1 citations · 1 across the 1 of their papers we have counts for
8 papers
CrowdSpeech and VoxDIY: Benchmark Datasets for Crowdsourced Audio Transcription
Nikita Pavlichenko, Ivan Stelmakh, Dmitry Ustalov
Domain-specific data is the crux of the successful transfer of machine learning systems from benchmarks to real life. In simple problems such as image classification, crowdsourcing…
Word Sense Disambiguation for 158 Languages using Word Embeddings Only
Varvara Logacheva, Denis Teslenko, Artem Shelmanov +7
Disambiguation of word senses in context is easy for humans, but is a major challenge for automatic approaches. Sophisticated supervised and knowledge-based models were developed t…
HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings
Saba Anwar, Dmitry Ustalov, Nikolay Arefyev +3
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsuperv…
Watset: Local-Global Graph Clustering with Applications in Sense and Frame Induction
Dmitry Ustalov, Alexander Panchenko, Chris Biemann +1
We present a detailed theoretical and computational analysis of the Watset meta-algorithm for fuzzy graph clustering, which has been found to be widely applicable in a variety of d…
Unsupervised Semantic Frame Induction using Triclustering
Dmitry Ustalov, Alexander Panchenko, Andrei Kutuzov +2
We use dependency triples automatically extracted from a Web-scale corpus to perform unsupervised semantic frame induction. We cast the frame induction problem as a triclustering p…
An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages
Dmitry Ustalov, Denis Teslenko, Alexander Panchenko +3
In this paper, we present Watasense, an unsupervised system for word sense disambiguation. Given a sentence, the system chooses the most relevant sense of each input word with resp…