Falak TAHIR, Sajid SALEEM, Ayaz AHMAD

97113

Extracting accent information from Urdu speech for forensic speaker recognition

This paper presents a new method for extraction of accent information from Urdu speech signals. Accent is used in speaker recognition system especially in forensic cases and plays a vital role in discriminating people of different groups, communities and origins due to their different speaking styles. The proposed method is based on Gaussian mixture model-universal background model (GMM-UBM), mel-frequency cepstral coefficients (MFCC), and a data augmentation (DA) process. The DA process appends features to base MFCC features and improves the accent extraction and forensic speaker recognition performances of GMM-UBM. Experiments are performed on an Urdu forensic speaker corpus. The experimental results show that the proposed method improves the equal error rate and the accuracy of GMM-UBM by 2.5 % and 3.7 %, respectively.
Keywords:

Forensic classification, speaker recognition, speech features,

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Turkish Journal of Electrical Engineering and Computer Science-Cover
  • ISSN: 1300-0632
  • Yayın Aralığı: Yılda 6 Sayı
  • Yayıncı: TÜBİTAK
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