title: Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ° ÑÐ¸ÑÑÐµÐ¼Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð·Ð²ÑÐºÐ¾Ð²ÑÑ ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð² Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð³Ð»ÑÐ±Ð¾ÐºÐ¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Development of a sound signal classification system using deep neural networks
Creators: name: ÐÐµÑÑÐ¾Ð², Ð¡ÐµÑÐ³ÐµÐ¹
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: python
keras
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Ð·Ð²ÑÐºÐ¸ Ð¾ÐºÑÑÐ¶Ð°ÑÑÐµÐ¹ ÑÑÐµÐ´Ñ
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ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð°Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ
ÑÐ¿ÐµÐºÑÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð°
convolutional neural network
deep neural networks
environmental sounds
sound signals
sound
event classification
spectrogram

description: Ð Ð°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ¸ÑÑÐµÐ¼Ñ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð·Ð²ÑÐºÐ¾Ð²ÑÑ ÑÐ¾Ð±ÑÑÐ¸Ð¹ Ð½Ð° Ð±Ð°Ð·Ðµ Ð³Ð»ÑÐ±Ð¾ÐºÐ¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¸ Ð¿ÐµÑÐµÐ½Ð¾ÑÐ° Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ. Ð Ð¿ÐµÑÐ²Ð¾Ð¹ Ð³Ð»Ð°Ð²Ðµ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐ¿Ð¾ÑÐ¾Ð±Ð¾Ð² Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð·Ð²ÑÐºÐ¾Ð²Ð¾Ð³Ð¾ ÑÐ¸Ð³Ð½Ð°Ð»Ð°, Ð° ÑÐ°ÐºÐ¶Ðµ ÐºÐ»ÑÑÐµÐ²ÑÑ Ð¾ÑÐ¾Ð±ÐµÐ½Ð½Ð¾ÑÑÐµÐ¹ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð·Ð°Ð´Ð°ÑÐ¸ ÐºÐ»Ð°ÑÑÐ¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¸ Ð·Ð²ÑÐºÐ¾Ð²ÑÑ ÑÐ¾Ð±ÑÑÐ¸Ð¹. ÐÑÐ¾ÑÐ°Ñ Ð³Ð»Ð°Ð²Ð° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ ÑÐ¸ÑÑÐµÐ¼Ñ Ð´Ð»Ñ ÑÐµÑÐµÐ½Ð¸Ñ Ð¿Ð¾ÑÑÐ°Ð²Ð»ÐµÐ½Ð½Ð¾Ð¹ Ð·Ð°Ð´Ð°ÑÐ¸. Ð ÑÑÐµÑÑÐµÐ¹ Ð³Ð»Ð°Ð²Ðµ Ð¾ÑÑÑÐµÑÑÐ²Ð»ÑÐµÑÑÑ Ð²ÑÐ±Ð¾Ñ ÑÐ¾Ð¾ÑÐ²ÐµÑÑÑÐ²ÑÑÑÐ¸Ñ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¹ Ð¸ Ð¸Ð½ÑÑÑÑÐ¼ÐµÐ½ÑÐ¾Ð², Ð° ÑÐ°ÐºÐ¶Ðµ Ð´Ð°ÐµÑÑÑ Ð¾Ð¿Ð¸ÑÐ°Ð½Ð¸Ðµ Ð¿Ð¾Ð»Ð½Ð¾Ð³Ð¾ ÑÐ¸ÐºÐ»Ð° ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ¸ÑÑÐµÐ¼Ñ, Ð½Ð°ÑÐ¸Ð½Ð°Ñ Ñ Ð¿Ð¾Ð´Ð³Ð¾ÑÐ¾Ð²ÐºÐ¸ ÑÑÐµÐ½Ð¸ÑÐ¾Ð²Ð¾ÑÐ½ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð·Ð°ÐºÐ°Ð½ÑÐ¸Ð²Ð°Ñ ÑÐ¾ÑÑÐ°Ð½ÐµÐ½Ð¸ÐµÐ¼ Ð¸ÑÐ¾Ð³Ð¾Ð²ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² (Ð²ÐµÑÐ¾Ð², Ð¸ÑÑÐ¾ÑÐ¸Ð¸ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¸ Ñ.Ð´.) Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸. Ð ÑÐµÑÐ²ÐµÑÑÐ¾Ð¹ Ð³Ð»Ð°Ð²Ðµ Ð¿ÑÐ¾Ð²Ð¾Ð´Ð¸ÑÑÑ ÑÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¸ Ð¾ÑÐµÐ½ÐºÐ° Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð½ÑÑ Ð¼Ð¾Ð´ÐµÐ»ÐµÐ¹.
description: This study is devoted to the implementation of a sound event classification system based on a deep neural network using the technology of transfer learning. In the first chapter, the analysis of ways to represent an audio signal and the key features of building neural networks to solve the problem of classifying sound events is conducted. The second chapter is devoted to the development of a system model for solving this task. In the third chapter, the selection of appropriate technologies and tools, along with a description of the full implementation cycle of the system, from preparation of training data to preservation of the final parameters (weights, training history, etc.) of the neural network is provided. Testing and evaluation of the constructed models are performed in the fourth chapter.