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  The End-to-end Speech Challenge (ESC) is a benchmark for assessing a single ASR system on a collection of eight different speech recognition datasets. The ESC datasets are sourced from different domains and cover a range of audio and text distributions (speaking styles, background noise, transcription requirements). ESC consists of:
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- A Hugging Face dataset to easily download and use pre-prepared audio-text data
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- Checkpoints and scripts to reproduce runs for the five official baseline systems
 
 
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- A leaderboard for ranking systems according to overall performance on the benchmark
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  ESC was proposed in _ESC: A Benchmark For Multi-Domain End-to-End Speech Recognition_ by ... For more information, please see the official submission on [OpenReview.net](https://openreview.net/forum?id=9OL2fIfDLK).
 
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  The End-to-end Speech Challenge (ESC) is a benchmark for assessing a single ASR system on a collection of eight different speech recognition datasets. The ESC datasets are sourced from different domains and cover a range of audio and text distributions (speaking styles, background noise, transcription requirements). ESC consists of:
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+ 1) A Hugging Face dataset to easily download and use pre-prepared audio-text data
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+ 2) Checkpoints and scripts to reproduce runs for the five official baseline systems
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+ 3) A leaderboard for ranking systems according to overall performance on the benchmark
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  ESC was proposed in _ESC: A Benchmark For Multi-Domain End-to-End Speech Recognition_ by ... For more information, please see the official submission on [OpenReview.net](https://openreview.net/forum?id=9OL2fIfDLK).