rupakvignesh
Machine Learning and Pattern Recognition for Speech and Music Signal Processing.
United States
Pinned Repositories
JUCE-Vibrato-Plugin-MUSI8903
Assignment 4
mir_eval
Evaluation functions for music/audio information retrieval/signal processing algorithms.
ACA-Python
Python Code accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnlysis.org) by Alexander Lerch
Lyrics-to-Audio-Alignment
Aligns text (lyrics) with monophonic singing voice (audio). The algorithm uses structural segmentation to segment the audio into structures and then uses hidden markov models to obtain alignment within segments. The final alignment is concatenation of time stamps of lyrics within the segments for each song.
MUSI6106
Audio Software Engineering Course Repo
Singing-Voice-Detection
Term Project at GTCMT exploring phase based features for Singing Voice Detection with Neural Networks
Singing-Voice-Separation
A Modular Deep Neural Network framework for Singing Voice Separation.
Sinusoidal-Modelling
A Virtual Software Technology (VST) plugin that allow users to sculpt sounds based on sinusoidal models.
rupakvignesh's Repositories
rupakvignesh/Lyrics-to-Audio-Alignment
Aligns text (lyrics) with monophonic singing voice (audio). The algorithm uses structural segmentation to segment the audio into structures and then uses hidden markov models to obtain alignment within segments. The final alignment is concatenation of time stamps of lyrics within the segments for each song.
rupakvignesh/Singing-Voice-Detection
Term Project at GTCMT exploring phase based features for Singing Voice Detection with Neural Networks
rupakvignesh/Singing-Voice-Separation
A Modular Deep Neural Network framework for Singing Voice Separation.
rupakvignesh/MUSI6106
Audio Software Engineering Course Repo
rupakvignesh/Sinusoidal-Modelling
A Virtual Software Technology (VST) plugin that allow users to sculpt sounds based on sinusoidal models.
rupakvignesh/ACA-Python
Python Code accompanying the book "An Introduction to Audio Content Analysis" (www.AudioContentAnlysis.org) by Alexander Lerch