Abstract-Constructive learning is an important research area having wide impact on teaching methods in education, learning theories, and plays a major role in many education reform movements. Teachers play a major role in improving the learning skill of the students. It is observed that constructive learning advocates the interconnection between emotions and learning. When students fail to get the excepted results they tend to feel that they are not good at the subject/task. Teachers should make them realize that failure is also a part of learning process and improve their learning rates. Human teachers identify the emotions of students with varying degrees of accuracy. In learning with computers, computers also should be given the capability to recognize emotions so as to optimize the learning process. Literature survey indicates the wide use of image processing to understand the constructive learning theory. The paper presents a novel system which can be used by computer to access the emotional state of the learner further presenting a corrective measure to improve their learning states. This is the first paper which analyses constructive learning using speech analysis. It is the primary paper which analyses the effect of emotions on the learning rate using pitch tracking. A database consisting of acoustic waveforms produced by an amateur musician is taken and the learning rates are analyzed. The pitch contours of waveforms are compared with the standard waveform and the error graphs are plotted. Analysis of the emotion of the subject is also made by observing the error plots.
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