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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.
This repository contain the code of the main part of my master thesis degree at Politecnico di Torino in Data science & Engineering
In this repository, the wavLM model is used for quality and poor quality data for speaker verification task, and the PyCM library is used for evaluation.
This repo contains code used in the paper "Characterizing the temporal dynamics of universal speech representations for generalizable deepfake detection"
CryCeleb2023 experiments