Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
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Updated
Mar 31, 2024 - Python
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
Predicting emotions based on speech audio samples of American English, German and British English languages using Support Vector Machine, K-Nearest Neighbor, Random Forest and Recurrent Neural Network. Analyzing the performance of each model based on the dataset.
An experimental project to demonstrate how a user keyboard input may be sniffed through the pattern analysis of the sounds emitted by the keystrokes.
🏆 🏆 Top-1 Submission to CORSMAL Challenge 2020 (at ICPR). The winning solution for the CORSMAL Challenge (on Intelligent Sensing Summer School 2020)
software that analyzes speech utterances
Web application to fight Covid19
Classification base on kernel SVM
Python program to display sound, amplitude and the different frequency ranges in your terminal window
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
Conv2dAE nets as feature extractors VS hand-crafted 'pyaudioanalysis' features
Finds device that is capable of using loopback then opens a stream to get audio directly from system.
Recognising classical composers with machine learning algorithms
Convolutional Neural Network (CNN) functioning as a visual feature extractor and trained using raw speech information.
This Bot can send emails to anyone, any number of times from a USER's account [used GMAIL, here], using MANUAL or VOICE input!
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