags and lemmas aligned with existing dialectal Arabic morphological resources.These layers yield ∼26K annotated tokens suitable for both text-and speech-based NLP tasks.We provide a benchmark on morphological disambiguation and Arabic ASR.We outline lexical and morphosyntactic differences between ARABABYTALK-EGY and general Egyptian Arabic resources, highlighting the value of genrespecific training data for language acquisition studies and Arabic speech technology. 1 BPæbu-be dæ? ‫َﻩ؟‬ ِ ‫ﺍ‬ ُ ‫ﺃ‬

Source: Conference of the European Chapter of the Association for Computational Linguistics

DOI: 10.18653/v1/2026.eacl-long.102

Authors: Salam Khalifa, Abed Qaddoumi, Nizar Habash, Owen Rambow

Institutions: New York University Abu Dhabi, Stony Brook University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funder: Stony Brook University

OpenAlex ID: W7140105413