Extracting accent information from Urdu speech for forensic speaker recognition

Falak TAHIR; Sajid SALEEM; Ayaz AHMAD

Makale detayları

Extracting accent information from Urdu speech for forensic speaker recognition

Yazarlar:

Falak TAHIR | Sajid SALEEM | Ayaz AHMAD

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2019 Vol.27 Issue 5, pp.3763-3778

Belge Tipi:

Makale

Yayın Tarihi:

9/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000733684

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

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.

Makale detayları

Extracting accent information from Urdu speech for forensic speaker recognition

Yazarlar: Falak TAHIR | Sajid SALEEM | Ayaz AHMAD

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2019 Vol.27 Issue 5, pp.3763-3778

Belge Tipi: Makale

Yayın Tarihi: 9/2019

Belge Dili: İngilizce

Document ID (Org No.): 2000733684

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Falak TAHIR | Sajid SALEEM | Ayaz AHMAD

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2019 Vol.27 Issue 5, pp.3763-3778

Belge Tipi:

Makale

Yayın Tarihi:

9/2019

Belge Dili:

İngilizce

Document ID (Org No.):

2000733684

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632