Matlab is a registered trademark of The Mathworks, Inc.

 Advanced Source Code . Com

Source code for fingerprint recognition, face recognition and much more

Software Info    About us     
Go To Matlab Official Website

.: Click here to download :.

The efforts to automate the combination of expert opinions have been studied extensively in the second half of the twentieth century. The combined experts are classifiers and the result of the combination is also a classifier. The outputs of classifiers can be represented as vectors of numbers where the dimension of vectors is equal to the number of classes. As a result, the combination problem can be defined as a problem of finding the combination function accepting N-dimensional score vectors from M classifiers and outputting N final classification scores, where the function is optimal in some sense, e.g. minimizing the misclassification cost.

Combination methods can also be grouped based on the level at which they operate. Combinations of the first type operate at the feature level. The features of each classifier are combined to form a joint feature vector and classification is subsequently performed in the new feature space.

Combinations can also operate at the decision or score level, that is they use outputs of the classifiers for combination. This is a popular approach because the knowledge of the internal structure of classifiers and their feature vectors is not needed. Though there is a possibility that representational information is lost during such combinations, this is usually compensated by the lower complexity of the combination method and superior training of the final system.

We have developed a fast and reliable algorithm for speech recognition for isolated words. The proposed method combines at decision level several algorithms commonly used for speech recognition such as Discrete Cosine Transform, Mel-Frequency Cepstral Coefficients, Linear Predictive Coding, Relative Spectral Transform and Perceptual Linear Prediction. The algorithm for combination can be easily parallelized and run on low-cost hardware in reasonable time.

Index Terms: Matlab, source, code, speech, recognition, isolated, word, words, feature, algorithm, combination, fusion.






Figure 1. Speech waveform

A simple and effective source code for Hybrid Speech Recognition System.

Demo code (protected P-files) available for performance evaluation. Matlab Image Processing Toolbox, Matlab Wavelet Toolbox and Matlab Signal Processing Toolbox are required.

Major features


  • Speech recognition based on multiple features selection
  • Optimized algorithm for combination of classifiers
  • Sound acquisition from microphone
  • Sound acquisition from disk
  • Discrete Cosine Transform
  • Mel-Frequency Cepstral Coefficients
  • Linear Predictive Coding
  • Relative Spectral Transform
  • Perceptual Linear Prediction
  • Fast and optimized implementation
  • Easy and intuitive GUI
  • Demo code (protected P-files) available for performance evaluation

We recommend to check the secure connection to PayPal, in order to avoid any fraud.
This donation has to be considered an encouragement to improve the code itself.

Hybrid Speech Recognition System - Click here for your donation. In order to obtain the source code you have to pay a little sum of money: 400 EUROS (less than 560 U.S. Dollars).

Once you have done this, please email us
As soon as possible (in a few days) you will receive our new release of Hybrid Speech Recognition System.

Alternatively, you can bestow using our banking coordinates:
Name :
Luigi Rosa
Address :
Via Pozzo Strada 5 10139 Torino Italy
Bank name:
Poste Italiane
Bank address:
Viale Europa 190 00144 Roma Italy
IBAN (International Bank Account Number) :
BIC (Bank Identifier Code) :

The authors have no relationship or partnership with The Mathworks. All the code provided is written in Matlab language (M-files and/or M-functions), with no dll or other protected parts of code (P-files or executables). The code was developed with Matlab 2006a. Matlab Image Processing Toolbox, Matlab Wavelet Toolbox and Matlab Signal Processing Toolbox are required. The code provided has to be considered "as is" and it is without any kind of warranty. The authors deny any kind of warranty concerning the code as well as any kind of responsibility for problems and damages which may be caused by the use of the code itself including all parts of the source code.

New - Python Face Recognition
 Biometric Authentication with Python We have developed a fast and reliable Python code for face recognition based on Principal Component Analysis (PCA). Proposed algorithm results computationally inexpensive and it can run also in a low-cost pc such as Raspberry PI.
New - Raspberry PI Remote Desktop
 Raspberry PI Remote Desktop A complete and detailed PDF tutorial to learn how to connect to and from a Raspberry PI using Remote Desktop.
New - Speaker Verification System
 Text-Independent Speaker Authentication There are two major applications of speaker recognition technologies and methodologies. If the speaker claims to be of a certain identity and the voice is used to verify this claim, this is called verification or authentication.
New - Java Face Recognition
 Java-based Biometric Authentication System Face recognition is essential in many applications, including mugshot matching, surveillance, access control and personal identification, and forensic and law enforcement applications.
New - White Papers
 High Capacity Wavelet Watermarking Using CDMA Multilevel Codes This paper proposes a technique based on CDMA and multilevel coding in order to achieve a high capacity watermarking scheme. The bits of watermark are grouped together and for each sequence a different modulation coefficient is used.
New - WebCam Face Identification
 Face Recognition Based on Fractional Gaussian Derivatives Local photometric descriptors computed for interest regions have proven to be very successful in applications such as wide baseline matching, object recognition, texture recognition, image retrieval, robot localization, video data mining, building panoramas, and recognition of object categories.
New - Speaker Recognition System
 Source code for speaker recognition
Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves.
New - Speech Recognition System
 Source code for isolated words recognition
Speech recognition technology is used more and more for telephone applications like travel booking and information, financial account information, customer service call routing, and directory assistance. Using constrained grammar recognition, such applications can achieve remarkably high accuracy.

The MathWorks, Inc. Google NeuralNetworks.It Octave Scilab The R Project for Statistical Computing Python Other available resources English Dictionary Download .Com
Software Info    About us