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Review Papers | Forensic Science | India | Volume 11 Issue 5, May 2022 | Rating: 5 / 10
Detection of Ethno-Lingual Identity Using AI & ML
Nikhil Chandra Yadav | Aditya Saini | Vinny Sharma
Abstract: Ethnolinguistic distinguishing proof could be a subjective sense of having a place or affiliation with a social gather characterized by comparable ethnic legacy and dialect differences. According to ethnolinguistic identity theory, people utilize communication accommodation methods such as verbal and nonverbal convergence to or divergence from their communication partner to stress affiliation or disaffiliation. These microlevel intergroup interactions have large-scale, macrolevel ramifications for language preservation and shift. Related theories highlight the relevance of ethnolinguistic identity in the acquisition of communicative competence in foreign languages and the process of ethnolinguistic group acculturation. Recent conceptualizations of bicultural and situational identities point to future study avenues by relying on developmental, socio-cognitive, and cultural psychology, as well as language acquisition psychology. Machine intelligence is referred to as Artificial Intelligence. It is the replication of natural intelligence in robots that have been programmed to learn and emulate human behavior. Machine learning, on the other hand, is used in internet search engines, email filters to filter out spam, websites to provide tailored recommendations, banking software to identify anomalous transactions, and many apps on our phones, such as voice recognition.
Keywords: Ethno-lingual identification, Artificial Intelligence, Machine Learning, Forensic Science
Edition: Volume 11 Issue 5, May 2022,
Pages: 552 - 555