RIS ID
100501
Abstract
This paper presents a technique for recognizing spoken letter in Bengali Language. We first derive feature from spoken letter. Mel-frequency cepstral coefficient (MFCC) has been used to characterize a feature. Dynamic time warping (DTW) employed to calculate the distance of an unknown letter with the stored ones. K-nearest neighbors (KNN) algorithm is used to improve accuracy in noisy environment.
COinS
Publication Details
Sayem, A. (2014). Speech analysis for alphabets in Bangla language: automatic speech recognition. International Journal of Engineering Research, 3 (2), 88-93.