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Deeply Vocal Characterizer Dataset

A dataset by Deeply
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Deeply Vocal Characterizer Dataset

Volume

57 Hours of Audio
70,000 Records

Use Cases

Geography

Asia (1)
Korea (Republic of)

Categories

Product Description

The Vocal Characterizer Dataset is a human nonverbal vocal sound dataset consisting of 56.7 hours of short clips from 1419 speakers, crowdsourced by the general public in South Korea and validated by the AI data platform. 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 the first dataset to the world due to its large volume, various types of nonverbal vocal cues, and various participants. We expect that the utilization of this dataset would bring precise detection of the nonverbal vocal cues, and a better understanding of the human conversation. We're ready to deliver further information, statistics, or samples upon request. Don't hesitate to reach out! *The dataset can be delivered as either original wav files(44,100Hz, 16-bit PCM, 1-channel) or a single compressed h5 file(resampled to 16,000Hz).

Suitable Company Sizes

Small Business
Medium-sized Business
Enterprise

Pricing

Free sample available
Deeply has not published pricing information for this product yet. You can request detailed pricing information below.

Quality

Self-reported by the provider
Validity

Delivery

Methods
S3 Bucket
SFTP
Email
UI Export
REST API
SOAP API
Streaming API
Feed API

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