Abstract
Human voices are one of the easiest ways to communicate information between humans. Voice characteristics may vary from person to person and include voice rate, gentle form and function, pitch tone, language habits, and gender. Human voices are a key element of human communication. In the era of the Fourth Industrial Revolution, the voices are the main means of communication between people and people, between humans and machines, machines and machines. And for that reason, people are trying to communicate their intent clearly to others. In the process, language information and various additional information are included. Information such as emotional state, health status, reliability, presence of lies, changes due to alcohol, etc. These languages and non-linguistic information can be used as a device to assess the lie of telephone voices that appear as various parameters. Especially, it can be obtained by analyzing the relationship between the characteristics of the fundamental frequency (fundamental tone) of the vocal cords and the resonance frequency characteristics of vocal tracks. Previous studies have extracted parameters for false testimony of various telephone voices and conducted this study to evaluate whether a telephone voice is a lie. In this study, we proposed a judge to judge whether a lie is true by using a support vector machine. We propose a personal telephone truth discriminator.
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Park, H. (2020). A Study on the Faith Score of Telephone Voices Using Machine Learning. In: Lee, R. (eds) Applied Computing and Information Technology. ACIT 2019. Studies in Computational Intelligence, vol 847. Springer, Cham. https://doi.org/10.1007/978-3-030-25217-5_6
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DOI: https://doi.org/10.1007/978-3-030-25217-5_6
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