Abstract
This CNVVE Dataset contains clean audio samples encompassing six distinct classes of voice expressions, namely “Uh-huh” or “mm-hmm”, “Uh-uh” or“mm-mm”, “Hush” or “Shh”, “Psst”, “Ahem”, and Continuous humming, e.g., “hmmm.” Audio samples of each class are found in the respective folders. These audio samples have undergone a thorough cleaning process. The raw samples are published in https://doi.org/10.18419/darus-3897. Initially, we applied the Google WebRTC voice activity detection (VAD) algorithm on the given audio files to remove noise or silence from the collected voice signals. The intensity was set to "2", which could be a value between "1" and "3". However, because of variations in the data, some files required additional manual cleaning. These outliers, characterized by sharp click sounds (such as those occurring at the end of recordings), were addressed. The samples are recorded through a dedicated website for data collection that defines the purpose and type of voice data by providing example recordings toparticipants as well as the expressions’ written equivalent, e.g., “Uh-huh”. Audio recordings were automatically saved in the .wav format and keptanonymous, with a sampling rate of 48 kHz and a bit depth of 32 bits. For more info, please check the paper or feel free to contact the authors for any inquiries.
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