dataset_info:
features:
- name: license
dtype: string
- name: audio
dtype: audio
- name: file_name
dtype: string
- name: episode_name
dtype: string
- name: original_split
dtype: string
- name: sampling_rate
dtype: int64
- name: audio_length
dtype: float64
splits:
- name: CC_BY_3.0
num_bytes: 4245155531.5879397
num_examples: 100
- name: CC_BY_SA_3.0
num_bytes: 3168500218.8944726
num_examples: 79
- name: CC_BY_ND_3.0
num_bytes: 961275962.5175879
num_examples: 20
download_size: 8343014658
dataset_size: 8374931713
configs:
- config_name: default
data_files:
- split: CC_BY_3.0
path: data/CC_BY_3.0-*
- split: CC_BY_SA_3.0
path: data/CC_BY_SA_3.0-*
- split: CC_BY_ND_3.0
path: data/CC_BY_ND_3.0-*
license: cc
Some Podcasts
Podcasts are taken from the PodcastFillers dataset. The PodcastFillers dataset consists of 199 full-length podcast episodes in English with manually annotated filler words and automatically generated transcripts. The podcast audio recordings, sourced from SoundCloud, are CC-licensed, gender-balanced, and total 145 hours of audio from over 350 speakers.
This dataset doesn't upload the PodcastFillers annotations, which are under a non-commercial license. See here for more details.
Length by license type
CC_BY 3.0: Total length: 73.6 h. Mean length: 44.2 min
CC_BY SA 3.0: Total length: 54.9 h. Mean length: 41.7 min
CC_BY ND 3.0 : Total length: 16.7 h. Mean length: 50 min
License
See here for more details. The licenses are also in the metadata.
Citation Information
@inproceedings{Zhu:FillerWords:INTERSPEECH:22,
title = {Filler Word Detection and Classification: A Dataset and Benchmark},
booktitle = {23rd Annual Cong.~of the Int.~Speech Communication Association (INTERSPEECH)},
address = {Incheon, Korea},
month = {Sep.},
url = {https://arxiv.org/abs/2203.15135},
author = {Zhu, Ge and Caceres, Juan-Pablo and Salamon, Justin},
year = {2022},
}
Contributions
Thanks to @ylacombe for adding this dataset.