Search Results for author:
Found 6 papers, 3 papers with code
Do End-to-End Speech Recognition Models Care About Context?
We test this hypothesis by measuring temporal context sensitivity and evaluate how the models perform when we constrain the amount of contextual information in the audio input.
MultiQT: Multimodal Learning for Real-Time Question Tracking in Speech
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 broader decision support system for emergency call-takers.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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Towards Instance-Level Parser Selection for Cross-Lingual Transfer of Dependency Parsers
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".
Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging
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 languages.
Baselines and test data for cross-lingual inference
In this paper, we propose to advance the research in SNLI-style natural language inference toward multilingual evaluation.
Parsing Universal Dependencies without training
We propose UDP, the first training-free parser for Universal Dependencies (UD).
