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Introduction to fractal

introduction to fractal theory for speech processing
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  Introduction Red means PA PARAPHRASE Affective Computing  is computing that relates to, arises from, or deliberately influences emotion or other affective phenomena.[1]   Affective computing is currently one of the most active research topics, furthermore, having increasingly intensive attention. This strong interest is driven by a wide spectrum of promising applications in many areas such as virtual reality, smart surveillance, perceptual interface, etc. Affective computing concerns multidisciplinary knowledge background such as psychology, cognitive, physiology and computer sciences. [2] Detection of emotion in speech can be used in a variety of situations like providing assistance where human resources are limited, by automatically detecting where the levels of distress or need are highest, allowing human resources to be allocated where it is needed the most.    Although it is impossible to accurately compare recognition accuracies based from other studies because of the different data sets used.Other studies said that several confusing emotion  pairs exists such as happy and interest  , happy and  panic , interest   and  sadness ,  panic and hot anger  . The accuracy of classifying these pairs was relatively low due to the limitation of emotion representing ability of current features.[4] One research used the Fractal features for Emotion Recognition from Speech but disgust seems to be very difficult to detect with Fractal features.[3]   What is Emotion Emotions are fundamental for humans, impacting perception and everyday activities such as communication, learning and decision-making. They are expressed through speech, facial expressions, gestures and other non-verbal clues.[5]   We’ ll group emotions into 2 types of emotions:  Negative  and Positive.  Negative emotions express an attempt or intention to Exclude. Strengthening one's own position at the expense of others. Keeping bad stuff away, destroying what is  perceived as a threat. Negative emotions are fueled by an underlying fear of the unknown, a fear of the actions of others, and a need to control them or stop them to avoid being harmed.[6]  Negative emotions are, for example: apathy, grief, fear, hatred, shame, blame, regret, resentment, anger, hostility [6] Positive emotions express an attempt or an intention to Include. Taking the whole into consideration. Working on learning more viewpoints, interacting more with others,  enjoying making things better. Positive emotions are fueled by an underlying desire for enjoyment and unity.[6] Positive emotions are, for example: interest, enthusiasm, boredom, laughter, empathy, action, curiosity.[6] A fractal theory studies the phenomena of self-similarity. The object is considered a fractal if it exhibits some sort of self-similarity. Normal human speech is produced with pulmonary pressure provided by the lung. It creates phonation in the glottis that is then modified by the vocal tract into different vowels and consonants. Both the quasi-periodic vibration of the vocal folds and the modification by the vocal tract are nonlinear processes, especially when the consonant occurs, the turbulence is generated in the narrow parts of the vocal tract. Consequently, the waveform of speech signal shows both periodicity and self-similarity according to the vowels and consonants International which form syllables together. For example, a speaker in an excited emotion is one who is unable to breathe normally at the time of speech. The abnormal breathing could be caused either due to a physical or emotional shock. An abnormally breathing speaker, however, should produce speech which has similar underlying statistic, thus causing the fractal dimension to be invariant over the speaker, both excited and normal emotional states.[3] Delimitations Not 100% accurate, disadvantages, background music, noise sounds etc. etc. [1] [2] [3] study on the Emotion Recognition from Speech Signals Using Fractal Dimension Features Jun Seok Park1, Soo Hong Kim 2 2013    [4] Detecting Emotion in Human Speech  Alex Mordkovich, Kelly Veit, Daniel Zilber famordkov, kjveit, December 16th, 2011 [5]  Emotion Detection from Speech Computer Science Tripos Part II Gonville & Caius College 2009-2010  [6]Transformational Paths Facilitator Training Manual #2 By Flemming Funch -Transformational Processing Institute

Detmer Ch2 Ppt

Jul 23, 2017


Jul 23, 2017
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