Deep neural networks for audio scene recognition

التفاصيل البيبلوغرافية
العنوان: Deep neural networks for audio scene recognition
المؤلفون: Petetin, Yohan, Laroche, Cyrille, Mayoue, Aurelien
المساهمون: Laboratoire d'analyse des données et d'intelligence des systèmes (CEA, LIST) (LADIS (CEA, LIST)), Département Métrologie Instrumentation & Information (CEA, LIST) (DM2I (CEA, LIST)), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay
المصدر: 2015 23rd European Signal Processing Conference (EUSIPCO)
https://hal.science/hal-01888746
2015 23rd European Signal Processing Conference (EUSIPCO), Aug 2015, Nice, France. pp.7362358, ⟨10.1109/EUSIPCO.2015.7362358⟩
بيانات النشر: HAL CCSD
IEEE
سنة النشر: 2015
مصطلحات موضوعية: Deep neural network, neural network, deep learnin, audio scene recognition, audio signal processing, belief networks, machine learning, artificial intelligence, neural nets, signal classification, Training, Mel frequency cepstral coefficient, computational auditory scene recognition problem, artificial neural networks, ANN, training procedures, CASR problem, deep belief networks, Index Terms-Deep neural networks, deep beliefs net- works, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
جغرافية الموضوع: Nice, France
Time: Nice, France
الوصف: International audience ; These last years, artificial neural networks (ANN) have known a renewed interest since efficient training procedures have emerged to learn the so called deep neural networks (DNN), i.e. ANN with at least two hidden layers. In the same time, the computational auditory scene recognition (CASR) problem which consists in estimating the environment around a device from the received audio signal has been investigated. Most of works which deal with the CASR problem have tried to ind well-adapted features for this problem. However, these features are generally combined with a classical classi-ier. In this paper, we introduce DNN in the CASR ield and we show that such networks can provide promising results and perform better than standard classiiers when the same features are used.
نوع الوثيقة: conference object
اللغة: English
DOI: 10.1109/EUSIPCO.2015.7362358
الاتاحة: https://hal.science/hal-01888746
https://hal.science/hal-01888746v1/document
https://hal.science/hal-01888746v1/file/article_YohanPetetin_Deepneuralnetworks.pdf
https://doi.org/10.1109/EUSIPCO.2015.7362358
Rights: info:eu-repo/semantics/OpenAccess
رقم الانضمام: edsbas.A718EE46
قاعدة البيانات: BASE
الوصف
DOI:10.1109/EUSIPCO.2015.7362358