| العنوان باللغة العربية : | |
| العنوان باللغة الانكليزية : | Robust Speaker Recognition in Noisy Conditions by Means of Online Training with Noise Profiles |
| المؤلف : | Ahmed Hani Al-Noori |
| البريد الالكتروني : | |
| جهة انتساب المؤلف : | Al-Nahrain University |
| المشاركين : | PHILIP DUNCAN |
| المستفيدين : | |
| المستخلص : | Automated speaker recognition attains impressive reliability when tested under controlled laboratory acoustic conditions. The environmental noise that inevitably presents in many realworld speech samples causes considerable degradation of recognition accuracy due to the socalled “channel mismatch” that occurs between the enrollment and recognition phases. A new online training method is proposed in this paper to improve robustness of speaker recognition in noisy conditions. An estimate of the signal to noise ratio and the emulated ambient noise spectral profile found in the silence intervals of the speech signal are used to re-enroll the reference model for a claimed speaker to generate a new noisy reference model. The proposed online training method has been examined and validated using an MFCC-GMM UBM based speaker recognition system. Results show significant improvement in performance |
| المستخلص باللغة العربية : | |
| كلمات مفتاحية : | |
| الرابط : | DOI: https://doi.org/10.17743/jaes.2019.0004 |
