This paper addresses the task of recognizing environmental sounds using the AudioSet data set. Specifically, features were extracted by spectrogram ...
This paper addresses the task of recognizing environmental sounds using the AudioSet data set. Specifically, features were extracted by spectrogram conversion.
It would be of great convenience to live in an environment that can change automatically based on its "auditory sense". In this work we propose a novel ...
Dec 12, 2023 · In this study, we focus on a long-short-term memory convolutional neural network (LSTM-CNN) to extract time and / or frequency-dependent features of the sound ...
Environmental Sound Event Recognition (ESER) has significant potential for enhancing how we interpret and interact with sound data from various environments.
Missing: Recognition | Show results with:Recognition
This paper proposes a model which uses Convolutional Neural Networks (CNN) for classification of sound based on the spectrograms obtained for different sound ...
Environmental sound detection described as (iii) is conducted based on the convolutional neural network (Mel-CNN) using each Mel spectrogram as input.
Apr 22, 2022 · This paper proposes a resource adaptive convolutional neural network (RACNN). RACNN uses a novel resource adaptive convolutional (RAC) module.
Convolutional neural networks (CNNs) have become a potent tool for sound recognition, producing cutting-edge outcomes in a variety of challenges. In this study, ...
Jan 15, 2021 · In this study, an effective approach of spectral images based on environmental sound classification using Convolutional Neural Networks (CNN) with meaningful ...
Missing: LSTM. | Show results with:LSTM.