Abstract
In the prevailing period of innovation the automatic identification of speaker assumes a significant role. The application of speaker recognition is spin towards Biometric security. This paper depicted a speaker recognition framework for isolated word dataset. The feature extraction has been finished utilizing Mel Frequency Cepstral Coefficient (MFCC) techniques. The database of the research is structure and creates utilizing 25 Male and 25 Female speakers. The size of dataset is 2500 isolated words. The content for the dataset recording is chosen based on vowel letters in order. The execution of the framework is determined utilizing False Rejection Rate (FRR), False Acceptance Rate (FAR). The precision of the Speaker Recognition rate for Male is better as compare with the exactness of female. This structure is utilized for speaker recognition framework for the confined word distinguishing proof framework by applying highlight extraction methods as MFCC and arrangement is finished with Euclidian Distance. We got a normal exactness for Male rate is 85% and 81% for female. The exhibition of the haphazardly chosen subject gathering was 79%. This is the general precision pace of Speaker Recognition framework for Marathi Isolated Words.
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Kamble, P. et al. (2021). Automatic Speech Processing of Marathi Speaker İdentification for Isolated Words System. In: Santosh, K.C., Gawali, B. (eds) Recent Trends in Image Processing and Pattern Recognition. RTIP2R 2020. Communications in Computer and Information Science, vol 1381. Springer, Singapore. https://doi.org/10.1007/978-981-16-0493-5_30
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DOI: https://doi.org/10.1007/978-981-16-0493-5_30
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