{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,16]],"date-time":"2025-10-16T06:58:05Z","timestamp":1760597885072,"version":"3.37.3"},"reference-count":40,"publisher":"World Scientific Pub Co Pte Ltd","issue":"06","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2020,6,15]]},"abstract":"<jats:p> Speech recognition in multilingual scenario is not trivial in the case when multiple languages are used in one conversation. Language must be identified before we process speech recognition as such tools are language-dependent. We present a language identification system (or AI tool) to distinguish top-seven world languages namely Chinese, Spanish, English, Hindi, Arabic, Bangla and Portuguese [G. F. Simons and C. D. Fennig (eds.), Ethnologue: Laguage of the Americas and the Pacific, Twentieth Edn. (SIL Internatinal, 2017)]. The system uses linear predictive coefficients-based feature, i.e. the line spectral pair\u2013grade ratio (LSP\u2013GR) feature, and ensemble learning for classification. Experiments were performed on more than 200[Formula: see text]h of real-world YouTube data and the highest possible accuracy of 96.95% was received. The results can be compared with other machine learning classifiers. <\/jats:p>","DOI":"10.1142\/s0218001420580069","type":"journal-article","created":{"date-parts":[[2019,7,19]],"date-time":"2019-07-19T08:42:30Z","timestamp":1563525750000},"page":"2058006","source":"Crossref","is-referenced-by-count":11,"title":["Linear Predictive Coefficients-Based Feature to Identify Top-Seven Spoken Languages"],"prefix":"10.1142","volume":"34","author":[{"given":"Himadri","family":"Mukherjee","sequence":"first","affiliation":[{"name":"Department of Computer Science, West Bengal State University, Kolkata 700126, West Bengal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ankita","family":"Dhar","sequence":"additional","affiliation":[{"name":"Department of Computer Science, West Bengal State University, Kolkata 700126, West Bengal, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sk. 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