mjhydri

1D-StateSpace

This repository contains the implementation of an efficient joint beat, downbeat, tempo, and meter tracking system using a compact 1D probabilistic state space and a jump-back reward technique. ICASSP 2022.

BeatNet

BeatNet is state-of-the-art (Real-Time) and Offline joint music beat, downbeat, tempo, and meter tracking system using CRNN and particle filtering. (ISMIR 2021's paper implementation).

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

lhvqt

Frontend filterbank learning module with HVQT initialization capabilities.

online-music-structure-segmentation

Singing-Vocal-Beat-Tracking

This repo contains the source code of the first deep learning-base singing voice beat tracking system. It leverages WavLM and DistilHuBERT pre-trained speech models to create vocal embeddings and trains linear multi-head self-attention layers on top of them to extract vocal beat activations. Then, it uses HMM decoder to infer signing beats and tempo.

sparse-analytic-filters

Code for the paper "Learning Sparse Analytic Filters for Piano Transcription".

torchaudio-augmentations

Audio transformations library for PyTorch

transformer-in-transformer

Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

mjhydri/BeatNet

BeatNet is state-of-the-art (Real-Time) and Offline joint music beat, downbeat, tempo, and meter tracking system using CRNN and particle filtering. (ISMIR 2021's paper implementation).

mjhydri/1D-StateSpace

This repository contains the implementation of an efficient joint beat, downbeat, tempo, and meter tracking system using a compact 1D probabilistic state space and a jump-back reward technique. ICASSP 2022.

mjhydri/Singing-Vocal-Beat-Tracking

This repo contains the source code of the first deep learning-base singing voice beat tracking system. It leverages WavLM and DistilHuBERT pre-trained speech models to create vocal embeddings and trains linear multi-head self-attention layers on top of them to extract vocal beat activations. Then, it uses HMM decoder to infer signing beats and tempo.

mjhydri/online-music-structure-segmentation

mjhydri/fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

mjhydri/lhvqt

Frontend filterbank learning module with HVQT initialization capabilities.

mjhydri/sparse-analytic-filters

Code for the paper "Learning Sparse Analytic Filters for Piano Transcription".

mjhydri/torchaudio-augmentations

Audio transformations library for PyTorch

mjhydri/transformer-in-transformer

Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch

mjhydri/transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.