greenarcade/wav2vec2-vd-bird-sound-classification

Bird sound classification model trained on my custom dataset. Identifies local bird species from audio recordings.

Usage

from transformers import pipeline

classifier = pipeline("audio-classification", "greenarcade/wav2vec2-vd-bird-sound-classification")
result = classifier("your_audio.wav", top_k=3)

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• Developed by: Suvan GS & [Dharanya T]
• Model type: Transformers
• License: MIT

Model Sources [optional]

• Repository: Minor Project
• Paper : Coming Soon
• Demo [optional]: Space

Uses

Used to Classify the sounds for the 21 species of birds observed at Vedanthangal Bird Sanctuary

Out-of-Scope Use

The model will not work for any of the species not listed below:

Species Common Name
Asian openbill stork
Blue-tailed bee-eater
Common kingfisher
Eurasian spoonbill
Fulvous whistling duck
Garganey
Glossy ibis
Golden oriole
Great egret
Grey Heron
Indian pond heron
Indian spot-billed duck
Little egret
Northern pintail
Northern shoveler
Painted stork
Rosy starling
Spot-billed pelican
Spotted owlet
White Ibis
White-throated kingfisher

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Training Details

Training Data

[More Information Needed]

Training Procedure

Preprocessing [optional]

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Training Hyperparameters

• Training regime: [More Information Needed]

Speeds, Sizes, Times [optional]

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Evaluation

Testing Data, Factors & Metrics

Testing Data

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Factors

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Metrics

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Results

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Summary

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• Hardware Type: [More Information Needed]
• Hours used: [More Information Needed]
• Cloud Provider: [More Information Needed]
• Compute Region: [More Information Needed]
• Carbon Emitted: [More Information Needed]

Technical Specifications [optional]

Model Architecture and Objective

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Compute Infrastructure

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Hardware

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Software

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Citation [optional]

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APA:

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Glossary [optional]

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