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hzhongresearch/yamnetp_ahead_ds
yamnetp_ahead_ds is a audio classification model from hzhongresearch. Use it for the audio classification task on the model card, and read the license before you ship it in a product. It is set up for keras. The card lists the license as cc-by-sa-4.0.
This repository contains the models for OpenYAMNet/YAMNet+, introduced in the paper A dataset and model for auditory scene recognition for hearing devices: AHEAD-DS and OpenYAMNet.
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From the Hugging Face model README
This repository contains the models for OpenYAMNet/YAMNet+, introduced in the paper A dataset and model for auditory scene recognition for hearing devices: AHEAD-DS and OpenYAMNet.
OpenYAMNet is a sound recognition model designed for deployment on edge devices like smartphones connected to hearing devices (e.g., hearing aids and wireless earphones). It serves as a baseline model for sound-based scene recognition.
OpenYAMNet achieved the following results on the testing set of the AHEAD-DS dataset:
The model is optimized for real-time use, with approximately 50ms of latency for loading and a processing time of ~30ms per 1 second of audio on a 2018 Google Pixel 3.
| Classes |
|---|
| cocktail_party |
| interfering_speakers |
| in_traffic |
| in_vehicle |
| music |
| quiet_indoors |
| reverberant_environment |
| wind_turbulence |
| speech_in_traffic |
| speech_in_vehicle |
| speech_in_music |
| speech_in_quiet_indoors |
| speech_in_reverberant_environment |
| speech_in_wind_turbulence |
Licenced under CC BY-SA 4.0. See LICENCE.txt. Licence for original YAMNet weights.
@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},
}