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Demo Data from EDBT 2026 / reviewers in the wild / expert

Chiebuka Ohams

dblp:401/9490 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Speech recognition and synthesis · 50% Information extraction and text analysis · 50%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Speech recognition and synthesis › text-to-speech synthesis
prosody modeling		 0.912025
The time scale of redundancy between prosody and linguistic context · ACL (1) 2025

Methods — techniques the papers use, named apart from their topics

information-theoretic analysis · 0.9
YearPublicationVenuePosition
2025 The time scale of redundancy between prosody and linguistic context
abstract
Tamar I Regev, Chiebuka Ohams, Shaylee Xie, Lukas Wolf, Evelina Fedorenko, Alex Warstadt, Ethan Wilcox, Tiago Pimentel. Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2025.
Tamar I. Regev, Chiebuka Ohams, Shaylee Xie, Lukas Wolf, Evelina Fedorenko, Alex Warstadt, Ethan Wilcox, Tiago Pimentel
 ACL (1)2