Machine Learning Sound Classifier

Sound classification using ML.NET and D-CNN's

Heartbeat Sound Segmentation and Classification. Implemented ways to clean noisy hearbeat sounds in MATLAB and later trained ML models to classify the hearbeat sounds into diseased and normal categories

Clasifying urban sound into 10 different class followind UrbanSoun8K dataset, using a CNN in python. Implementing FIWARE for IoT network services.

An ML classifier that predicts urban sound types from .wav files using a scikit-learn pipeline trained on tabular audio features, served through a Flask web app

You Say "HI" , this program classifiies it .....

Repo contains files for applying several ML algorithms to classify heart sounds

ML project classifying sound

Classifies sounds in .wav files.

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Test to learn using sound classifier ml provided my Apple using Swift

A ML pipeline for classifying urban environmental sounds using audio feature extraction and classical ML classifiers.

3 ML methods from scratch to classify urban sounds

Classifying Natural Sounds into 5 different sources using Audio Processing and ML

🚨 Siren Classifier | MATLAB ML system detects ambulance 🚑 vs. firetruck 🚒 sounds (86% accuracy). Uses multi-band filters + SVM. Real-time (<5ms). #MATLAB #AI

Urban Sound Project classifies 8,732 urban sound clips (≤4s) into 10 categories using MFCC features and a Random Forest classifier. It preprocesses audio data, trains and validates the model, and saves it for future predictions, showcasing ML in audio classification.

AI/ML project that classifies dog bark sounds into emotions (happy, sad, alert, normal) using audio feature extraction and machine learning.

Drone malfunction finder is an end-to-end system for fault-detection-from-uav-sounds, leveraging ML-based audio analysis to identify and classify drone faults.

This project uses ML to classify forest sounds and detect potential poaching activities. It analyzes 2,026 audio files across 27 classes (animal sounds, fire, axe, etc.), converting them into Mel spectrograms and using a CNN model for classification to predict whether a sound is natural or a threat and integrated w flask for an interface

Machine learning project for classifying animal sounds in environmental recordings using Librosa for audio feature extraction. Implements various ML models with Random Forest achieving best performance, providing insights on audio data preprocessing and outlier handling.

An interactive web app that uses audio data from public APIs or user uploads to detect and classify urban sounds (e.g., traffic, construction, birds) with a fine-tuned ML model. Integrate real-time mapping to visualize noise pollution hotspots in cities, pulling geolocation data for dynamic heatmaps.

Employing machine learning to the sensors and signal data is making the devices smarter than ever. Get started with ML and Azure. Over the past few years, Deep Neural Networks have provided us the best results on a variety of problems, such as pattern recognition, computer vision, and Speech recognition and image classification. Employing Machine Learning to the sensors and signal data is making the devices smarter than ever and is going to be a breakthrough in the field of IoT. Whether you are using sounds, vibrations, images, electrical signals or accelerometer or other kinds of sensor data, you can build richer analytics by teaching a machine to detect and classify events happening in real-time, at the edge, using an inexpensive micro controller for processing - even with noisy, high variation data.

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Classify urban sounds

A machine learning pipeline predicting the recording location of an audio segment.

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Sound Classification Machine Learning Based on It's Decibel with Arduino UNO

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Real-time sound classifier for clap, whistle, and unknown sounds with Python and ML.