https://github.com/kavayk29/audio-classification-using-python-library

This is a audio classification Project using python Libraries such as librosa to make the visual representation of the audio files, and using numpy to make array of data for manipulation and then extraction the features for classification to train and test of CNN model.
https://github.com/kavayk29/audio-classification-using-python-library

librosa matplotlib-pyplot mfcc-features numpy pandas sklearn-library

Last synced: 8 days ago
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This is a audio classification Project using python Libraries such as librosa to make the visual representation of the audio files, and using numpy to make array of data for manipulation and then extraction the features for classification to train and test of CNN model.

• Host: GitHub
• URL: https://github.com/kavayk29/audio-classification-using-python-library
• Owner: Kavayk29
• Created: 2023-06-21T15:18:07.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2024-08-08T17:11:50.000Z (3 months ago)
• Last Synced: 2024-08-08T20:05:12.712Z (3 months ago)
• Topics: librosa, matplotlib-pyplot, mfcc-features, numpy, pandas, sklearn-library
• Language: Jupyter Notebook
• Homepage:
• Size: 1.34 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Audio-classification-using-Python-Library

This project focuses on audio processing and analysis using Python libraries like librosa and matplotlib. It includes tasks such as loading audio files, visualizing waveforms, and analyzing audio characteristics like sample rate and channels. The project is a comprehensive exploration of audio data manipulation, with potential applications in audio classification, signal processing, and machine learning.

Key Features:

Audio Visualization: Load and visualize audio waveforms to understand the structure and characteristics of sound signals.

Data Handling: Import and manage metadata associated with audio files, enabling detailed analysis and processing.

Exploratory Analysis: Investigate various audio features, including sample rate and channel information, to better understand the data.

Technologies Used:

Python: The primary language for all data processing and analysis tasks.

Librosa: A powerful library for audio analysis and manipulation.

Matplotlib: Used for visualizing audio waveforms and other relevant data.

This project is ideal for anyone interested in exploring the fundamentals of audio processing and its applications in various domains like machine learning and signal processing.