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- Title
Extracting accent information from Urdu speech for forensic speaker recognition.
- Authors
TAHIR, Falak; SALEEM, Sajid; AHMAD, Ayaz
- Abstract
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.
- Subjects
PROSODIC analysis (Linguistics); OBJECT recognition (Computer vision); ERROR rates; SPEECH; DATA mining
- Publication
Turkish Journal of Electrical Engineering & Computer Sciences, 2019, Vol 27, Issue 5, p3763
- ISSN
1300-0632
- Publication type
Article
- DOI
10.3906/elk-1812-152