Ali Kafaei - Master Student Amirkabir University of Technology Tehran, Iran
Abolghasem Sayadian - Associated Professor Amirkabir University of Technology Tehran, Iran
Hamidreza Baradaran Kashani - PHD Candidate Amirkabir University of Technology Tehran, Iran

Speaker verification has been studied for years. Many databases such as NIST has been used widely ;however , most of these databases are narrow band, not rich in context information and have high channel effect. In this paper, a wide band low noise and rich database of Farsi language has been used which does not have mentioned problems and it is suitable for many applications. Feature extraction is a key part in speaker verification. STFT-MFCC which uses FFT and filter bank is state of the art feature in speaker verification. The main problem of STFT-MFCC is that cannot model envelope accurately. We use STRAIGHT-MFCC, which is well-known for synthesis. STFT-MFCC and STRAIGHT-MFCC performance was compared for 2 minutes and full training data using GMM-UBM model. Results show that STRAIGHT-MFCC outperforms STFT-MFCC especially for short duration training data

speaker verification, wideband, MFCC, STREIGHT