331 citations · 581 across the 12 of their papers we have counts for
12 papers
Yet Another Format of Universal Dependencies for Korean
Yige Chen, Eunkyul Leah Jo, Yundong Yao +4
In this study, we propose a morpheme-based scheme for Korean dependency parsing and adopt the proposed scheme to Universal Dependencies. We present the linguistic rationale that il…
Curriculum optimization for low-resource speech recognition
Anastasia Kuznetsova, Anurag Kumar, Jennifer Drexler Fox +1
Modern end-to-end speech recognition models show astonishing results in transcribing audio signals into written text. However, conventional data feeding pipelines may be sub-optima…
Evaluating Multiway Multilingual NMT in the Turkic Languages
Jamshidbek Mirzakhalov, Anoop Babu, Aigiz Kunafin +11
Despite the increasing number of large and comprehensive machine translation (MT) systems, evaluation of these methods in various languages has been restrained by the lack of high-…
A Large-Scale Study of Machine Translation in the Turkic Languages
Jamshidbek Mirzakhalov, Anoop Babu, Duygu Ataman +13
Recent advances in neural machine translation (NMT) have pushed the quality of machine translation systems to the point where they are becoming widely adopted to build competitive…
What shall we do with an hour of data? Speech recognition for the un- and under-served languages of Common Voice
Francis M. Tyers, Josh Meyer
This technical report describes the methods and results of a three-week sprint to produce deployable speech recognition models for 31 under-served languages of the Common Voice pro…
Do RNN States Encode Abstract Phonological Processes?
Miikka Silfverberg, Francis Tyers, Garrett Nicolai +1
Sequence-to-sequence models have delivered impressive results in word formation tasks such as morphological inflection, often learning to model subtle morphophonological details wi…
A bandit approach to curriculum generation for automatic speech recognition
Anastasia Kuznetsova, Anurag Kumar, Francis M. Tyers
The Automated Speech Recognition (ASR) task has been a challenging domain especially for low data scenarios with few audio examples. This is the main problem in training ASR system…
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection
Ekaterina Vylomova, Jennifer White, Elizabeth Salesky +25
A broad goal in natural language processing (NLP) is to develop a system that has the capacity to process any natural language. Most systems, however, are developed using data from…
Neural Polysynthetic Language Modelling
Lane Schwartz, Francis Tyers, Lori Levin +18
Research in natural language processing commonly assumes that approaches that work well for English and and other widely-used languages are "language agnostic". In high-resource la…
Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection
Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter +6
Universal Dependencies is an open community effort to create cross-linguistically consistent treebank annotation for many languages within a dependency-based lexicalist framework.…
Common Voice: A Massively-Multilingual Speech Corpus
Rosana Ardila, Megan Branson, Kelly Davis +7
The Common Voice corpus is a massively-multilingual collection of transcribed speech intended for speech technology research and development. Common Voice is designed for Automatic…
Can LSTM Learn to Capture Agreement? The Case of Basque
Shauli Ravfogel, Francis M. Tyers, Yoav Goldberg
Sequential neural networks models are powerful tools in a variety of Natural Language Processing (NLP) tasks. The sequential nature of these models raises the questions: to what ex…