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SPEAKER RECOGNITION SYSTEM
No full textThis project is to design and implement a speaker recognition system, and apply it to a speech of an unknown speaker. By investigating the extracted features of the unknown speech and then compare them to the stored extracted features for each different speaker in order to identify the unknown speaker.Speaker Recognition is a very interesting area of Digital Signal Processing and it fits well with researches, since this application is still facing many difficulties which need modern technologies and researching efforts to be overcome.
Speech Recognition is the process of automatically recognizing a certain word spoken by a particular speaker based on individual information included in speech waves. This technique makes it possible to use the speaker’s voice to verify his/her identity.
Speaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves. This technique makes it possible to use the speaker's voice to verify their identity and control access to services such as voice dialing, banking by telephone, telephone shopping, database access services, information services, voice mail, security control for confidential information areas, and remote access to computers. By checking the voice characteristics of the input utterance, using an automatic speaker recognition system similar to the one that we will develop, the system is able to add an extra level of
security.
Practically the goal of this project is to design and implement a speaker recognition system, and apply it to a speech of an unknown speaker. By investigating the extracted features of the unknown speech and then compare them to the stored extracted features for each different speaker in order to identify the unknown speaker.
To achieve this, a particular speaker utters the password once in the training session so as to train and store the features of the access word. Later in the testing session the user utters the password again in order to achieve recognition if there is a match. The feature vectors unique to that speaker are obtained in the training phase and this is made use of later on to grant authentication to the same speaker who once again utters the same word in the testing phase. At this stage an intruder can also test the system to test the inherent security feature by uttering the same word.
The project objectives have been met successfully. Many algorithms have been used to design this system. These algorithms were tested and compared considering quality and accuracy. Also-as an optional work- we have implemented a GUI in order to facilitate the usage of this system and provide comfortable interaction for the user
Speaker Recognition System
No full textThe main aim of this project is to investigate and build a speaker recognition system in “ MATLAB program ” that recognises a person based on his/her speech patterns, using different recognition algorithms : MFCC extraction technique, FFT approach and also with Vector quantization modelSpeaker recognition is the process of automatically recognizing who is speaking on the basis of individual information included in speech waves. This technique makes it possible to use the speaker‟s voice to verify his/her identity and provide controlled access to services like voice based biometrics, database access services, voice based dialing, voice mail and remote access to computers .
Signal processing front end for extracting the feature set is an important stage in any speaker recognition system. The optimum feature set is still not yet decided though the vast efforts of researchers. There are many types of features, which are derived differently and have good impact on the recognition rate. This project presents one of the techniques to extract the feature set from a speech signal, which can be used in speaker recognition systems. The key is to convert the speech waveform to some type of parametric representation (at a considerably lower information rate) for further analysis and processing. This is often referred to as the signal-processing front end.
A wide range of possibilities exist for parametrically representing the speech signal for the speaker recognition task, such as Linear Prediction Coding (LPC), Mel-Frequency Cepstrum Coefficients (MFCC), and others. MFCC is perhaps the best known and most popular, and these will be used in this project. MFCCs are based on the known variation of the human ear‟s critical bandwidths with frequency filters spaced linearly at low frequencies and logarithmically at high frequencies have been used to capture the phonetically important characteristics of speech.
The voice based biometric system is based on isolated or single word recognition. A particular speaker utters the password once in the training session so as to train and store the features of the access word. Later in the testing session the user utters the password again in order to achieve recognition if there is a match. The feature vectors unique to that speaker are obtained in the training phase and this is made use of later on to grant authentication to the same speaker who once again utters the same word in the testing phase. At this stage an intruder can also test the system to test the inherent security feature by uttering the same word .
The project goals have been met successfully and the speaker recognition system was designed and implemented using MATLAB software program .Moreover , a GUI is introduced to ease using the system . Simulation and experimental results show the effectiveness of the proposed system , however , some limitations were discovered and should be eliminated in the future
إستخدام الطاقة الشمسية في التخزين المبرد للبطاطس
No full textإستخدام الطاقة الشمسية في التخزين المبرد للبطاط
