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.
Abstract-This paper describes the techniques to morph between the two portions of sound originated from a common source, broken because of by some reason. We make use of morphing technique to join the sound where the pitch of the sound slowly changes from one broken part to another broken part by slowly changing the pitch information also covering the unvoiced region of the music. Spectral shapes are encoded on the multidimensional space while pitch on orthogonal axes of it. After matching components of the sound, a morph smoothly interpolates the amplitudes to describe a new sound in the same perceptual space. Finally, by inverting the representation, sound is produced. According to the literature survey, this is the first paper which explains the step by step evolution of one sound resulting into other sound across all states of intermediate steps along with the step by step runtime analysis. This will help researchers in future to improve the morphing methodology by looking carefully into the intermediate steps which decides the overall results. Here, we key out representations for morphing, techniques for matching, and interpolation algorithms and morphing each sound component. Spectral images of complete morph spectrogram are shown in the end.
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