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. The annotations are provided under a non-commercial license and consist of 85,803 manually annotated audio events including approximately 35,000 filler words (“uh” and “um”) and 50,000 non-filler events such as breaths, music, laughter, repeated words, and noise. The annotated events are also provided as pre-processed 1-second audio clips. The dataset also includes automatically generated speech transcripts from a speech-to-text system. A detailed description is provided in Dataset.


Please cite the following paper in work that makes use of this dataset:

Filler Word Detection and Classification: A Dataset and Benchmark
Ge Zhu, Juan-Pablo Caceres and Justin Salamon
In 23rd Annual Cong. of the Int. Speech Communication Association (INTERSPEECH), Incheon, Korea, Sep. 2022.


  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},


PodcastFillers dataset is hosted at Zenodo.

To unzip the split compressed files, for Mac/Linux users: please use the following command line:

zip -FF PodcastFillers.zip --out PodcastFillers-full.zip
unzip PodcastFillers-full.zip

For Windows users, simply unzip PodcastFillers.zip with WinRAR.

The download link is available at: zenodo