Environmental Sound Recognition using Masked Conditional Neural Networks

2018-04-08 · Fady Medhat, David Chesmore, John Robinson

Neural network based architectures used for sound recognition are usually adapted from other application domains, which may not harness sound related properties. The ConditionaL Neural Network (CLNN) is designed to consider the relational properties across frames in a temporal signal, and its extension the Masked ConditionaL Neural Network (MCLNN) embeds a filterbank behavior within the network, which enforces the network to learn in frequency bands rather than bins. Additionally, it automates the exploration of different feature combinations analogous to handcrafting the optimum combination of features for a recognition task. We applied the MCLNN to the environmental sounds of the ESC-10 dataset. The MCLNN achieved competitive accuracies compared to state-of-the-art convolutional neural networks and hand-crafted attempts.

📄 PDF Abstract BibTeX arXiv:1804.02665

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fadymedhat/MCLNN 공식 구현 tf

Masked Conditional Neural Networks for Automatic Sound Events Recognition

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Deep neural network architectures designed for application domains other than sound, especially image recognition, may not optimally harness the time-frequency representation when adapted to the sound recognition problem…

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The ConditionaL Neural Network (CLNN) exploits the nature of the temporal sequencing of the sound signal represented in a spectrogram, and its variant the Masked ConditionaL Neural Network (MCLNN) induces the network to …

Classification Environmental Sound Classification General Classification Sound Classification

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Audio Classification Classification General Classification

EnCodecMAE: Leveraging neural codecs for universal audio representation learning

2023-09-14 · Leonardo Pepino, Pablo Riera, Luciana Ferrer

The goal of universal audio representation learning is to obtain foundational models that can be used for a variety of downstream tasks involving speech, music and environmental sounds. To approach this problem, methods …

Automatic Speech Recognition Automatic Speech Recognition (ASR)Representation Learning Self-Supervised Learning+2