Proceedings Article10.1109/SCCC.2016.7836034
Using spectrogram to detect North Atlantic right whale calls from audio recordings
Guilherme Kamizake de Freitas,Yandre M. G. Costa,Rafael de Lima Aguiar +2 more
- 01 Oct 2016
pp 1-6
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TL;DR: This work describes a number of experiments aiming to assess the use of spectrogram to detect North Atlantic right whale calls, taking into account different ranges of variation of the amplitude looking for the best setting to highlight the textural content of the spectrograms.
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Abstract: This work describes a number of experiments aiming to assess the use of spectrogram to detect North Atlantic right whale calls. For this purpose, spectrograms are generated from the audio signal and then, Local Binary Pattern textural features are taken from the spectrogram images, once texture is the main visual content found in this kind of image. Following, these features are sent to a Support Vector Machine classifier. The experiments were carried out taking into account different ranges of variation of the amplitude looking for the best setting to highlight the textural content of the spectrograms. In addition, some different values of SVM classifier parameters were evaluated. The best accuracy rate obtained is about 85.48%.
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Citations
Ensemble of convolutional neural networks to improve animal audio classification
Loris Nanni,Yandre M. G. Costa,Rafael de Lima Aguiar,Rafael B. Mangolin,Sheryl Brahnam,Carlos N. Silla +5 more
TL;DR: An ensemble for automated audio classification that fuses different types of features extracted from audio files that produces better classification accuracy than other state-of-the-art approaches without ad hoc parameter optimization is presented.
Identification of Infants’ Cry Motivation Using Spectrograms
Gustavo Zanoni Felipe,Rafael L. Aguiat,Yandre M. G. Costa,Carlos N. Silla,Sheryl Brahnam,Loris Nanni,Shannon McMurtrey +6 more
- 05 Jun 2019
TL;DR: This paper aims to automatically identify whether an infant’s cry is motivated by the feeling of pain using a novel dataset, which is carefully designed, curated and made available to the research community for the development of classifiers in this field of research.
38
On the Importance of Passive Acoustic Monitoring Filters
TL;DR: In this work, PAM filters are defined as the creation of the experimental protocols according to the dates and locations of the recordings, aiming to avoid the use of the same individuals, noise patterns, and recording devices in both the training and test sets.
A Brazilian Speech Database
Marco Aurelio Deoldoto Paulino,Yandre M. G. Costa,Alceu de Souza Britto Junior,Alisson Renan Svaigen,Linnyer Beatrys Ruiz Aylon,Luiz S. Oliveira +5 more
- 01 Nov 2018
TL;DR: This work introduces a Brazilian Speech Database (BrSD), a novel dataset freely available created to support the development of speech-based recognition tasks, and describes experiments accomplished exploring its different possibilities of classification tasks, i.e., age group and gender classification.
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•Posted Content
Automatic Chronic Degenerative Diseases Identification Using Enteric Nervous System Images
Gustavo Zanoni Felipe,Jacqueline Nelisis Zanoni,Camila Caviquioli Sehaber-Sierakowski,Gleison Daion Piovezana Bossolani,Sara Raquel Garcia de Souza,Franklin César Flores,Luiz S. Oliveira,Rodolfo Miranda Pereira,Yandre M. G. Costa +8 more
TL;DR: The proposed approach can distinguish healthy cells from the sick ones with a recognition rate of 89.30% (Rheumatoid Arthritis), 98.45% (Cancer), and 95.13% (Diabetes Mellitus) and is supported by statistical analysis.
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