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  We believe that rigorously measuring the "quality of inference" is necessary for developers and
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  enterprises to make informed decisions when opting to use optimized or compressed variants of
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  any machine learning model in production. To contextualize `WhisperKit`, we take the following Whisper
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- ---
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- pretty_name: "WhisperKit ASR Evaluation Results"
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- viewer: false
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- tags:
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- - whisper
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- - whisperkit
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- - coreml
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- - asr
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- - quantized
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- ---
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- # WhisperKit Evaluation Results
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  ## Dataset: `librispeech`
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  ### Quality Evaluation
 
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+ ---
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+ pretty_name: "WhisperKit ASR Evaluation Results"
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+ viewer: false
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+ tags:
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+ - whisper
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+ - whisperkit
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+ - coreml
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+ - asr
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+ - quantized
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+ ---
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+ # WhisperKit Evaluation Results
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+
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+
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  We believe that rigorously measuring the "quality of inference" is necessary for developers and
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  enterprises to make informed decisions when opting to use optimized or compressed variants of
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  any machine learning model in production. To contextualize `WhisperKit`, we take the following Whisper
 
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  ## Dataset: `librispeech`
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  ### Quality Evaluation