Authors:
Adnan Firoze
;
M. Shamsul Arifin
;
Ryana Quadir
and
Rashedur M. Rahman
Affiliation:
North South University, Bangladesh
Keyword(s):
Speech Recognition, Spectrogram, Fuzzy Logic, STFT, Standard Deviation, Segmentation.
Related
Ontology
Subjects/Areas/Topics:
Advanced Applications of Fuzzy Logic
;
Applications of Expert Systems
;
Artificial Intelligence and Decision Support Systems
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Tools, Techniques and Methodologies for System Development
Abstract:
The paper presents Bangla word speech recognition using spectral analysis and fuzzy logic. As human speech is imprecise and ambiguous, the fuzzy logic – the base of which is indeed linguistic ambiguity, could serve as a more precise tool for analysing and recognizing human speech. Even though the core source of an uttered word is a voiced signal, our system revolves around the visual representation of voiced signals – the spectrogram. The spectrogram may be perceived as a “visual” entity. The essences of a spectrogram are matrices that include information about properties of a sound, e.g., energy, frequency and time. In this research the spectral analysis has been chosen as opposed to image processing for increased accuracy. The decision making process of our system is based on fuzzy logic. Experimental results demonstrate that our system is 80% accurate compared to a commercial Hidden Markov Model (HMM) based speech recognizer that shows 73% accuracy on an average.