• Corpus ID: 233423634

DASEE A Synthetic Database of Domestic Acoustic Scenes and Events in Dementia Patients Environment

  title={DASEE A Synthetic Database of Domestic Acoustic Scenes and Events in Dementia Patients Environment},
  author={Abigail Copiaco and Christian Ritz and Stefano Fasciani and Nidhal Abdulaziz},
Access to informative databases is a crucial part of notable research developments. In the field of domestic audio classification there have been significant advances in recent years. Although several audio databases exist, these can be limited in terms of the amount of information they provide, such as the exact location of the sound sources, and the associated noise levels. In this work, we detail our approach on generating an unbiased synthetic domestic audio database, consisting of sound… 
1 Citations

Figures and Tables from this paper

Evaluating Spectral Magnitude Representation and Spectral Energy for Audio-based Activity Detection

Extensive experimental results on a public database for detection of daily activities in a home environment, show that the overall highest recognition accuracy is achieved by the STFT magnitude representations.



The SINS Database for Detection of Daily Activities in a Home Environment Using an Acoustic Sensor Network

A database recorded in one living home, over a period of one week, containing activities being performed in a spontaneous manner, which make use of an acoustic sensor network, and are recorded as a continuous stream is introduced.

Sound Event Detection in Domestic Environments with Weakly Labeled Data and Soundscape Synthesis

The paper introduces Domestic Environment Sound Event Detection (DESED) dataset mixing a part of last year dataset and an additional synthetic, strongly labeled, dataset provided this year that’s described more in detail.

Deep Convolutional Neural Networks and Data Augmentation for Acoustic Event Recognition

This work introduces a convolutional neural network (CNN) with a large input field for AED that significantly outperforms state of the art methods including Bag of Audio Words (BoAW) and classical CNNs, achieving a 16% absolute improvement.

Audio tagging with noisy labels and minimal supervision

This paper presents the task setup, the FSDKaggle2019 dataset prepared for this scientific evaluation, and a baseline system consisting of a convolutional neural network.

FSD50K: An Open Dataset of Human-Labeled Sound Events

FSD50K is introduced, an open dataset containing over 51 k audio clips totalling over 100 h of audio manually labeled using 200 classes drawn from the AudioSet Ontology, to provide an alternative benchmark dataset and thus foster SER research.

Acoustic design guidelines for dementia care facilities

The role of noise on the ability of people with dementia to interpret and understand their surroundings is explored and examples are provided of acoustical design and management practices that contribute to increased levels of agitation and aggression among residents who have dementia.

Scalogram Neural Network Activations with Machine Learning for Domestic Multi-channel Audio Classification

This paper looks at domestic multi-channel audio classification through a comparison of various combinations of existing pre-trained Neural Network (NN) models, with Support Vector Machine (SVM) for classification.

Open-source Multi-speaker Speech Corpora for Building Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu Speech Synthesis Systems

We present free high quality multi-speaker speech corpora for Gujarati, Kannada, Malayalam, Marathi, Tamil and Telugu, which are six of the twenty two official languages of India spoken by 374

A Dataset and Taxonomy for Urban Sound Research

A taxonomy of urban sounds and a new dataset, UrbanSound, containing 27 hours of audio with 18.5 hours of annotated sound event occurrences across 10 sound classes are presented.