AUDIO-MTHRFCKR

FPGA based USB 2.0 high speed audio interface featuring multiple optical ADAT inputs and outputs

AudioLDM training, finetuning, evaluation and inference.

USB Audio DAC using inexpensive STM32F411 / 401 "Black Pill" and PCM5102A modules

Code for Vision-Infused Deep Audio Inpainting (ICCV 2019)

the dataset used in the paper https://drive.google.com/file/d/0B4bIMgQlCAuqdGVRbVNNbzJfeUU/view

Lyrics-to-audio-alignement system. Based on Machine Learning Algorithms: Hidden Markov Models with Viterbi forced alignment. The alignment is explicitly aware of durations of musical notes. The phonetic model are classified with MLP Deep Neural Network.

Control mechanisms to the U-Net architecture for doing multiple source separation instruments

DALI: a large Dataset of synchronised Audio, LyrIcs and vocal notes.

A Freesound Community Sampler

Creation of an embedding space using unsupervised triplet loss and Tile2Vec that can be used for a variety of downstream tasks

Using Deep Learning to Categorize Music as Time Progresses Through Spectrogram Analysis evanoterodeepmusicgenreclassification

Neural network to classify some styles of Electronic music

This is the codes repository for the paper "Emotion-Guided Music Accompaniment Generation based on VAE".

The code for the MaD TwinNet. Demo page:

Classification wrappers for 4 Deep Learning Embedded Runtimes for Music Information Retrieval, plus utilities to convert a TensorFlow Model

Code for "Deep Learning Based EDM Subgenre Classification using Mel-Spectrogram and Tempogram Features" arXiv:2110.08862, 2021.

Repository for the IEEE/ACM TASLP 2023 Paper "Zero-Note Samba".

Removing background noise in a sound file

Classify audio into genres

Score following algorithms component for EnsembleVR. Uses Hierarchical Hidden Markov Models and Kalman Filtering to process audio and generate accompaniment in real time

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

A Machine Learning Approach of Emotional Model

Master thesis project - a hybrid Neural Network-Decision Tree system and dataset for classical music form recognition and analysis.

A convolutional neural network trained to classify emotions in singing voices.

Audio Conductor is a tool that enhances the usability of audio features (AudioClip/AudioSource) in Unity, providing greater convenience in managing and controlling audio assets.

Experimenting with Python and librosa to do Audio Event Detection

MIDI audio to musical tablature converter.

A Multimodal Audio Sheet Music Dataset

One-click launcher for Audiocraft MusicGen + AudioGen Gradio Web UI