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  ## Dataset: `librispeech`
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- (Short-form Audio (<30s/clip) - 5 hours of English audiobook clips)
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  | | WER (↓) | QoI (↑) | File Size (MB) |
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  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------:|----------:|-----------------:|
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  | [whisper.cpp/openai_whisper-large-v3](https://hf.co/datasets/argmaxinc/whisperkit-evals/tree/main/whisper.cpp/openai_whisper-large-v3/librispeech) | 1.97 | 95.4 | 3100 |
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  ## Dataset: `earnings22`
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- (Long-Form Audio (>1hr/clip) - 120 hours of earnings call recordings in English with various accents)
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  | | WER (↓) | QoI (↑) | File Size (MB) |
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  |:------------------------------------------------------------------------------------------------------------------------------------------------------------|----------:|----------:|-----------------:|
 
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  ## Dataset: `librispeech`
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+ ## Explanation: Short-form Audio (<30s/clip) - 5 hours of English audiobook clips
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  | | WER (↓) | QoI (↑) | File Size (MB) |
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  |:---------------------------------------------------------------------------------------------------------------------------------------------------------------------------|----------:|----------:|-----------------:|
 
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  | [whisper.cpp/openai_whisper-large-v3](https://hf.co/datasets/argmaxinc/whisperkit-evals/tree/main/whisper.cpp/openai_whisper-large-v3/librispeech) | 1.97 | 95.4 | 3100 |
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  ## Dataset: `earnings22`
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+ ## Explanation: Long-Form Audio (>1hr/clip) - 120 hours of earnings call recordings in English with various accents
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  | | WER (↓) | QoI (↑) | File Size (MB) |
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  |:------------------------------------------------------------------------------------------------------------------------------------------------------------|----------:|----------:|-----------------:|