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hzhongresearch/ahead_ds

Another HEaring AiD DataSet (AHEAD-DS) Another HEaring AiD DataSet (AHEAD-DS) is an audio dataset labelled with audiologically relevant scene categories for hearing aids. Website Paper Code Dataset AHEAD-DS Dataset AHEAD-DS unmixed Models Description of data All files are encoded as single channel WAV, 16 bit signed, sampled at 16 kHz with 10 seconds per recording. Category Training Validation Testing All cocktail_party 934 134 266 1334… See the full description on the dataset page: https://huggingface.co/datasets/hzhongresearch/ahead_ds.

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Another HEaring AiD DataSet (AHEAD-DS)

Another HEaring AiD DataSet (AHEAD-DS) is an audio dataset labelled with audiologically relevant scene categories for hearing aids.

Description of data

All files are encoded as single channel WAV, 16 bit signed, sampled at 16 kHz with 10 seconds per recording.

Category	Training	Validation	Testing	All
cocktail_party	934	134	266	1334
interfering_speakers	733	105	209	1047
in_traffic	370	53	105	528
in_vehicle	409	59	116	584
music	1047	150	299	1496
quiet_indoors	368	53	104	525
reverberant_environment	156	22	44	222
wind_turbulence	307	44	88	439
speechintraffic	370	53	105	528
speechinvehicle	409	59	116	584
speechinmusic	1047	150	299	1496
speechinquiet_indoors	368	53	104	525
speechinreverberant_environment	155	22	44	221
speechinwind_turbulence	307	44	88	439
Total	6980	1001	1987	9968

Licence

Licenced under CC BY-SA 4.0. See LICENCE.txt.

AHEAD-DS was derived from HEAR-DS (CC0 licence) and CHiME 6 dev (CC BY-SA 4.0 licence). If you use this work, please cite the following publications.

Attribution.

@misc{zhong2026datasetmodelauditoryscene,
      title={A dataset and model for auditory scene recognition for hearing devices: AHEAD-DS and OpenYAMNet}, 
      author={Henry Zhong and Jörg M. Buchholz and Julian Maclaren and Simon Carlile and Richard Lyon},
      year={2026},
      eprint={2508.10360},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2508.10360}, 
}

HEAR-DS attribution.

@inproceedings{huwel2020hearing,
  title={Hearing aid research data set for acoustic environment recognition},
  author={H{\"u}wel, Andreas and Adilo{\u{g}}lu, Kamil and Bach, J{\"o}rg-Hendrik},
  booktitle={ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={706--710},
  year={2020},
  organization={IEEE}
}

CHiME 6 attribution.

@inproceedings{barker18_interspeech,
  author={Jon Barker and Shinji Watanabe and Emmanuel Vincent and Jan Trmal},
  title={{The Fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, Task and Baselines}},
  year=2018,
  booktitle={Proc. Interspeech 2018},
  pages={1561--1565},
  doi={10.21437/Interspeech.2018-1768}
}

@inproceedings{watanabe2020chime,
  title={CHiME-6 Challenge: Tackling multispeaker speech recognition for unsegmented recordings},
  author={Watanabe, Shinji and Mandel, Michael and Barker, Jon and Vincent, Emmanuel and Arora, Ashish and Chang, Xuankai and Khudanpur, Sanjeev and Manohar, Vimal and Povey, Daniel and Raj, Desh and others},
  booktitle={CHiME 2020-6th International Workshop on Speech Processing in Everyday Environments},
  year={2020}
}