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| CODE | PROJECT TITLES | ABSTRACT | IEEE YEAR |
| SP01 | Acoustic interference cancellation for a voice-driven interface in smart TVs | A novel method is proposed to improve the voice recognition performance by suppressing acoustic interferences that add nonlinear distortion to a target recording signal when received by the recognition device. The proposed method is expected to provide the best performance in smart TV environments, where a remote control collects command speech by the internal microphone and performs automatic voice recognition, and the secondary microphone equipped in a TV set provides the reference signal for the background noise source. Due to the transmission channel, the original interference is corrupted nonlinearly, and the conventional speech enhancement techniques such as beamforming and blind signal separation are not applicable. The proposed method first equalizes the interference in the two microphones by maximizing the instantaneous correlation between the nonlinearly related target recording and reference signal, and suppresses the equalized interference. To obtain an optimal estimation of the equalization filter, a method for detecting instantaneous activity of interference is also proposed. The validity of the proposed method is proved by the improvement in automatic voice recognition performance in a simulated TV room where loud TV sounds or babbling speech interfere in a user’s commanding speech. | 2013 |
| SP02 | Signal detection for cognitive radar | The problem of signal detection for cognitive radar (CR) is considered, and a closed-loop detection system is proposed to detect the extended target in the presence of signal-dependent interference. In the system, the estimator of target impulse response (TIR) and waveform design are used to improve the detection performance of CR, and the estimate of TIR is also used for designing the matched waveform. In addition, in order to improve the reliability of detection, the two-step process which is called estimation before detection is proposed. Simulation results indicate that the proposed system performs better than the traditional radar system which used the fixed waveform. | 2013 |
| SP03 | Smart-TV Based Integrated E-health Monitoring System with Agent Technology | An ageing population is now the leading concern for higher healthcare costs due to more cases of chronic illnesses. Telemedicine systems based on modern Information and Communication Technology (ICT) are expected to play a pivotal role in alleviating the pressure on health care services. Environmental factors have also profound impact on health condition of the patients. As a consequence monitoring of human health along with the environmental (where the patient is located) health enables the health care providers to comprehend more accurately about a patient’s situation. In this paper we describe a novel integrated tele-monitoring framework (theoretical architecture) proposed to support both of the above functions simultaneously though a single framework. The proposed system also innovatively harnesses the power of emerging Smart-TV technology as a means of interaction between patient and the health care providers. To the best of our knowledge, this is the first of its kind. | 2013 |
| SP04 | Target detecting defence humanoid sniper | In this paper, a new method of defence system using image processing has been implemented. It is mainly focussed on bringing out the best target tracking technology. The defence humanoid is designed to overcome foreign attacks at the country border. The defence system consists of two modules- control unit and humanoid unit. The control unit has a laptop in which Graphical User Interface (GUI) using MATLAB has been implemented. Image processing is done and the control signal is transmitted. The humanoid unit receives the signal from the control unit, at a remote location and responds according to the processed control signal. The control signal has been processed by image processing technique. The humanoid does image processing by the combination of edge detection, scale space analysis, thermal image processing and virtual 3D sizing in 2D image processing and colour detection. The humanoid, works in three modes- (1) Auto Targeting and Auto Shooting (Fully Autonomous).(2)Auto Targeting and Manual Shooting.(Semi-Autonomous).(3)Manual Targeting and Manual Shooting (User Oriented). | 2013 |
| SP05 | Least-Mean-Square algorithm based adaptive filters for removing power line interference from ECG signal | The 50 Hz power line is one of the main sources of interference in ECG signal measurement, and it distorts the original ECG signal while recording. Recently, adaptive filtering has become one of the effective and popular methods for the processing and analysis of the ECG signal. In this study, we have used adaptive filters to remove the power line interference from the ECG signal. We have used different adaptive filter algorithms, such as, Least-Mean-Square (LMS), Block LMS (BLMS), Delay LMS (DLMS), Adjoint LMS, Filtered-X (XLMS), Normalized LMS (NLMS) and Fast Fourier Transform BLMS (FFT BLMS). We have used the Signal Processing Toolbox of the mentioned algorithms built in MATLAB®. It reveals that among all the adaptive filters, the adaptive NLMS filter removes the 50 Hz power line interference more effectively. | 2013 |
| SP06 | A laboratory experiment for real-time echo cancellation using a BeagleBoard | Practical experience is an important aspect of the training of every engineer. One way to develop such experience is by hands-on laboratory experimentation which involves cutting-edge technology. In this paper, we present a signal processing lab experiment developed for undergraduate students. Throughout the experiment, students first learn the basics of adaptive filtering and implement an adaptive echo cancellation algorithm using MATLAB. Then, students use a software framework for implementing the same echo cancellation algorithm on a BeagleBoard development platform using both ARM and fixed-point DSP cores of an embedded system-on-chip from Texas Instruments. In a relatively short amount of time (8 hours at the lab and a few additional hours of homework), students learn an important signal processing technique, as well as use complex state-of-the-art DSP hardware to implement it as part of an application running in real-time. | 2013 |
| SP07 | Application of temperature compensated ultrasonic ranging for blind person and verification using MATLAB | This paper contains a method to implement a mobility aid for blind person and also can be used in automatic robots, self-propelling vehicles in automated production factories etc. Model contains signal processing unit with PIC microcontroller which receives data from Ultrasonic sensor and Temperature sensor then processed it and delivers it to the computer using serial input/output port & gives alert to the blind person using voice processor with earphone. Paper contains temperature compensation method to reduce the error in measurement of distance using ultrasonic sensors. Signal processing unit contains PIC microcontroller which is used for interfacing between different sensors and computer. Then received data is verified using MATLAB. | 2013 |
| SP08 | Wavelet-based analysis for heart sound monitoring system | Phonocardiography is a modern form of auscultation, it consists in the graphical representation of heart sounds. Digital signal processing techniques applied to phonocardiography result in developing a more reliable heart sounds monitoring system in less time and at lower costs. This paper describes the design and implementation of a heart sound monitoring system on Digital Signal Processor board; graphical representation of heart sound is implemented on a MATLAB platform through Real-Time Data Exchange algorithms and two methods to extract the time and frequency characteristics of the heart sounds are presented: short time fourier transform and wavelet transforms. Experimental data is processed comparing the obtained results from both algorithms. | 2013 |
| SP09 | Automated pitch-based gender recognition using an adaptive neuro-fuzzy inference system | Results on classifying a speaker on the basis of gender by processing speech and analyzing the voice samples are presented. Firstly, the speech samples are classified into voiced/unvoiced/silence by using a speech classification algorithm implemented in MATLab. The pitch of the subject’s voice is extracted from the classified speech sample. Following this, automated clustering is done by an Adaptive Neuro-Fuzzy Inference System (ANFIS) to separate male and female pitch values. An automated gender classification is successfully performed by ANFIS, although, the ANFIS has to be trained before the actual classification. | 2013 |
| SP10 | Fuzzy rule based voice emotion control for user demand speech generation of emotion robot | The emotional function of the human mind has an important role for decision-making, memory, action, and good communication or so. Especially, emotion characteristics of voice are very import for warm communication, successful business, human-to-human good relationship, and good care for children and silver ages. On the other hand, recently, service robot market such as educator, helper, secretary, deliver, and guider has been growing up because of old population and complicated social situation. In that case the emotion function is needed in those areas. The emotion characteristic of voice depends on pitch contour, acoustic energy, vocal tract features, speech energy or so. Therefore we need to consider on how we have to apply and implement emotion function of voice for service robot. However, its implement for robot is very difficult and recognition is also not easy because of various emotion patterns in voice. This paper suggests method of voice emotion generation for user demand emotion talk in service robot. Fuzzy rule based approach is introduced to generate emotion for user demand emotional function by controlling pitch contour, acoustic energy, vocal tract features, and speech energy. | 2013 |
| SP11 | Speech recognition based wireless automation of home loads with fault identification for physically challenged | The design of this project helps in providing a fool proof solution for physically challenged to control their home appliances by giving voice commands through personal computer in a wireless environment. When automating a home load not available in the visible range, Fault identification system in this design helps the user to ensure that their home appliances had gone exactly ON or OFF or undergone FAULT by getting the status from load end, unlike the other design that gets the status at user end which may give a false indication, when power supply is not available for the particular load or when load get open circuited (due to wire discontinuity or open fuse condition). During user screen navigation and controlling home appliances voice output of the current screen information and status of the automated appliances enables visually impaired person to use the system to control their home appliances. Navigation of the screen by giving voice commands enables paralyzed person and person who lost their hands in an unfortunate accident to control their home loads along with normal person. For achieving wireless environment low cost zigbee is used. To provide security based authentication RFID is used. Each home load will be having two commands ON and OFF commands, Automation of 20 loads such as mixer, grinder, TV, refrigerator, fan, light, AC etc…, has been tested by giving 40 voice commands through personal computer. When user creates his own profile and automates the load speech recognition accuracy of more than 90% is achieved. Other people who were allowed to automate the load by the user can use user profile and achieve a speech recognition accuracy of 75% in the same personal computer. | 2013 |
| SP12 | Wind Signal Forecasting Based on System Identification Toolbox of MATLAB | Wind signal (including wind speed and direction) forecasting can relieve or avoid the disadvantageous impact of wind power plants and enhance the competitive ability of wind power plants against other power plants in electricity markets. Firstly, the method for analyzing and dealing with the dynamic data, the process of rank – determining and model-constructing of time series were discussed. At last, the result for wind signal forecasting was gained. The result shows that the ARMA model based on System Identification Toolbox of MATLAB is every valid to forecast wind signal and can reflect the future characteristics of the signal. | 2013 |