Yazarlar: Hasan Erdinc KOCER, Mustafa Cumaah AHMED
Anahtar Kelimeler:HiddMarkov Model, Mel-Frequency Cepstral Coefficients, Turkish Speech Recognition
Özet: In this paper, a new Turkish spoken number recognition system proposed. The Mel-frequency cepstral coefficients (MFCC) algorithm used as a feature extraction method, the Gaussian Hidden Markov model, used for numbers phonemes modeling where each number has a Markov model. The system trained on a dataset collected from 20 subjects that includes 7 females and 13 males. Each one says the Turkish numbers from “zero” to “ten”. Audio files sampled at 8000Hz at each second and each file has one-second length and recorded in an isolated environment. We tested the system using random records for different people. The training files include 220 audio record and testing files include 18 audio record. The system achieves %83.3 accuracy, %86 precision, and %83 recall rates.