Zobrazeno 1 - 10 of 52 pro vyhledávání: '"Daan van Esch"'
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XTREME-S: Evaluating Cross-lingual Speech Representations
Autor: Alexis Conneau, Ankur Bapna, Yu Zhang, Min Ma, Patrick von Platen, Anton Lozhkov, Colin Cherry, Ye Jia, Clara Rivera, Mihir Kale, Daan van Esch, Vera Axelrod, Simran Khanuja, Jonathan Clark, Orhan Firat, Michael Auli, Sebastian Ruder, Jason Riesa, Melvin Johnson
We introduce XTREME-S, a new benchmark to evaluate universal cross-lingual speech representations in many languages. XTREME-S covers four task families: speech recognition, classification, speech-to-text translation and retrieval. Covering 102 langua
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7d5112276248b7b6fa2427d9ed857587
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3
How Might We Create Better Benchmarks for Speech Recognition?
Autor: James Flynn, Alëna Aksënova, Pavel Golik, Daan van Esch
Publikováno v: Proceedings of the 1st Workshop on Benchmarking: Past, Present and Future.
The applications of automatic speech recognition (ASR) systems are proliferating, in part due to recent significant quality improvements. However, as recent work indicates, even state-of-the-art speech recognition systems – some which deliver impre
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::d147bac8634995568c3dd5368ceea862
https://doi.org/10.18653/v1/2021.bppf-1.4
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4
Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus
Autor: Isaac Caswell, Daan van Esch, Ankur Bapna, Theresa Breiner
Publikováno v: COLING
Large text corpora are increasingly important for a wide variety of Natural Language Processing (NLP) tasks, and automatic language identification (LangID) is a core technology needed to collect such datasets in a multilingual context. LangID is larg
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25cfb0764a492e7b9e8ed9f2843fdbdc
http://arxiv.org/abs/2010.14571
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7
Future Directions in Technological Support for Language Documentation
Autor: Daan van Esch, Ben Foley, Nay San
Publikováno v: Proceedings of the Workshop on Computational Methods for Endangered Languages.
To reduce the annotation burden placed on linguistic fieldworkers, freeing up time for deeper linguistic analysis and descriptive work, the language documentation community has been working with machine learning researchers to investigate what assist
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::50ee0c69dea9f35dea3b7933c0903ada
https://doi.org/10.33011/computel.v1i.341
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