Audio Signal Processing
17 papers with code • 0 benchmarks • 1 datasets
This is a general task that covers transforming audio inputs into audio outputs, not limited to existing PaperWithCode categories of Source Separation, Denoising, Classification, Recognition, etc.
Benchmarks
These leaderboards are used to track progress in Audio Signal Processing
Most implemented papers
Differentiable Signal Processing With Black-Box Audio Effects
We present a data-driven approach to automate audio signal processing by incorporating stateful third-party, audio effects as layers within a deep neural network.
Unifying Probabilistic Models for Time-Frequency Analysis
In audio signal processing, probabilistic time-frequency models have many benefits over their non-probabilistic counterparts.
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
A typical audio signal processing pipeline includes multiple disjoint analysis stages, including calculation of a time-frequency representation followed by spectrogram-based feature analysis.
Deep Learning for Audio Signal Processing
Given the recent surge in developments of deep learning, this article provides a review of the state-of-the-art deep learning techniques for audio signal processing.
SignalTrain: Profiling Audio Compressors with Deep Neural Networks
In this work we present a data-driven approach for predicting the behavior of (i. e., profiling) a given non-linear audio signal processing effect (henceforth "audio effect").
Exploring Quality and Generalizability in Parameterized Neural Audio Effects
Deep neural networks have shown promise for music audio signal processing applications, often surpassing prior approaches, particularly as end-to-end models in the waveform domain.
wav2shape: Hearing the Shape of a Drum Machine
Disentangling and recovering physical attributes, such as shape and material, from a few waveform examples is a challenging inverse problem in audio signal processing, with numerous applications in musical acoustics as well as structural engineering.
Upsampling artifacts in neural audio synthesis
We then compare different upsampling layers, showing that nearest neighbor upsamplers can be an alternative to the problematic (but state-of-the-art) transposed and subpixel convolutions which are prone to introduce tonal artifacts.
Melon Playlist Dataset: a public dataset for audio-based playlist generation and music tagging
We present Melon Playlist Dataset, a public dataset of mel-spectrograms for 649, 091tracks and 148, 826 associated playlists annotated by 30, 652 different tags.
L3DAS21 Challenge: Machine Learning for 3D Audio Signal Processing
The L3DAS21 Challenge is aimed at encouraging and fostering collaborative research on machine learning for 3D audio signal processing, with particular focus on 3D speech enhancement (SE) and 3D sound localization and detection (SELD).