Abstract
Speaker verification systems based on multilayer perceptrons (MLPs) have good prospects in reliability and flexibility as required for a successful authentication system. However, poor learning speed of error backpropagation (EBP), the representative method of learning for MLPs, has been the major problem which must be resolved to achieve real-time user enrollment. In this paper, we implement an MLP-based speaker verification system by applying methods of omitting patterns in instant learning (OIL) and discriminative cohort speakers (DCS) to approach the real-time enrollment. We evaluate the system on a Korean speech database and demonstrate the feasibility of it as a speaker verification system of high performance.
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Lee, TS., Choi, HJ. (2004). High Performance Speaker Verification System Based on Multilayer Perceptrons and Real-Time Enrollment. In: Zhang, D., Jain, A.K. (eds) Biometric Authentication. ICBA 2004. Lecture Notes in Computer Science, vol 3072. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25948-0_85
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DOI: https://doi.org/10.1007/978-3-540-25948-0_85
Publisher Name: Springer, Berlin, Heidelberg
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