منابع مشابه
Environmental Sound Recognition: A Statistical Approach
Introduction Noise pollution has become an important problem in our society. Noise assessment regulations require the measurement and evaluation of noise. The basic equipment for this measurement is the noise monitoring systems (or NMS). The current generation of NMS consists of "dumb" systems that record noise level and, possibly, noise spectra, over programmed periods of time. The interpretat...
متن کاملA Robust Environmental Sound Recognition System using Frequency Domain Features
In ubiquitous environments, analysis and classification of sound plays a critical role in various acoustic-based recognition systems. This work aims to contribute towards building an automatic sound recognition system that can understand the surrounding environment by the audio information. In this paper, an acoustic signal based context awareness system is proposed for detecting sound events i...
متن کاملA Robust Environmental Sound Recognition System using BPNN and RBFNN
Abstract— In a reverberant environment, the performance of acoustic event recognition system can be bolstered by choosing appropriate feature descriptors and classifier techniques. Neural networks are by far providing stunning classification results when compared to other classifiers. This paper analyses two different neural networks and their precision when they both stumble upon same targets ...
متن کاملEnvironmental Sound Recognition Using Masked Conditional Neural Networks
Neural network based architectures used for sound recognition are usually adapted from other application domains, which may not harness sound related properties. The ConditionaL Neural Network (CLNN) is designed to consider the relational properties across frames in a temporal signal, and its extension the Masked ConditionaL Neural Network (MCLNN) embeds a filterbank behavior within the network...
متن کاملEnvironmental Sound Recognition With Time-Frequency Audio Features
The paper considers the task of recognizing environmental sounds for the understanding of a scene or context surrounding an audio sensor. A variety of features have been proposed for audio recognition, including the popular Mel-frequency cepstral coefficients (MFCCs) which describe the audio spectral shape. Environmental sounds, such as chirpings of insects and sounds of rain which are typicall...
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ژورنال
عنوان ژورنال: APSIPA Transactions on Signal and Information Processing
سال: 2014
ISSN: 2048-7703
DOI: 10.1017/atsip.2014.12