Open Speech and Language Resources

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Deeply vocal characterizer dataset

Identifier: SLR99

Summary: A human nonverbal vocalization dataset by Deeply Inc.

Category: Audio

License: Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)

Download: VocalCharacterizer.tar.gz [45M]   ( Vocal characterizer dataset )   Mirrors: [US]  

About this resource:

  • Volume(full set): ~0.6(~57) hours, ~800(~70,000) utterances, ~500(~1500) speakers
  • Format: 16kHz, 16-bit, mono
  • Device: Android phones

The Vocal Characterizer Dataset is a human nonverbal vocalization dataset crowdsourced by the general public in South Korea. Also, the dataset includes metadata such as age, sex, noise level, and quality of utterance.
16 classes of Included human nonverbal sound contain 'teeth-chattering', teeth-grinding', 'tongue-clicking', 'nose-blowing', 'coughing', 'yawning', 'throat clearing', 'sighing', 'lip-popping', 'lip-smacking', 'panting', 'crying', 'laughing', 'sneezing', 'moaning', and 'screaming'.

The dataset is a subset(approximately 1%) of a much bigger dataset which were recorded under the same environment as this public dataset.
Please visit our website Deeply Inc., GitHub, or contact us for more details and access to the full set of the dataset with commercial license.

Deeply makes products that anyone can use with audio AI technology and makes people's lives happier with those products. For more products and services, please visit Deeply Inc..



                                               {"label": 0, "speakerID": "87LX", "age": 19, "sex": 0, "location": 0, "quality": 0, "noise": 0},

label   : {0: 'teeth-chattering', 1: 'teeth-grinding', 2: 'tongue-clicking', 3: 'nose-blowing', 
           4: 'coughing', 5: 'yawning', 6: 'throat-clearing', 7: 'sighing', 8: 'lip-popping', 
           9: 'lip-smacking', 10: 'panting', 11: 'crying', 12: 'laughing', 13: 'sneezing', 14: 'moaning', 15: screaming'}
Sex     : {0: 'Female', 1: 'Male'}
Location: {0: 'indoor', 1: 'outdoor'}
Quality : {0: 'High', 1: 'Low'}
Noise   : {0: 'Noiseless', 1: 'Noisy'}

You can cite the data as follows:
  title={{Deeply vocal characterizer dataset}},
  author={Deeply Inc.},

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