9 citations · 9 across the 2 of their papers we have counts for
5 papers
Do End-to-End Speech Recognition Models Care About Context?
Lasse Borgholt, Jakob Drachmann Havtorn, Željko Agić +3
The two most common paradigms for end-to-end speech recognition are connectionist temporal classification (CTC) and attention-based encoder-decoder (AED) models. It has been argued…
MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech
Jakob D. Havtorn, Jan Latko, Joakim Edin +6
We address a challenging and practical task of labeling questions in speech in real time during telephone calls to emergency medical services in English, which embeds within a broa…
Towards Instance-Level Parser Selection for Cross-Lingual Transfer of Dependency Parsers
Robert Litschko, Ivan Vulić, Željko Agić +1
Current methods of cross-lingual parser transfer focus on predicting the best parser for a low-resource target language globally, that is, "at treebank level". In this work, we pro…
The Best of Both Worlds: Lexical Resources To Improve Low-Resource Part-of-Speech Tagging
Barbara Plank, Sigrid Klerke, Zeljko Agic
In natural language processing, the deep learning revolution has shifted the focus from conventional hand-crafted symbolic representations to dense inputs, which are adequate repre…
Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging
Barbara Plank, Željko Agić
We introduce DsDs: a cross-lingual neural part-of-speech tagger that learns from disparate sources of distant supervision, and realistically scales to hundreds of low-resource lang…