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Intoxication Detection from Audio Using Deep Learning Public

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Driving under the influence is one of the largest risk factors leading to accidents. Intoxication manifests in the drinker’s voice. This paper explores deep learning architectures and hand extracted features to classify voice samples as either intoxicated of sober. Our method classifies intoxicated speech with an unweighted average recall of 59.2%.

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  • E-project-040720-170111
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Year
  • 2020
Date created
  • 2020-04-07
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Permanent link to this page: https://digital.wpi.edu/show/z890rx02c