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1
XTREME-S: Evaluating Cross-lingual Speech Representations ...
Abstract: 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 languages from 10+ language families, 3 different domains and 4 task families, XTREME-S aims to simplify multilingual speech representation evaluation, as well as catalyze research in "universal" speech representation learning. This paper describes the new benchmark and establishes the first speech-only and speech-text baselines using XLS-R and mSLAM on all downstream tasks. We motivate the design choices and detail how to use the benchmark. Datasets and fine-tuning scripts are made easily accessible at https://hf.co/datasets/google/xtreme_s. ... : Minor fix: language code for Filipino (Tagalog), "tg" -> "tl" ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.2203.10752
https://arxiv.org/abs/2203.10752
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2
CANINE: Pre-training an Efficient Tokenization-Free Encoder for Language Representation ...
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3
TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages ...
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4
XOR QA: Cross-lingual Open-Retrieval Question Answering ...
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5
Learning to Recognize Dialect Features ...
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6
Locally Non-Linear Learning for Statistical Machine Translation via Discretization and Structured Regularization ...
Clark, Jonathan H.; Dyer, Chris; Lavie, Alon. - : Carnegie Mellon University, 2014
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Locally Non-Linear Learning for Statistical Machine Translation via Discretization and Structured Regularization ...
Clark, Jonathan H.; Dyer, Chris; Lavie, Alon. - : Carnegie Mellon University, 2014
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8
The machine translation toolpack for LoonyBin: automated management of experimental machine translation Hyperworkflows
In: The Prague bulletin of mathematical linguistics. - Praha : Univ. (2010) 93, 117-126
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