Abstract
Speaker Identification (SI) is a process of identifying a speaker automatically via a machine using the speaker’s voice. In SI, one speaker’s voice is compared with n- number of speakers’ templates within the reference database to find the best match among the potential speakers. Speakers are capable of changing their voice, though, such as their accent, which makes is more challenging to identify who is talking. In this paper, we extracted phonemes from a speaker’s voice recording and investigated the associated frequencies and amplitudes to be assist in identifying the person who is speaking. This paper demonstrates the importance of phonemes in both speech and voice recognition systems. The results demonstrate that we can use phonemes to help the machine identify a particular speaker, however, phonemes get better accuracy in speech recognition than speaker identification.
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Kinkiri, S., Barakat, B., Keates, S. (2020). Phonemes: An Explanatory Study Applied to Identify a Speaker. In: Bhattacharjee, A., Borgohain, S., Soni, B., Verma, G., Gao, XZ. (eds) Machine Learning, Image Processing, Network Security and Data Sciences. MIND 2020. Communications in Computer and Information Science, vol 1241. Springer, Singapore. https://doi.org/10.1007/978-981-15-6318-8_6
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DOI: https://doi.org/10.1007/978-981-15-6318-8_6
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