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Gender recognition bot

This bot determines gender based upon the voice or the speech acoustic properties. Thanks to multiple layers of artificial neural network, which have been trained with more than 3 thousand items of sample data, this bot works fine for both seen and never seen data-sets (83% accurate, 81% cross-validation).

Embed this bot on your own site, add the code:

<iframe style="max-width: 100% !important; border: none; height:230px" width="560" src="https://hailp.com/api/main/loadwidget/488/parent/csvbulk"></iframe>

TRY ME, FILL IN THE FIELDS

Input details are as follows; more about these attributes can be seen at [1]:

  • [duration]: length of signal
  • [meanfreq]: mean frequency (in kHz)
  • [sd]: standard deviation of frequency
  • [median]: median frequency (in kHz)
  • [Q25]: first quantile (in kHz)
  • [Q75]: third quantile (in kHz)
  • [IQR]: interquantile range (in kHz)
  • [skew]: skewness
  • [kurt]: kurtosis
  • [sp.ent]: spectral entropy
  • [sfm]: spectral flatness
  • [mode]: mode frequency
  • [centroid]: frequency centroid
  • [peakf]: peak frequency (frequency with highest energy)
  • [meanfun]: average of fundamental frequency measured across acoustic signal
  • [minfun]: minimum fundamental frequency measured across acoustic signal
  • [maxfun]: maximum fundamental frequency measured across acoustic signal
  • [meandom]: average of dominant frequency measured across acoustic signal
  • [mindom]: minimum of dominant frequency measured across acoustic signal
  • [maxdom]: maximum of dominant frequency measured across acoustic signal
  • [dfrange]: range of dominant frequency measured across acoustic signal
  • [modindx]: modulation index

[1] Data source: Identifying the Gender of a Voice using Machine Learning –
http://www.primaryobjects.com/kory-becker/

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