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Rufael Marew

Rufael Marew has 2 papers in our library, in 2025–2026, most of them on Speech & spoken language, Semitic languages; often with Hanan Aldarmaki, Amr Keleg, Hawau Olamide Toyin.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 2 · 11 works · 10 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 8 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6020

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2025–2026 · 6 paperscurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksSignal Processing · 2 works

🧭 Topics 2Research subjects and languages the work is about.Semitic languages · 2 worksSpeech & spoken language · 2 works

 Works by year

2020s

20261 paperConstrained CTC Decoding for Efficient Diacritic Restoration20251 paperArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis

 Papers

The most cited first (OpenAlex and our library).

  1. ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis (2025 · 6 citations)
    Arabic speech synthesis lacks clean, multi-speaker training data with full diacritics. Without diacritics, the vowels are unspecified, so a TTS system has to guess how each word is pronounced. Existing Arabic speech collections were mostly built for ASR from noisy broadcast or web audio. The two open TTS corpora, ASC…
  2. Constrained CTC Decoding for Efficient Diacritic Restoration (2026)
    The paper addresses speech-to-text diacritization of Arabic. Given a recording and its undiacritized transcript, the goal is a fully vowelled transcript that agrees with both. Earlier systems pair an ASR model with a separate text decoder and train them jointly. The authors replace that multi-modal pipeline with a…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. ArVoice: A Multi-Speaker Dataset for Arabic Speech SynthesisInterspeechHawau Olamide Toyin, Rufael Marew, Humaid Alblooshi, et al.2025 · 6 citations
  2. KSAA-2026 Shared Task on Arabic Speech Dictation with Automatic DiacritizationThe 7th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT7) with 5 Shared Tasks · original ↗ · no summary yetAsma Ali Al Wazrah et al.2026 · 4 citations
  3. Constrained CTC Decoding for Efficient Diacritic RestorationarXiv:2607.18946Rufael Marew, Amr Keleg, Hanan Aldarmaki2026

 Co-authors here

5 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 8 times (of the 141,840 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/rufael-marew/