Voice Recognition MATLAB Projects 2019

Speech Recognition Using Matlab using MATLAB

Speech Recognition is the process in which certain words of a particular speaker will automatically recognized that are based on the information included in individual speech waves. This paper enlightens upon the invention as well as technological advancement in the field of voice recognition and also focuses upon different steps involved for speaker identification using MATLAB Programming. In this paper firstly we will going to perform speech editing as well as degradation of signals by the application of Gaussian Noise. This background noise then will success fully removed by the application of Butterworth Filter. Moreover, the technique applied here is to develop a code using MATLAB Programming which will compare the pitch and format vectors of a known speech signal which will then compare with the bunch of other unknown speech signals and prior to it choose the appropriate matches.

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Speech Recognition with Dynamic Time Warping using MATLAB using MATLAB

Speech recognition has found its application on various aspects of our daily lives from automatic phone answering service to dictating text and issuing voice commands to computers. In this paper, we present the historical background and technological advances in speech recognition technology over the past few decades. More importantly, we present the steps involved in the design of a speaker-independent speech recognition system. We focus mainly on the pre-processing stage that extracts salient features of a speech signal and a technique called Dynamic Time Warping commonly used to compare the feature vectors of speech signals. These techniques are applied for recognition of isolated as well as connected words spoken. We conduct experiments on MATLAB to verify these techniques. Finally, we design a simple ‘Voice-to-Text’ converter application using MATLAB.

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Generating an Isolated Word Recognition System Using Matlab using MATLAB

MATLAB’s straight forward programming interface makes it an ideal tool for speech analysis. In this work, experience was gained in general MATLAB programming. A basic speaker recognition algorithm has been written to sort through a rule base in MATLAB and choose the one most likely match based on the predefine time frame of the speech utterance. Speech communication has evolved to be efficient and robust and it is clear that the route to computer based speech recognition is the modeling of the human system. Speaker dependent speech recognition is therefore an engineering compromise between the ideal, i.e. a complete model of the human, and the practical, i.e. the tools that science and technology provide and that costs allow the modeling of the human system.

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Speech Recognition Using Correlation Technique using MATLAB

The growth in wireless communication and mobile devices has supported the development of Speech recognition systems. So for any speech recognition system feature extraction and patter matching are two very significant terms. In this paper we have developed a simple algorithm for matching the patterns to recognize speech. We used Mel frequency cepstral coefficients (MFCCs) as the feature of the recorded speech. This algorithm is implemented simply by using the principle of correlation. All the simulation experiments were carried out using MATLAB where the method produced relatively good results. This paper gives a details introduction of recorded speech processing, design considerations and evaluation results.

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Voice & Speech based Security System using MATLAB using MATLAB

VSSS is designed for the users who intend to achieve high definition security system to secure office or home. The important features for a security system to be accessible are authentication as well as authorization. The human voice includes speech as well as voice. For the system to operate, speech as well as voice is mandatory to match the recorded sample. The design of system also involves a GSM system to provide a feedback message to the prime member of the unit with the information of user accessing the system. This project includes the hybrid of all approaches which are helpful in achieving more accurate result.

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Attention Modeling for Face Recognition via Deep Learning using MATLAB

Face recognition is an important area of research in cognitive science and machine learning. This is the first paper utilizing deep learning techniques to model human’s attention for face recognition. In our attention model based on bilinear deep belief network (DBDN), the discriminant information is maximized in a frame of simulating the human visual cortex and human’s perception. Comparative experiments demonstrate that from recognition accuracy our deep learning model outperforms both representative benchmark models and existing bio-inspired models. Furthermore, our model is able to automatically abstract and emphasize the important facial features and patterns which are consistent with the human’s attention map.

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