Environmental audio scene and sound event recognition for autonomous surveillance: A survey and comparative studies
S Chandrakala, SL Jayalakshmi - ACM Computing Surveys (CSUR), 2019 - dl.acm.org
Monitoring of human and social activities is becoming increasingly pervasive in our living
environment for public security and safety applications. The recognition of suspicious events …
environment for public security and safety applications. The recognition of suspicious events …
The internet of audio things: State of the art, vision, and challenges
The Internet of Audio Things (IoAuT) is an emerging research field positioned at the
intersection of the Internet of Things, sound and music computing, artificial intelligence, and …
intersection of the Internet of Things, sound and music computing, artificial intelligence, and …
Detection and classification of acoustic scenes and events: Outcome of the DCASE 2016 challenge
Public evaluation campaigns and datasets promote active development in target research
areas, allowing direct comparison of algorithms. The second edition of the challenge on …
areas, allowing direct comparison of algorithms. The second edition of the challenge on …
Classification of lung sounds with CNN model using parallel pooling structure
The recognition of various lung sounds recorded using electronic stethoscopes plays a
significant role in the early diagnoses of respiratory diseases. To increase the accuracy of …
significant role in the early diagnoses of respiratory diseases. To increase the accuracy of …
ECG signal classification for the detection of cardiac arrhythmias using a convolutional recurrent neural network
Objective: The electrocardiogram (ECG) provides an effective, non-invasive approach for
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …
clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the …
QTI submission to DCASE 2021: Residual normalization for device-imbalanced acoustic scene classification with efficient design
This technical report describes the details of our TASK1A submission of the DCASE2021
challenge. The goal of the task is to design an audio scene classification system for device …
challenge. The goal of the task is to design an audio scene classification system for device …
Exploring deep spectrum representations via attention-based recurrent and convolutional neural networks for speech emotion recognition
The automatic detection of an emotional state from human speech, which plays a crucial role
in the area of human-machine interaction, has consistently been shown to be a difficult task …
in the area of human-machine interaction, has consistently been shown to be a difficult task …
Spying with your robot vacuum cleaner: eavesdropping via lidar sensors
Eavesdropping on private conversations is one of the most common yet detrimental threats
to privacy. A number of recent works have explored side-channels on smart devices for …
to privacy. A number of recent works have explored side-channels on smart devices for …
[PDF][PDF] Convolutional Neural Networks with Binaural Representations and Background Subtraction for Acoustic Scene Classification.
In this paper, we demonstrate how we applied convolutional neural network for DCASE
2017 task 1, acoustic scene classification. We propose a variety of preprocessing methods …
2017 task 1, acoustic scene classification. We propose a variety of preprocessing methods …
Deep scalogram representations for acoustic scene classification
Spectrogram representations of acoustic scenes have achieved competitive performance for
acoustic scene classification. Yet, the spectrogram alone does not take into account a …
acoustic scene classification. Yet, the spectrogram alone does not take into account a …