Crossbreed Wavelet decomposition for speech emotion detection using HMM in MATLAB - open to bidding

Five types of emotions were analyzed and compared in previous paper. The proposed method was completely simulated on PC; the results demonstrate that significant advances have been achieved in this area. The wavelet transform and improved HMM make our speech emotion recognition system robust. The combination of wavelet transforms and HMM as a solid model that can reduce error rates.

Table 1. The result using wavelet transform and HMM

Emotion A F J S P

Anger 85 6 1 8 0

Fear 14 78 6 1 1

Joy 0 0 89 1 10

Sadness 1 3 4 92 0

Surprise 0 0 16 4 79

Total 101 87 116 106 90

Table 2. The result using wavelet transforms and improved HMM

Emotion A F J S P

Anger 90 4 1 4 1

Fear 11 83 3 1 2

Joy 0 0 95 2 3

Sadness 0 1 2 97 0

Surprise 0 2 7 3 88

Total 101 90 108 107 94

When compare table 1& 2 there is certain improve in efficiency but many shortages are lying the selecting of the features, so to find more efficient features and to do further analysis and experiment in a wide field.


Keeping problems discussed in previous chapter following will be my goals, which will be achieved during my thesis:

• The emotion is to be detected from the input speech signal the whole signal processing revolves around the speech signal for the extraction and selection of speech features correspond to emotions.

• In the previous work there is only single wavelet is used so to improve efficiency, the crossbreed decomposition takes place.

• The next is generating a database for training and testing of extracted speech features followed by the last stage of emotion detection by the classifier section using pattern recognition algorithms.


• Extraction and selection of speech feature: - The extraction of speech feature involves potential audio segmentation followed by acoustic preprocessing like filtering to form their meaningful units. The purpose of the audio segmentation is to segment a speech signal into units that are representative for emotions

• Database for training and testing: - A good database is as important as the desired result. There are different database created by speech processing community used in research work.

• Detect emotions: - Stored database are classifier to detect the emotions by comparing the vectors from the trained data and test data vector.

Evner: CakePHP, Codeigniter, PHP, WordPress, Yii

Se mere: emotion detection thesis, using algorithms, types of algorithms, the analysis of algorithms, testing algorithms, test algorithms, problems in algorithms, problems.algorithms, efficiency of algorithms, different types of algorithms, data stage 8.1, area vectors, analysis of algorithms, algorithms using c, algorithms test, algorithms problems, algorithms efficiency, algorithms and analysis, speech recognition, signal matlab, matlab training, matlab test, matlab signal processing, matlab find, data extraction and input

Om arbejdsgiveren:
( 0 bedømmelser ) Jammu, India

Projekt ID: #6015961

3 freelancere byder i gennemsnit ₹10712 på dette job


have gone through with the requirement and we can start this project now. I want to introduce our self, we are a group of freelancers we have 11 year of experience in web application development and design, we w Flere

₹10000 INR in 12 dage
(23 bedømmelser)

Hello, I have gone through your project’s initial requirements with the help of the job posting you have placed. And I think I have requisite experience and expertise to complete your project successfully. I am very Flere

₹8247 INR in 4 dage
(10 bedømmelser)

Hi, I am familiar with digital signal and image processing. I even bored with it because always deal with the same case, recognition, feature extraction, detection etc. Here is my portfolio: http://bacasekilas.b Flere

₹13888 INR in 14 dage
(0 bedømmelser)