Speech Recognition of Malayalam Numbers

Digit speech recognition is important in many applications such as automatic data entry, PIN entry, voice dialing telephone, automated banking system, etc. This paper presents speaker independent speech recognition system for Malayalam digits. The system employs Mel frequency cepstrum coefficient (MFCC) as feature for signal processing and Hidden Markov model (HMM) for recognition. The system is trained with 21 male and female voices in the age group of 20 to 40 years and there was 98.5% word recognition accuracy (94.8% sentence recognition accuracy) on a test set of continuous digit recognition task.

A reconfiguration dual-frequency slot-loaded microstrip antenna controlled by pin diodes

A novel reconfigurable, single feed, dual frequency, dualpolarized operation of a hexagonal slot-loaded square mwrostrip antenna is presented in this paper. A pin diode incorporated in the slot is used to switch the two operating frequencies considerably, without significantly affecting the radiation characteristics and gain. The proposed antenna provides a size reduction up to 61% and 26% Jor the two resonating frequencies, compared to standard rectangular patches. This design also gives considerable bandwidth up to 3.3% and 4.27%, for the two frequencies with a low operating frequency ratio

Investigations on Reconfigurable Dual Frequency Microstrip Antennas Controlled by PIN Diodes and Varactors

In this work,we investigate novel designs of compact electronically reconfigurable dual frequency microstrip antennas with a single feed,operating mainly in L-band,without using any matching networks and complicated biasing circuitry.These antennas have been designed to operate in very popular frequency range where a great number of wireless communication applications exist.Efforts were carried out to introduce a successful,low cost reconfigurable dual-frequency microstrip antenna design to the wireless and radio frequency design community.

A Comparative study of HMM and SVM in Malayalam Digit Recognition

A primary medium for the human beings to communicate through language is Speech. Automatic Speech Recognition is wide spread today. Recognizing single digits is vital to a number of applications such as voice dialling of telephone numbers, automatic data entry, credit card entry, PIN (personal identification number) entry, entry of access codes for transactions, etc. In this paper we present a comparative study of SVM (Support Vector Machine) and HMM (Hidden Markov Model) to recognize and identify the digits used in Malayalam speech.