Denys Katerenchuk


Interpersonal Relationship Labels for the CALLHOME Corpus
Denys Katerenchuk | David Guy Brizan | Andrew Rosenberg
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


Age Group Classification with Speech and Metadata Multimodality Fusion
Denys Katerenchuk
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers

Children comprise a significant proportion of TV viewers and it is worthwhile to customize the experience for them. However, identifying who is a child in the audience can be a challenging task. We present initial studies of a novel method which combines utterances with user metadata. In particular, we develop an ensemble of different machine learning techniques on different subsets of data to improve child detection. Our initial results show an 9.2% absolute improvement over the baseline, leading to a state-of-the-art performance.


RankDCG: Rank-Ordering Evaluation Measure
Denys Katerenchuk | Andrew Rosenberg
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

Ranking is used for a wide array of problems, most notably information retrieval (search). Kendall’s τ, Average Precision, and nDCG are a few popular approaches to the evaluation of ranking. When dealing with problems such as user ranking or recommendation systems, all these measures suffer from various problems, including the inability to deal with elements of the same rank, inconsistent and ambiguous lower bound scores, and an inappropriate cost function. We propose a new measure, a modification of the popular nDCG algorithm, named rankDCG, that addresses these problems. We provide a number of criteria for any effective ranking algorithm and show that only rankDCG satisfies them all. Results are presented on constructed and real data sets. We release a publicly available rankDCG evaluation package.