paper-with-me

홈 › Papers

Best Practices for Crowdsourcing Dialectal Arabic Speech Transcription

2015-07-01 · WS 2015 7 · Samantha Wray, Hamdy Mubarak, Ahmed Ali
📄 PDF Abstract BibTeX

Code (0)

등록된 구현이 없습니다.

Tasks

Speech Recognition

Similar Papers 제목 키워드 기반

MyVoice: Arabic Speech Resource Collaboration Platform

2023-07-23 · Yousseif Elshahawy, Yassine El Kheir, Shammur Absar Chowdhury, Ahmed Ali

We introduce MyVoice, a crowdsourcing platform designed to collect Arabic speech to enhance dialectal speech technologies. This platform offers an opportunity to design large dialectal speech datasets; and makes them pub…

Ara-Best-RQ: Multi Dialectal Arabic SSL

2026-03-23 · Haroun Elleuch, Ryan Whetten, Salima Mdhaffar, Yannick Estève 외 arxiv

We present Ara-BEST-RQ, a family of self-supervised learning (SSL) models specifically designed for multi-dialectal Arabic speech processing. Leveraging 5,640 hours of crawled Creative Commons speech and combining it wit…

Self-Supervised LearningSpeech Recognition

Arab Voices: Mapping Standard and Dialectal Arabic Speech Technology

2026-01-19 · Peter Sullivan, AbdelRahim Elmadany, Alcides Alcoba Inciarte, Muhammad Abdul-Mageed arxiv

Dialectal Arabic (DA) speech data vary widely in domain coverage, dialect labeling practices, and recording conditions, complicating cross-dataset comparison and model evaluation. To characterize this landscape, we condu…

Arabic Tweet Act: A Weighted Ensemble Pre-Trained Transformer Model for Classifying Arabic Speech Acts on Twitter

2024-01-30 · Khadejaa Alshehri, Areej Alhothali, Nahed Alowidi

Speech acts are a speakers actions when performing an utterance within a conversation, such as asking, recommending, greeting, or thanking someone, expressing a thought, or making a suggestion. Understanding speech acts …

Arabic Sentiment AnalysisData AugmentationEnsemble LearningSentiment Analysis

ELYADATA & LIA at NADI 2025: ASR and ADI Subtasks

2025-11-13 · Haroun Elleuch, Youssef Saidi, Salima Mdhaffar, Yannick Estève 외 arxiv

This paper describes Elyadata \& LIA's joint submission to the NADI multi-dialectal Arabic Speech Processing 2025. We participated in the Spoken Arabic Dialect Identification (ADI) and multi-dialectal Arabic ASR subtasks…

Data Augmentation