1 简介

为了提高语音情感识别系统的识别率研究分析了一种支持向量机核函数参数的优选方法首先给出影响支持向量机核参数的因素其次依据这些因素结合 Fisher 准则和最大熵原理对支持向量机的核参数进行优选最后用优选参数对基于情感语音数据库进行 5 种情感的识别测试测试结果表明 Fisher 准则和最大熵方法相融合能够有效地提高语音情感识别准确率

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_ide

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_fish_02

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_最大熵_03

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_支持向量机_04

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_最大熵_05

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_参考文献_06

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_fish_07

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_支持向量机_08

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_支持向量机_09

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_参考文献_10

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_参考文献_11

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_最大熵_12

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_最大熵_13


2 部分代码

function varargout = main(varargin)
% MAIN MATLAB code for main.fig
%     MAIN, by itself, creates a new MAIN or raises the existing
%     singleton*.
%
%     H = MAIN returns the handle to a new MAIN or the handle to
%     the existing singleton*.
%
%     MAIN('CALLBACK',hObject,eventData,handles,...) calls the local
%     function named CALLBACK in MAIN.M with the given input arguments.
%
%     MAIN('Property','Value',...) creates a new MAIN or raises the
%     existing singleton*. Starting from the left, property value pairs are
%     applied to the GUI before main_OpeningFcn gets called. An
%     unrecognized property name or invalid value makes property application
%     stop. All inputs are passed to main_OpeningFcn via varargin.
%
%     *See GUI Options on GUIDE's Tools menu. Choose "GUI allows only one
%     instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES
% Edit the above text to modify the response to help main
% Last Modified by GUIDE v2.5 12-Apr-2020 14:35:36
% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
'gui_Singleton',  gui_Singleton, ...
'gui_OpeningFcn', @main_OpeningFcn, ...
'gui_OutputFcn',  @main_OutputFcn, ...
'gui_LayoutFcn', [] , ...
'gui_Callback',   []);
if nargin && ischar(varargin{1})
gui_State.gui_Callback = str2func(varargin{1});
end
if nargout
[varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT
% --- Executes just before main is made visible.
function main_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject   handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles   structure with handles and user data (see GUIDATA)
% varargin   command line arguments to main (see VARARGIN)
% Choose default command line output for main
handles.output = hObject;
% Update handles structure
guidata(hObject, handles);
% UIWAIT makes main wait for user response (see UIRESUME)
% uiwait(handles.figure1);
ha=axes('units','normalized','pos',[0 0 1 1]);
uistack(ha,'down');
ii=imread('背景.jpg');
image(ii);
colormap gray
set(ha,'handlevisibility','off','visible','on');
% --- Outputs from this function are returned to the command line.
function varargout = main_OutputFcn(hObject, eventdata, handles)
% varargout cell array for returning output args (see VARARGOUT);
% hObject   handle to figure
% eventdata reserved - to be defined in a future version of MATLAB
% handles   structure with handles and user data (see GUIDATA)
% Get default command line output from handles structure
varargout{1} = handles.output;
% --- Executes on button press in pushbutton1.
function pushbutton1_Callback(hObject, eventdata, handles)
% hObject   handle to pushbutton1 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles   structure with handles and user data (see GUIDATA)
close
gui
% --- Executes on button press in pushbutton2.
function pushbutton2_Callback(hObject, eventdata, handles)
% hObject   handle to pushbutton2 (see GCBO)
% eventdata reserved - to be defined in a future version of MATLAB
% handles   structure with handles and user data (see GUIDATA)
close


3 仿真结果

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_支持向量机_14

4 参考文献

[1]潘涛[1], 王胜利[1]. 支持向量机在语音情感识别中的应用[J]. 电子技术与软件工程, 2019(6):1.

【语音识别】基于支持向量机算法svm实现情感识别系统matlab代码_ide_15