title: README
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The End-to-end Speech Challenge (ESC) is a benchmark for assessing ASR systems on a collection of eight different speech recognition datasets. The ESC datasets are sourced from 11 different domains and cover a range of audio and text distributions (speaking styles, background noise, transcription requirements). There is no restriction on architecture or training data. The only constraint is that systems must use the same training and evaluation algorithms across datasets and may not use any dataset-specific pre- or post-processing. The objective of ESC is to promote generalisable ASR systems that can be applied in a multi-domain setting.
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ESC was proposed in ESC: A Benchmark For Multi-Domain End-to-End Speech Recognition by ... For more information, see the official submission on OpenReview.net or the blog post at ESC Benchmark (TODO).