CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Task

Jindřich Helcl

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arXiv · 2212.00477

CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Task

Jindřich Helcl

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Abstract

We present a non-autoregressive system submission to the WMT 22 Efficient Translation Shared Task. Our system was used by Helcl et al. (2022) in an attempt to provide fair comparison between non-autoregressive and autoregressive models. This submission is an effort to establish solid baselines along with sound evaluation methodology, particularly in terms of measuring the decoding speed. The model itself is a 12-layer Transformer model trained with connectionist temporal classification on knowledge-distilled dataset by a strong autoregressive teacher model.

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BibTeX RIS

Jindřich Helcl. 2022-12-01. CUNI Non-Autoregressive System for the WMT 22 Efficient Translation Shared Task. https://arxiv.org/abs/2212.00477

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