Abstract
Nowadays, most of the mobile and handheld devices use speech and speaker verification systems (SVS). Even though these systems give satisfactory performance in constrained conditions, there are a number of real-life unconstrained conditions where their performance is not satisfactory. Such SVS cannot accurately authenticate a person when deployed in applications where varying environmental or channel conditions. The actual conditions may be very much different than those used during system training. This creates a large uncertainty in verification scores obtained during evaluation phase of the system. In this regard, we have implemented a verification system using state of the art i-vector-based approach. It is based on total variability subspace (TVS) that benefits in modeling both session and channel variabilities using a single low-dimensional space instead of two different subspaces. Our experiments are conducted using the data taken from speakers in the wild (SITW) database, and the equal error rate (EER) value we have obtained is 23.16%.
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Nirmal, A., Jayaswal, D. (2023). Investigating i-Vector Framework for Speaker Verification in Wild Conditions. In: Choudrie, J., Mahalle, P., Perumal, T., Joshi, A. (eds) IOT with Smart Systems. Smart Innovation, Systems and Technologies, vol 312. Springer, Singapore. https://doi.org/10.1007/978-981-19-3575-6_13
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DOI: https://doi.org/10.1007/978-981-19-3575-6_13
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