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Found 8 papers, 8 papers with code
Differentiable All-pole Filters for Time-varying Audio Systems
Infinite impulse response filters are an essential building block of many time-varying audio systems, such as audio effects and synthesisers.
Zero-Shot Duet Singing Voices Separation with Diffusion Models
In this paper, we examine this problem in the context of duet singing voices separation, and propose a method to enforce the coherency of singer identity by splitting the mixture into overlapping segments and performing posterior sampling in an auto-regressive manner, conditioning on the previous segment.
TorchAudio 2.1: Advancing speech recognition, self-supervised learning, and audio processing components for PyTorch
TorchAudio is an open-source audio and speech processing library built for PyTorch.
Singing Voice Synthesis Using Differentiable LPC and Glottal-Flow-Inspired Wavetables
This paper introduces GlOttal-flow LPC Filter (GOLF), a novel method for singing voice synthesis (SVS) that exploits the physical characteristics of the human voice using differentiable digital signal processing.
Conditioning and Sampling in Variational Diffusion Models for Speech Super-Resolution
Moreover, by coupling the proposed sampling method with an unconditional DM, i. e., a DM with no auxiliary inputs to its noise predictor, we can generalize it to a wide range of SR setups.
Danna-Sep: Unite to separate them all
Deep learning-based music source separation has gained a lot of interest in the last decades.
Music Demixing Challenge 2021
The main differences compared with the past challenges are 1) the competition is designed to more easily allow machine learning practitioners from other disciplines to participate, 2) evaluation is done on a hidden test set created by music professionals dedicated exclusively to the challenge to assure the transparency of the challenge, i. e., the test set is not accessible from anyone except the challenge organizers, and 3) the dataset provides a wider range of music genres and involved a greater number of mixing engineers.
Multi-layered Cepstrum for Instantaneous Frequency Estimation
We propose the multi-layered cepstrum (MLC) method to estimate multiple fundamental frequencies (MF0) of a signal under challenging contamination such as high-pass filter noise.
