Python library for audio and music analysis

Understanding emotions from audio files using neural networks and multiple datasets.

A Machine Learning Approach of Emotional Model

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Lightweight and Interpretable ML Model for Speech Emotion Recognition and Ambiguity Resolution (trained on IEMOCAP dataset)

A music video generator based on rhythm, built with moviepy and librosa

In this project is presented a simple method to train an MLP neural network for audio signals. The trained model can be exported on a Raspberry Pi (2 or superior suggested) to classify audio signal registered with USB microphone

Python framework for Speech and Music Detection using Keras.

Music Synthesis with Python talk, originally given at PyGotham 2017.

Music genre classification model using CRNN

Image Processing, Speech Processing, Encoder Decoder, Research Paper implementation

Music genre classification from audio spectrograms using deep learning

Sound Classification using Neural Networks

Classifying English Music (.mp3) files using Music Information Retrieval (MIR), Digital/Audio Signal Processing (DIP) and Machine Learning (ML) Strategies

Artificial intelligence bot for live voice improvisation

Scene Classification using Audio in the nearby Environment.

Methods to compute various chroma audio features and audio similarity measures particularly for the task of cover song identification

Predicting various emotion in human speech signal by detecting different speech components affected by human emotion.

An open-source Python library for audio time-scale modification.

Human Emotion Understanding using multimodal dataset.

Digital Signal Processing mini project: Autotune

infinite jukebox clone using librosa

Python script utilising Librosa to log the timings of audio peaks in an MP3 file

100行代码实现简单音乐卡点

Bird's tweet classification with Deep Learning

Creating a remix of sam from game of thrones

Using machine learning for the study of music.

Text-to-Speech Synthesis by Generating Spectrograms using Generative Adversarial Network

A content-based music recommendation system, that suggests playlists made from the locally stored songs, and updates its suggestions based on the user feedback using non-stationary Bayesian reinforcement learning. Created using React and the Electron.js framework.

Bird sound identification web application