speaker model updating by the conversational sounds in speaker verification
Recent advancements in information technology have enabled handheld devices to process many types of information. Most security locks used in these devices are managed through the use of a password. However, this feature has attracted only a few users because conventional security is generally viewed as troublesome. Speaker verification is a possible alternative because it offers a feature that converts the user's password into a security lock. Because this is a unobtrusive user certification method, it is less cumbersome for the user. However, speaker verification is not robust to changes in the user's voices. Therefore, in this study, we propose to update the speaker model used for speaker verification in smart-phones. The sound samples comprise Japanese phoneme-balanced sentences recorded from 20 speakers over a 1-month period. The speaker models are updated by putting an old sound sample and a new sound sample together. As a result of the model update, the equal error rate (EER) decreases from 9.84\% to 5.46\%, representing a drop of approximately 44.52\%.
biometrie security speech processing speaker verification system gaussian mixture model mobile security