iosr-JCE   Volume-17 ~ Issue-4 ~ July-August 2015

Abstract: Speech is a medium through which emotions are expressed by human being. In this paper, a mixture of MFCC and LPCC has been proposed for audio feature extraction. One of the greatest advantage of MFCC is that it is capable of identifying features even in the existence of noise and henceforth it is combined with the advantage of LPCC which helps in extracting features in low acoustics. Two databases have been considered namely Berlin Emotional Database and a SAVEE database.

[1]. Igor Bisio, Alessandro Delfino, Fabio Lavagetto, Mario Marchese, And Andrea Sciarrone, "Gender-Driven Emotion Recognition Through Speech Signals For Ambient Intelligence Applications", Ieee Transactions On Emerging Topics In Computing, Digital Object Identifier 10.1109/Tetc.2013.2274797, 21 January 2014.
[2]. http://www.expressive-speech.net/, Berlin emotional Speech database
[3]. http://personal.ee.surrey.ac.uk/Personal/P.Jackson/SAVEE/, SAVEE Database
[4]. Nitin Thapliyal, Gargi Amoli, "Speech based Emotion Recognition with Gaussian Mixture Model‟, International Journal of Advanced Research in Computer Engineering & Technology, Volume 1, Issue 5, July 2012, ISSN: 2278 1323.
[5]. Inma Mohino-Herranz, Roberto Gil-Pita, Sagrario Alonso-Diaz and Manuel Rosa-Zurera, "MFCC Based Enlargement Of The Training Set For Emotion Recognition In Speech", Signal & Image Processing : An International Journal (SIPIJ) Vol.5, No.1, February 2014.

Abstract:In essence of fuzzy inference system (FIS) for classification, Genetic algorithm (GA) which is an optimal searching technique is used for generation rules in the proposed work. This paper develops an FIS with rules generated using GA, the GA is developed with rule importance as fitness criteria. The rule importance of each rule is calculated by its rule support in each rule class. Encoding of rules is using the fuzzy membership set no for antecedent and consequent. Also the stopping criteria is a combination ofgenerations specified and Minimum rules fired count. The Proposed system using GA approach for rule generation giving consistent results with optimal rules.

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[6]. SoumadipGhosh, SushantaBiswas, DebasreeSarkar, ParthaPratimSarkar, "Mining Frequent Itemsets Using Genetic Algorithm",International Journal of Artificial Intelligence & Applications (IJAIA), Vol.1, No.4,pg. 133-144, October 2010.

Abstract: Major online "Question and Answer" forums have proven to be of enormous help to programmers and developers from all parts of the world. One such important forum is the Stack Overflow community. In this paper, we explore and analyze the title of a question posted on the Stack Overflow community and check whether the title abides by the set of rules and guidelines defined by the Stack Overflow community [1] and [3]. We also carry out sentiment analysis on the title to judge the virality [2] quotient of the question. We present an application (or tool) developed using the Natural Language Toolkit (NLTK) and Py-stackexchange API (Application Programming Interface) of Stack Overflow in Python.

[1]. How do I write a good title? http://meta.stackexchange.com/questions/10647/writing-a-good-title

[2]. Berger, Jonah, and Katherine L. Milkman. "What makes online content viral? "Journal of marketing research 49.2 (2012):192-205.[pdf]Can we prevent titles with an unnecessary tag in them? http://meta.stackexchange.com/questions/103563/can-we-prevent-titles-with-an-unnecessary-tag-in-them

[3]. Squire, Megan, and Christian Funkhouser. "" A Bit of Code": How the Stack Overflow Community Creates Quality Postings." System Sciences (HICSS), 2014 47th Hawaii International Conference on. IEEE, 2014.[pdf]