A New Approach for Automatic Audio Segmentation , And Reconstruction
نویسندگان
چکیده
Automatic Audio Segmentation aims at extracting information about type of audio i.e. silence, clean speech or speech with noise, music etc. The aim of this thesis is to find and extract different features of audio, segment the audio and combine them to form single type of audio. In this work, the audio signal is initially decomposed into non-overlapping frames. Then these frames are decomposed into a set of band-limited functions known as Intrinsic Mode Functions (IMF) using Empirical Mode Decomposition (EMD). Temporal and Spectral features then extracted from these IMFs and thereafter classification is done using k-nearest neighbour (kNN) classifier. Depending upon classification accuracy of the features the segmentation is done using k-means clustering algorithm. Then the segments were combined to form new audio signal. KEYWORDS--Intrinsic Mode Function, Empirical Mode Decomposition, Spectral And Temporal Features, k-NN classifier, K Means Clustering.
منابع مشابه
A multi-scale convolutional neural network for automatic cloud and cloud shadow detection from Gaofen-1 images
The reconstruction of the information contaminated by cloud and cloud shadow is an important step in pre-processing of high-resolution satellite images. The cloud and cloud shadow automatic segmentation could be the first step in the process of reconstructing the information contaminated by cloud and cloud shadow. This stage is a remarkable challenge due to the relatively inefficient performanc...
متن کاملAn Improved Automatic EEG Signal Segmentation Method based on Generalized Likelihood Ratio
It is often needed to label electroencephalogram (EEG) signals by segments of similar characteristics that are particularly meaningful to clinicians and for assessment by neurophysiologists. Within each segment, the signals are considered statistically stationary, usually with similar characteristics such as amplitude and/or frequency. In order to detect the segments boundaries of a signal, we ...
متن کاملReducing Light Change Effects in Automatic Road Detection
Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...
متن کاملReducing Light Change Effects in Automatic Road Detection
Automatic road extraction from aerial images can be very helpful in traffic control and vehicle guidance systems. Most of the road detection approaches are based on image segmentation algorithms. Color-based segmentation is very sensitive to light changes and consequently the change of weather condition affects the recognition rate of road detection systems. In order to reduce the light change ...
متن کاملA hierarchical Convolutional Neural Network for Segmentation of Stroke Lesion in 3D Brain MRI
Introduction: Brain tumors such as glioma are among the most aggressive lesions, which result in a very short life expectancy in patients. Image segmentation is highly essential in medical image analysis with applications, particularly in clinical practices to treat brain tumors. Accurate segmentation of magnetic resonance data is crucial for diagnostic purposes, planning surgical treatments, a...
متن کامل