sound-recognition

Sound recognition involving a pre-trained neural network on an embedded STM32 board

🎵 🎶 ACR Cloud SDK For flutter

Building a Sound Classification iOS Application using AI

A neural network lib in C++20 optimized for CPU. Create, train and use a neural network in less than 10 lines of codes.

Quranic sound recognizer to detect any wrong recitation

🔉 A Sound Detection System for the Deaf and Hard of Hearing using On-Device Machine Learning

Educational Vue application that captures audio and predicts piano chords.

This project leverages Convolutional Neural Networks (CNNs) to perform real-time audio classification in rainforest environments, detecting sounds such as chainsaws, truck engines, and storms. Audio data, sourced from UrbanSound8K and rainforest recordings, is preprocessed into spectrograms using Librosa, while synthetic soundscapes are generated w

Query-by-humming system: a framework that assumes a hummed fragment of song in real time as an input parameter for a search system and gets the name of the full original version.

Replicating published research on sound classification using two-streamed CNN. a personal repository for the University of Bristol Applied Deep Learning unit (COMSM0018) project.

🔈Process sounds easy on python

Conversation assistance and local sound detection for users with hearing difficulties.

ROS2-based audio node enabling multi-language text-to-speech, audio recording, and real-time sound classification. Designed for robotics and infotainment use cases, featuring service-based architecture and support for custom-trained audio models.

Course project - Embedded Systems 2019 IIT Delhi

A sub-project of Mergen for practicing Audio Processing / Sound Recognition. Like MyCV, the Python codes shall be translated to C++ after reaching stability.

Yondulib is a Unity plugin that allows you to use sounds detected by the computer's microphone as input in videogames.

AI-Powered Environmental Monitoring System for detecting deforestation, poaching, and environmental hazards

CNIT 581-ATR Fall 2017 – Smart Cane Team: Wonse Jo and Shyam Sundar Kannan