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Audio-Based Deep Learning Algorithm to Identify Alcohol Inebriation (Adlaia)

• giuliomagnifico 4y ago
  > ADLAIA was trained on a publicly available German Alcohol Language Corpus that comprises a total of 12,360 audio clips of inebriated and sober speakers (total of 162, aged 21-64, 47.7% female). ADLAIA’s performance was determined by computing the unweighted average recall (UAR) and accuracy of inebriation prediction. > ADLAIA was able to identify inebriated speakers—with BAC of 0.05% or higher—with an UAR of 68.09% and accuracy of 67.67%. ADLAIA had a higher performance (UAR of 75.7%) in identifying intoxicated speakers (BAC > 0.12%). Far from be accurately but I didn’t know that these kind of training datasets existed: “ ADLAIA was trained on a publicly available German Alcohol Language Corpus that comprises a total of 12,360 audio clips of inebriated and sober speakers”