Hugging Face's logo

speechbrain
/
vit-base-esc50

English
Sound Classification
Interpretable Sound Classification
Activation Maps Thresholding
ViT
Model card Files Community
vit-base-esc50
File size: 2,644 Bytes 
375c09a
285c510
 
 
 
 
 
 
 
 
 
375c09a
285c510
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
 
---
language: "en"
thumbnail:
tags:
- Sound Classification
- Interpretable Sound Classification
- Activation Maps Thresholding
- ViT
license: "apache-2.0"
datasets:
- ESC50
---

<iframe src="https://ghbtns.com/github-btn.html?user=speechbrain&repo=speechbrain&type=star&count=true&size=large&v=2" frameborder="0" scrolling="0" width="170" height="30" title="GitHub"></iframe>
<br/><br/>

# ViT Classifier trained on ESC50

This repository provides the pretrained model to perform audio classification with ViT, implemented with SpeechBrain on the ESC50 dataset: 

|  Release   | Accuracy (%) |   Training time    |    GPUs     |
|:----------:|:------------:|:------------------:|:-----------:|
|  01-16-24  |     73.6     | 56 seconds / epoch | 1xV100 32GB |

Please, take a look at the [reference paper](https://arxiv.org/abs/2402.02754) for more info. You can find the training recipe in SpeechBrain [here](https://github.com/speechbrain/speechbrain/tree/develop/recipes/ESC50/interpret).

## Install SpeechBrain

First of all, please install SpeechBrain with the following command:

```
pip install speechbrain
```

Please notice that we encourage you to read our tutorials and learn more about
[SpeechBrain](https://speechbrain.github.io).

### Limitations

The SpeechBrain team does not provide any warranty on the performance achieved by this model when used on other datasets.

#### Referencing SpeechBrain

```bibtex
@misc{speechbrain,
    title={{SpeechBrain}: A General-Purpose Speech Toolkit},
    author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
    year={2021},
    eprint={2106.04624},
    archivePrefix={arXiv},
    primaryClass={eess.AS},
    note={arXiv:2106.04624}
}
```

#### Referencing ViT

If you use this model for your research, please use the following Bibtex to cite it:  
```bibtex
@inproceedings{dellalibera2024focal,
    title={Focal Modulation Networks for Interpretable Sound Classification},
    author={Luca Della Libera and Cem Subakan and Mirco Ravanelli},
    booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) XAI-SA Workshop},
    year={2024},
}
```

# **About SpeechBrain**

- Website: https://speechbrain.github.io/
- Code: https://github.com/speechbrain/speechbrain/
- HuggingFace: https://huggingface.co/speechbrain/