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Speech
Speech and MusiC CIassification
Based on Feed—Forward ANN
Major:Software and Theory of Computer Name:LiU Q5aohui
Supervisor:Associate Professor Ou Guiwen
Abstract
In thiS paper,the approaches,which based on Feed—Forward Artificial Neural Networks,to speech and music classification in continuous audio are deeply studied.The work consists of two aspects mainly:1.What kind of audio feature vectors can be the basi S of classifieation and which one is the best:2.The creating,training,simulating of Feed—Forward Artificial Neural Networks,and the realizing of speech and music
classification aecording the audi0 feature vectors.
The main contents of thiS paper including:
1.The corpus was recorded from the radio on the Internet.It consists of three audio documents:pure speech、pure music、speech+music,with 225s each one.
2.The effect of every parameter on the classification are studied.The result of experiments shows that MFCC performed the best.
3.The features of Feed—Forward Artificial Neural Networks are introduced.How to creat,train and simulate the Feed~Forward Artificial Neural Networks and to classify the audio documents in MATLAB 6.5 are descr ibed.
4.Training the network using the Levenberg—Marquardt Algorithm is purposed.A val idat J on set is established in order to indicate the end point of training and to avoid endless training which would make the
II
network
network adap L the training set excess and has weak abil ity to extend
to other data.
5.Part]y codes of the MATI.AB funct ions are given for referenee. 6.Data and charts are g iven in this paper.The advantage and
disadvantage o[。the methods mentioned in this paper is analyzed.
The resu]t shows:to speech,music,speech+music documents, Feed—Forward Artificial Neural Networks perfarm terrific,the average classjfi cation accuracy iS up to 94%.
Key words:Speech:Music:Classi Fication:Feed—Forward Artj ficial Neural Network
IU
基于前馈型人:I一神经网络的语音;fl_】音乐识别第1章引
基于前馈型人:I一神经网络的语音;fl_】音乐识别
第1章引 言
1.1研究背景
随着电台
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