license: mit
language:
- en
library_name: adapter-transformers
pipeline_tag: audio-classification
tags:
- code
- audio
- clap detection
- machine learning
Model Card for Clap Detection Model
Model Details
Model Description
This model is a deep learning-based audio classifier trained to detect claps in audio recordings. It has been developed using the PyTorch framework and utilizes the adapter-transformers library. The model can differentiate between clap sounds and background noise.
Uses
Direct Use
The model can be directly used to detect claps in audio recordings.
Bias, Risks, and Limitations
The model may have limitations in accurately detecting claps in noisy environments or when there are overlapping sounds. It is recommended to evaluate the model's performance in various real-world scenarios.
How to Get Started with the Model
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Training Details
Training Data
The model was trained on a dataset consisting of audio recordings containing both clap sounds and background noise.
Evaluation
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Environmental Impact
Carbon emissions and additional considerations have not been evaluated for this model.
Technical Specifications
Model Architecture and Objective
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Compute Infrastructure
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Citation
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Model Card Authors
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Model Card Contact
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