{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,18]],"date-time":"2025-12-18T08:44:07Z","timestamp":1766047447699},"reference-count":55,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T00:00:00Z","timestamp":1642636800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T00:00:00Z","timestamp":1642636800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s00521-021-06678-0","type":"journal-article","created":{"date-parts":[[2022,1,20]],"date-time":"2022-01-20T00:03:46Z","timestamp":1642637026000},"page":"4875-4888","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Development of accurate automated language identification model using polymer pattern and tent maximum absolute pooling techniques"],"prefix":"10.1007","volume":"34","author":[{"given":"Turker","family":"Tuncer","sequence":"first","affiliation":[]},{"given":"Sengul","family":"Dogan","sequence":"additional","affiliation":[]},{"given":"Erhan","family":"Akbal","sequence":"additional","affiliation":[]},{"given":"Abdullah","family":"Cicekli","sequence":"additional","affiliation":[]},{"given":"U.","family":"Rajendra Acharya","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,20]]},"reference":[{"key":"6678_CR1","doi-asserted-by":"crossref","unstructured":"Rosenthal S, Atanasova P, Karadzhov G, Zampieri M, Nakov P (2020) A large-scale semi-supervised dataset for offensive language identification. arXiv preprint","DOI":"10.18653\/v1\/2021.findings-acl.80"},{"key":"6678_CR2","doi-asserted-by":"publisher","first-page":"444","DOI":"10.1016\/j.protcy.2012.02.099","volume":"1","author":"H Tak\u00e7i","year":"2012","unstructured":"Tak\u00e7i H, Ekinci E (2012) Minimal feature set in language identification and finding suitable classification method with it. Procedia Technol 1:444\u2013448","journal-title":"Procedia Technol"},{"key":"6678_CR3","doi-asserted-by":"publisher","first-page":"106440","DOI":"10.1016\/j.knosys.2020.106440","volume":"209","author":"V Habic","year":"2020","unstructured":"Habic V, Semenov A, Pasiliao EL (2020) Multitask deep learning for native language identification. Knowl Based Syst 209:106440","journal-title":"Knowl Based Syst"},{"key":"6678_CR4","doi-asserted-by":"publisher","first-page":"182868","DOI":"10.1109\/ACCESS.2020.3028121","volume":"8","author":"S Guha","year":"2020","unstructured":"Guha S, Das A, Singh PK, Ahmadian A, Senu N, Sarkar R (2020) Hybrid feature selection method based on harmony search and naked mole-rat algorithms for spoken language identification from audio signals. IEEE Access 8:182868\u2013182887","journal-title":"IEEE Access"},{"issue":"1","key":"6678_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13042-019-00928-3","volume":"11","author":"H Mukherjee","year":"2020","unstructured":"Mukherjee H, Obaidullah SM, Santosh K, Phadikar S, Roy K (2020) A lazy learning-based language identification from speech using MFCC-2 features. Int J Mach Learn Cybern 11(1):1\u201314","journal-title":"Int J Mach Learn Cybern"},{"key":"6678_CR6","doi-asserted-by":"crossref","unstructured":"Abdullah B, Avgustinova T, M\u00f6bius B, Klakow D (2020) Cross-domain adaptation of spoken language identification for related languages: the curious case of slavic languages. arXiv preprint","DOI":"10.21437\/Interspeech.2020-2930"},{"key":"6678_CR7","doi-asserted-by":"publisher","first-page":"2674","DOI":"10.1109\/TASLP.2020.3023627","volume":"28","author":"P Shen","year":"2020","unstructured":"Shen P, Lu X, Li S, Kawai H (2020) Knowledge distillation-based representation learning for short-utterance spoken language identification. IEEE\/ACM Trans Audio Speech Lang Process 28:2674\u20132683","journal-title":"IEEE\/ACM Trans Audio Speech Lang Process"},{"key":"6678_CR8","unstructured":"Hughes B, Baldwin T, Bird S, Nicholson J, MacKinlay A (2006) Reconsidering language identification for written language resources"},{"issue":"1","key":"6678_CR9","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1109\/TASL.2006.876860","volume":"15","author":"H Li","year":"2006","unstructured":"Li H, Ma B, Lee C-H (2006) A vector space modeling approach to spoken language identification. IEEE Trans Audio Speech Lang Process 15(1):271\u2013284","journal-title":"IEEE Trans Audio Speech Lang Process"},{"key":"6678_CR10","unstructured":"Tong R, Ma B, Zhu D, Li H, Chng ES (2006) Integrating acoustic, prosodic and phonotactic features for spoken language identification. In: 2006 IEEE international conference on acoustics speech and signal processing proceedings. IEEE, pp I-I"},{"key":"6678_CR11","doi-asserted-by":"crossref","unstructured":"Teixeira C, Trancoso I, Serralheiro A (1996) Accent identification. In: proceeding of fourth international conference on spoken language processing. ICSLP'96. IEEE, pp 1784\u20131787","DOI":"10.1109\/ICSLP.1996.607975"},{"key":"6678_CR12","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1016\/j.specom.2018.04.004","volume":"100","author":"S Irtza","year":"2018","unstructured":"Irtza S, Sethu V, Ambikairajah E, Li H (2018) Using language cluster models in hierarchical language identification. Speech Commun 100:30\u201340","journal-title":"Speech Commun"},{"key":"6678_CR13","doi-asserted-by":"publisher","first-page":"364","DOI":"10.1016\/j.csl.2019.05.006","volume":"58","author":"J Monteiro","year":"2019","unstructured":"Monteiro J, Alam J, Falk TH (2019) Residual convolutional neural network with attentive feature pooling for end-to-end language identification from short-duration speech. Comput Speech Lang 58:364\u2013376","journal-title":"Comput Speech Lang"},{"key":"6678_CR14","doi-asserted-by":"publisher","first-page":"107562","DOI":"10.1016\/j.neuropsychologia.2020.107562","volume":"146","author":"J Xue","year":"2020","unstructured":"Xue J, Li B, Yan R, Gruen JR, Feng T, Joanisse MF, Malins JG (2020) The temporal dynamics of first and second language processing: ERPs to spoken words in Mandarin-English bilinguals. Neuropsychologia 146:107562","journal-title":"Neuropsychologia"},{"key":"6678_CR15","doi-asserted-by":"publisher","first-page":"101142","DOI":"10.1016\/j.csl.2020.101142","volume":"66","author":"J Poncelet","year":"2020","unstructured":"Poncelet J, Renkens V (2020) Low resource end-to-end spoken language understanding with capsule networks. Comput Speech Lang 66:101142","journal-title":"Comput Speech Lang"},{"key":"6678_CR16","doi-asserted-by":"publisher","first-page":"107289","DOI":"10.1016\/j.apacoust.2020.107289","volume":"164","author":"D Deshwal","year":"2020","unstructured":"Deshwal D, Sangwan P, Kumar D (2020) A language identification system using hybrid features and back-propagation neural network. Appl Acoust 164:107289","journal-title":"Appl Acoust"},{"issue":"6","key":"6678_CR17","doi-asserted-by":"publisher","first-page":"84","DOI":"10.1145\/3065386","volume":"60","author":"A Krizhevsky","year":"2017","unstructured":"Krizhevsky A, Sutskever I, Hinton GE (2017) Imagenet classification with deep convolutional neural networks. Commun ACM 60(6):84\u201390","journal-title":"Commun ACM"},{"key":"6678_CR18","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.eswa.2018.06.031","volume":"113","author":"S Raghu","year":"2018","unstructured":"Raghu S, Sriraam N (2018) Classification of focal and non-focal EEG signals using neighborhood component analysis and machine learning algorithms. Expert Syst Appl 113:18\u201332","journal-title":"Expert Syst Appl"},{"key":"6678_CR19","unstructured":"Montavon G (2009) Deep learning for spoken language identification. In: NIPS workshop on deep learning for speech recognition and related applications. Citeseer, pp 1\u20134"},{"key":"6678_CR20","unstructured":"VoxForge (2020) VoxForge, free speech recognition, www.voxforge.org"},{"key":"6678_CR21","doi-asserted-by":"crossref","unstructured":". Lounnas K, Abbas M, Teffahi H, Lichouri M (2019) A language identification system based on voxforge speech corpus. In: international conference on advanced machine learning technologies and applications. Springer, pp 529-534","DOI":"10.1007\/978-3-030-14118-9_53"},{"key":"6678_CR22","unstructured":"Kumar P, Biswas A, Mishra AN, Chandra M (2010) Spoken language identification using hybrid feature extraction methods. arXiv preprint"},{"key":"6678_CR23","doi-asserted-by":"publisher","first-page":"106243","DOI":"10.1016\/j.knosys.2020.106243","volume":"205","author":"H Cui","year":"2020","unstructured":"Cui H, Liu A, Zhang X, Chen X, Wang K, Chen X (2020) EEG-based emotion recognition using an end-to-end regional-asymmetric convolutional neural network. Knowl Based Syst 205:106243","journal-title":"Knowl Based Syst"},{"key":"6678_CR24","doi-asserted-by":"publisher","first-page":"290","DOI":"10.1016\/j.eswa.2018.06.004","volume":"110","author":"RK Vuddagiri","year":"2018","unstructured":"Vuddagiri RK, Vydana HK, Vuppala AK (2018) Curriculum learning based approach for noise robust language identification using DNN with attention. Expert Syst Appl 110:290\u2013297","journal-title":"Expert Syst Appl"},{"key":"6678_CR25","unstructured":"Mounika K, Achanta S, Lakshmi H, Gangashetty SV, Vuppala AK (2016) An investigation of deep neural network architectures for language recognition in indian languages. In: INTERSPEECH. pp 2930\u20132933"},{"key":"6678_CR26","doi-asserted-by":"crossref","unstructured":"Tang Z, Wang D, Chen Y, Chen Q (2017) AP17-OLR challenge: data, plan, and baseline. In: 2017 Asia-Pacific signal and information processing association annual summit and conference (APSIPA ASC). IEEE, pp 749\u2013753","DOI":"10.1109\/APSIPA.2017.8282134"},{"key":"6678_CR27","doi-asserted-by":"crossref","unstructured":"Wang D, Li L, Tang D, Chen Q (2016) Ap16-ol7: A multilingual database for oriental languages and a language recognition baseline. In: 2016 Asia-Pacific signal and information processing association annual summit and conference (APSIPA). IEEE, pp 1\u20135","DOI":"10.1109\/APSIPA.2016.7820796"},{"issue":"3","key":"6678_CR28","doi-asserted-by":"publisher","first-page":"509","DOI":"10.1007\/s10772-017-9482-5","volume":"21","author":"AK Dutta","year":"2018","unstructured":"Dutta AK, Rao KS (2018) Language identification using phase information. Int J Speech Technol 21(3):509\u2013519","journal-title":"Int J Speech Technol"},{"key":"6678_CR29","doi-asserted-by":"crossref","unstructured":"Maity S, Vuppala AK, Rao KS, Nandi D (2012) IITKGP-MLILSC speech database for language identification. In: 2012 national conference on communications (NCC). IEEE, pp 1\u20135","DOI":"10.1109\/NCC.2012.6176831"},{"key":"6678_CR30","doi-asserted-by":"crossref","unstructured":"Muthusamy YK, Cole RA, Oshika BT (1992) The OGI multi-language telephone speech corpus. In: second international conference on spoken language processing","DOI":"10.21437\/ICSLP.1992-276"},{"key":"6678_CR31","doi-asserted-by":"crossref","unstructured":"Tang Z, Wang D, Song L (2019) AP19-OLR Challenge: three tasks and their baselines. In: 2019 Asia-pacific signal and information processing association annual summit and conference (APSIPA ASC), IEEE, pp 1917\u20131921","DOI":"10.1109\/APSIPAASC47483.2019.9023321"},{"key":"6678_CR32","unstructured":"Revay S, Teschke M (2019) Multiclass language identification using deep learning on spectral images of audio signals. arXiv preprint"},{"issue":"5","key":"6678_CR33","doi-asserted-by":"publisher","first-page":"2266","DOI":"10.1007\/s00034-018-0962-x","volume":"38","author":"CC Bhanja","year":"2019","unstructured":"Bhanja CC, Laskar MA, Laskar RH (2019) A pre-classification-based language identification for Northeast Indian languages using prosody and spectral features. Circuits Syst Signal Process 38(5):2266\u20132296","journal-title":"Circuits Syst Signal Process"},{"issue":"11","key":"6678_CR34","doi-asserted-by":"publisher","first-page":"3187","DOI":"10.1364\/OSAC.405929","volume":"3","author":"M Baba","year":"2020","unstructured":"Baba M, Imamura T, Hoshikawa N, Nakayama H, Ito T, Shiraki A (2020) Development of a multilingual digital signage system using a directional volumetric display and language identification. OSA Continuum 3(11):3187\u20133196","journal-title":"OSA Continuum"},{"key":"6678_CR35","doi-asserted-by":"crossref","unstructured":"Blanchard D, Tetreault J, Higgins D, Cahill A, Chodorow M (2013) TOEFL11: A corpus of non\u2010native English. ETS Research Report Series 2013 (2):i-15","DOI":"10.1002\/j.2333-8504.2013.tb02331.x"},{"key":"6678_CR36","volume-title":"International corpus of learner english, (ICLE)","author":"S Granger","year":"2002","unstructured":"Granger S, Dagneaux E, Meunier F, Paquot M (2002) International corpus of learner english, (ICLE). Presses Universitaires de Louvain, Louvain-la-Neuve"},{"key":"6678_CR37","doi-asserted-by":"publisher","first-page":"113575","DOI":"10.1016\/j.eswa.2020.113575","volume":"158","author":"G Yasmin","year":"2020","unstructured":"Yasmin G, Das AK, Nayak J, Pelusi D, Ding W (2020) Graph based feature selection investigating boundary region of rough set for language identification. Expert Syst Appl 158:113575","journal-title":"Expert Syst Appl"},{"issue":"4","key":"6678_CR38","doi-asserted-by":"publisher","first-page":"489","DOI":"10.1007\/s10772-013-9198-0","volume":"16","author":"VR Reddy","year":"2013","unstructured":"Reddy VR, Maity S, Rao KS (2013) Identification of Indian languages using multi-level spectral and prosodic features. Int J Speech Technol 16(4):489\u2013511","journal-title":"Int J Speech Technol"},{"key":"6678_CR39","doi-asserted-by":"crossref","unstructured":"Sisodia DS, Nikhil S, Kiran GS, Sathvik P (2020) Ensemble learners for identification of spoken languages using mel frequency cepstral coefficients. In: 2nd international conference on data, engineering and applications (IDEA). IEEE, pp 1\u20135","DOI":"10.1109\/IDEA49133.2020.9170720"},{"key":"6678_CR40","doi-asserted-by":"crossref","unstructured":"Verma M, Buduru AB (2020) Fine-grained language identification with multilingual capsNet Model. In: 2020 IEEE sixth international conference on multimedia big data (BigMM), IEEE, pp 94\u2013102","DOI":"10.1109\/BigMM50055.2020.00023"},{"issue":"4k","key":"6678_CR41","first-page":"10k","volume":"37","author":"W Hou","year":"2020","unstructured":"Hou W, Dong Y, Zhuang B, Yang L, Shi J, Shinozaki T (2020) Large-scale end-to-end multilingual speech recognition and language identification with multi-task learning. Babel 37(4k):10k","journal-title":"Babel"},{"key":"6678_CR42","doi-asserted-by":"crossref","unstructured":"Fan W, Ma Y, Li Q, He Y, Zhao E, Tang J, Yin D (2019) Graph neural networks for social recommendation. In: The World Wide Web Conference, pp 417\u2013426","DOI":"10.1145\/3308558.3313488"},{"key":"6678_CR43","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3054830","author":"FM Bianchi","year":"2021","unstructured":"Bianchi FM, Grattarola D, Livi L, Alippi C (2021) Graph neural networks with convolutional arma filters. IEEE Trans Pattern Anal Mach Intell. https:\/\/doi.org\/10.1109\/TPAMI.2021.3054830","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"6678_CR44","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1109\/TSP.2018.2879624","volume":"67","author":"R Levie","year":"2018","unstructured":"Levie R, Monti F, Bresson X, Bronstein MM (2018) Cayleynets: graph convolutional neural networks with complex rational spectral filters. IEEE Trans Signal Process 67(1):97\u2013109","journal-title":"IEEE Trans Signal Process"},{"issue":"6","key":"6678_CR45","doi-asserted-by":"publisher","first-page":"884","DOI":"10.1109\/JSTSP.2017.2726981","volume":"11","author":"FP Such","year":"2017","unstructured":"Such FP, Sah S, Dominguez MA, Pillai S, Zhang C, Michael A, Cahill ND, Ptucha R (2017) Robust spatial filtering with graph convolutional neural networks. IEEE J Sel Top Signal Process 11(6):884\u2013896","journal-title":"IEEE J Sel Top Signal Process"},{"key":"6678_CR46","unstructured":"Vries RD (2021) Perspective on AlphaFold 2 and advances in computational protein folding predictions."},{"key":"6678_CR47","doi-asserted-by":"publisher","first-page":"107607","DOI":"10.1016\/j.apacoust.2020.107607","volume":"172","author":"T Tuncer","year":"2021","unstructured":"Tuncer T (2021) A new stable nonlinear textural feature extraction method based EEG signal classification method using substitution Box of the Hamsi hash function: Hamsi pattern. Appl Acoust 172:107607","journal-title":"Appl Acoust"},{"key":"6678_CR48","doi-asserted-by":"publisher","first-page":"84532","DOI":"10.1109\/ACCESS.2020.2992641","volume":"8","author":"T Tuncer","year":"2020","unstructured":"Tuncer T, Dogan S, \u00d6zyurt F, Belhaouari SB, Bensmail H (2020) Novel multi center and threshold ternary pattern based method for disease detection method using voice. IEEE Access 8:84532\u201384540","journal-title":"IEEE Access"},{"key":"6678_CR49","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.knosys.2016.06.012","volume":"117","author":"J Maillo","year":"2017","unstructured":"Maillo J, Ram\u00edrez S, Triguero I, Herrera F (2017) kNN-IS: an Iterative Spark-based design of the k-Nearest Neighbors classifier for big data. Knowl-Based Syst 117:3\u201315","journal-title":"Knowl-Based Syst"},{"key":"6678_CR50","doi-asserted-by":"crossref","unstructured":"Zhao W, Chellappa R, Nandhakumar N (1998) Empirical performance analysis of linear discriminant classifiers. In: Proceedings. 1998 IEEE computer society conference on computer vision and pattern recognition (Cat. No. 98CB36231), IEEE, pp 164\u2013169","DOI":"10.1109\/CVPR.1998.698604"},{"key":"6678_CR51","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/978-1-4615-5703-6_3","volume-title":"Nonlinear modeling","author":"V Vapnik","year":"1998","unstructured":"Vapnik V (1998) The support vector method of function estimation. In: Suykens JAK, Vandewalle J (eds) Nonlinear modeling. Springer, pp 55\u201385"},{"key":"6678_CR52","volume-title":"The nature of statistical learning theory","author":"V Vapnik","year":"2013","unstructured":"Vapnik V (2013) The nature of statistical learning theory. Springer science & business media"},{"key":"6678_CR53","doi-asserted-by":"publisher","first-page":"104923","DOI":"10.1016\/j.knosys.2019.104923","volume":"186","author":"T Tuncer","year":"2019","unstructured":"Tuncer T, Dogan S, P\u0142awiak P, Acharya UR (2019) Automated arrhythmia detection using novel hexadecimal local pattern and multilevel wavelet transform with ECG signals. Knowl Based Syst 186:104923","journal-title":"Knowl Based Syst"},{"issue":"1","key":"6678_CR54","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1186\/s12864-019-6413-7","volume":"21","author":"D Chicco","year":"2020","unstructured":"Chicco D, Jurman G (2020) The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation. BMC Genomics 21(1):6","journal-title":"BMC Genomics"},{"issue":"2","key":"6678_CR55","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/s00357-008-9023-7","volume":"25","author":"MJ Warrens","year":"2008","unstructured":"Warrens MJ (2008) On the equivalence of Cohen\u2019s kappa and the Hubert-Arabie adjusted Rand index. J Classif 25(2):177\u2013183","journal-title":"J Classif"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06678-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06678-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06678-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T20:27:29Z","timestamp":1674505649000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06678-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,20]]},"references-count":55,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["6678"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06678-0","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,20]]},"assertion":[{"value":"8 January 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 October 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors confirm that this article content has no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}