{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T12:18:01Z","timestamp":1766578681320,"version":"3.37.3"},"reference-count":60,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2021,1,22]],"date-time":"2021-01-22T00:00:00Z","timestamp":1611273600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,22]],"date-time":"2021-01-22T00:00:00Z","timestamp":1611273600000},"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":["Int J Speech Technol"],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1007\/s10772-021-09795-2","type":"journal-article","created":{"date-parts":[[2021,1,22]],"date-time":"2021-01-22T03:02:37Z","timestamp":1611284557000},"page":"389-400","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Convolutional neural network vectors for speaker recognition"],"prefix":"10.1007","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6349-4560","authenticated-orcid":false,"given":"Soufiane","family":"Hourri","sequence":"first","affiliation":[]},{"given":"Nikola S.","family":"Nikolov","sequence":"additional","affiliation":[]},{"given":"Jamal","family":"Kharroubi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,1,22]]},"reference":[{"key":"9795_CR1","doi-asserted-by":"crossref","unstructured":"Agrawal, P., Kapoor, R., & Agrawal, S. (2014). A hybrid partial fingerprint matching algorithm for estimation of equal error rate. 2014 IEEE International Conference on Advanced Communications (pp. 1295\u20131299). IEEE: Control and Computing Technologies.","DOI":"10.1109\/ICACCCT.2014.7019308"},{"key":"9795_CR2","unstructured":"Amodei D, Ananthanarayanan S, Anubhai R, Bai J, Battenberg E, Case C, Casper J, Catanzaro B, Cheng Q, Chen G, et\u00a0al. (2016) Deep speech 2: End-to-end speech recognition in english and mandarin. In: International conference on machine learning, pp 173\u2013182"},{"issue":"1","key":"9795_CR3","first-page":"2320","volume":"6","author":"L Basyal","year":"2018","unstructured":"Basyal, L., Kaushal, S., & Singh, G. (2018). Voice recognition robot with real time surveillance and automation. International Journal of Creative Research Thoughts, 6(1), 2320\u20132882.","journal-title":"International Journal of Creative Research Thoughts"},{"key":"9795_CR4","unstructured":"Bennani, Y., & Gallinari, P . (1994) . Connectionist approaches for automatic speaker recognition. In: Automatic Speaker Recognition, Identification and Verification."},{"key":"9795_CR5","doi-asserted-by":"crossref","unstructured":"Bouziane, A., Kadi, H., Hourri, S., & Kharroubi, J . (2016). An open and free speech corpus for speaker recognition: The fscsr speech corpus. In: 2016 11th International Conference on Intelligent Systems: Theories and Applications (SITA), IEEE, pp 1\u20135","DOI":"10.1109\/SITA.2016.7772320"},{"key":"9795_CR6","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1016\/j.ejca.2019.02.005","volume":"111","author":"TJ Brinker","year":"2019","unstructured":"Brinker, T. J., Hekler, A., Enk, A. H., Klode, J., Hauschild, A., Berking, C., et al. (2019). A convolutional neural network trained with dermoscopic images performed on par with 145 dermatologists in a clinical melanoma image classification task. European Journal of Cancer, 111, 148\u2013154.","journal-title":"European Journal of Cancer"},{"issue":"9","key":"9795_CR7","doi-asserted-by":"publisher","first-page":"7048","DOI":"10.1109\/TGRS.2019.2910603","volume":"57","author":"Y Chen","year":"2019","unstructured":"Chen, Y., Zhu, K., Zhu, L., He, X., Ghamisi, P., & Benediktsson, J. A. (2019). Automatic design of convolutional neural network for hyperspectral image classification. IEEE Transactions on Geoscience and Remote Sensing, 57(9), 7048\u20137066.","journal-title":"IEEE Transactions on Geoscience and Remote Sensing"},{"key":"9795_CR8","unstructured":"Chen, Yh., Lopez-Moreno, I., Sainath, TN., Visontai, M., Alvarez, R., & Parada, C . (2015). Locally-connected and convolutional neural networks for small footprint speaker recognition. In: Sixteenth Annual Conference of the International Speech Communication Association."},{"key":"9795_CR9","unstructured":"Choi, SS., Cha, SH., & Tappert, CC .(2010) . A survey of binary similarity and distance measures. Journal of Systemics, Cybernetics and Informatics pp 43\u201348."},{"key":"9795_CR10","doi-asserted-by":"crossref","unstructured":"Chung, JS., Nagrani, A., & Zisserman, A . (2018) . Voxceleb2: Deep speaker recognition. arXiv preprint arXiv:180605622.","DOI":"10.21437\/Interspeech.2018-1929"},{"issue":"4","key":"9795_CR11","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1007\/BF02551274","volume":"2","author":"G Cybenko","year":"1989","unstructured":"Cybenko, G. (1989). Approximation by superpositions of a sigmoidal function. Mathematics of Control, Signals and Systems, 2(4), 303\u2013314.","journal-title":"Mathematics of Control, Signals and Systems"},{"key":"9795_CR12","doi-asserted-by":"crossref","unstructured":"Deng, L .(2014). A tutorial survey of architectures, algorithms, and applications for deep learning. In: APSIPA Transactions on Signal and Information Processing 3.","DOI":"10.1017\/ATSIP.2014.4"},{"key":"9795_CR13","doi-asserted-by":"crossref","unstructured":"Deng, L., Hinton, G., & Kingsbury, B. (2013). New types of deep neural network learning for speech recognition and related applications: An overview. 2013 IEEE International Conference on Acoustics (pp. 8599\u20138603). IEEE: Speech and Signal Processing.","DOI":"10.1109\/ICASSP.2013.6639344"},{"issue":"3\u20134","key":"9795_CR14","doi-asserted-by":"publisher","first-page":"411","DOI":"10.1016\/0167-6393(93)90039-N","volume":"13","author":"ME Forsyth","year":"1993","unstructured":"Forsyth, M. E., Sutherland, A. M., Elliott, J., & Jack, M. A. (1993). Hmm speaker verification with sparse training data on telephone quality speech. Speech Communication, 13(3\u20134), 411\u2013416.","journal-title":"Speech Communication"},{"issue":"14\u201315","key":"9795_CR15","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1016\/S1352-2310(97)00447-0","volume":"32","author":"MW Gardner","year":"1998","unstructured":"Gardner, M. W., & Dorling, S. (1998). Artificial neural networks (the multilayer perceptron): A review of applications in the atmospheric sciences. Atmospheric Environment, 32(14\u201315), 2627\u20132636.","journal-title":"Atmospheric Environment"},{"issue":"4","key":"9795_CR16","first-page":"9","volume":"1","author":"MR Hasan","year":"2004","unstructured":"Hasan, M. R., Jamil, M., Rahman, M., et al. (2004). Speaker identification using MEL frequency cepstral coefficients. Variations, 1(4), 9.","journal-title":"Variations"},{"key":"9795_CR17","doi-asserted-by":"crossref","unstructured":"Hinton, G., Deng, L., Yu, D., Dahl, G., Mohamed, Ar., Jaitly, N., Senior, A., Vanhoucke, V., Nguyen, P., & Kingsbury, B., et\u00a0al. (2012). Deep neural networks for acoustic modeling in speech recognition. IEEE Signal processing magazine 29.","DOI":"10.1109\/MSP.2012.2205597"},{"key":"9795_CR18","doi-asserted-by":"crossref","unstructured":"Hinton, GE. (2012). A practical guide to training restricted Boltzmann machines. In: Neural networks: Tricks of the trade, Springer, pp 599\u2013619.","DOI":"10.1007\/978-3-642-35289-8_32"},{"issue":"7","key":"9795_CR19","doi-asserted-by":"publisher","first-page":"1527","DOI":"10.1162\/neco.2006.18.7.1527","volume":"18","author":"GE Hinton","year":"2006","unstructured":"Hinton, G. E., Osindero, S., & Teh, Y. W. (2006). A fast learning algorithm for deep belief nets. Neural Computation, 18(7), 1527\u20131554.","journal-title":"Neural Computation"},{"key":"9795_CR20","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1016\/j.procs.2019.01.068","volume":"148","author":"S Hourri","year":"2019","unstructured":"Hourri, S., & Kharroubi, J. (2019). A novel scoring method based on distance calculation for similarity measurement in text-independent speaker verification. Procedia Computer Science, 148, 256\u2013265.","journal-title":"Procedia Computer Science"},{"issue":"1","key":"9795_CR21","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1007\/s10772-019-09665-y","volume":"23","author":"S Hourri","year":"2020","unstructured":"Hourri, S., & Kharroubi, J. (2020). A deep learning approach for speaker recognition. International Journal of Speech Technology, 23(1), 123\u2013131.","journal-title":"International Journal of Speech Technology"},{"issue":"3","key":"9795_CR22","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1007\/s10772-020-09718-7","volume":"23","author":"S Hourri","year":"2020","unstructured":"Hourri, S., Nikolov, N. S., & Kharroubi, J. (2020). A deep learning approach to integrate convolutional neural networks in speaker recognition. International Journal of Speech Technology, 23(3), 615\u2013623.","journal-title":"International Journal of Speech Technology"},{"issue":"1","key":"9795_CR23","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1080\/02763869.2018.1404391","volume":"37","author":"MB Hoy","year":"2018","unstructured":"Hoy, M. B. (2018). Alexa, Siri, Cortana, and more: An introduction to voice assistants. Medical Reference Services Quarterly, 37(1), 81\u201388.","journal-title":"Medical Reference Services Quarterly"},{"issue":"1","key":"9795_CR24","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1113\/jphysiol.1968.sp008455","volume":"195","author":"DH Hubel","year":"1968","unstructured":"Hubel, D. H., & Wiesel, T. N. (1968). Receptive fields and functional architecture of monkey striate cortex. The Journal of Physiology, 195(1), 215\u2013243.","journal-title":"The Journal of Physiology"},{"key":"9795_CR25","doi-asserted-by":"crossref","unstructured":"Kalchbrenner, N., Grefenstette, E., & Blunsom, P. (2014). A convolutional neural network for modelling sentences. arXiv preprint arXiv:14042188.","DOI":"10.3115\/v1\/P14-1062"},{"key":"9795_CR26","doi-asserted-by":"crossref","unstructured":"Kenny, P., Gupta, V., Stafylakis, T., Ouellet, P., & Alam, J . (2014) . Deep neural networks for extracting baum-welch statistics for speaker recognition. In: Proceeding of the Odyssey, pp 293\u2013298.","DOI":"10.21437\/Odyssey.2014-44"},{"issue":"1","key":"9795_CR27","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.specom.2009.08.009","volume":"52","author":"T Kinnunen","year":"2010","unstructured":"Kinnunen, T., & Li, H. (2010). An overview of text-independent speaker recognition: From features to supervectors. Speech Communication, 52(1), 12\u201340.","journal-title":"Speech Communication"},{"key":"9795_CR28","unstructured":"Krizhevsky, A., Sutskever, I., Hinton, GE. (2012). Imagenet classification with deep convolutional neural networks. In: Advances in neural information processing systems, pp 1097\u20131105."},{"key":"9795_CR29","unstructured":"LeCun, Y., Bengio, Y., et al. (1995). Convolutional networks for images, speech, and time series. The handbook of brain theory and neural networks, 3361(10)."},{"key":"9795_CR30","doi-asserted-by":"crossref","unstructured":"Lee, KF., & Hon, HW. (1988) .Large-vocabulary speaker-independent continuous speech recognition using hmm. In: Acoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on, IEEE, pp 123\u2013126.","DOI":"10.1109\/ICASSP.1988.196527"},{"key":"9795_CR31","doi-asserted-by":"crossref","unstructured":"Lei, Y., Scheffer, N., Ferrer, L., & McLaren, M .(2014) . A novel scheme for speaker recognition using a phonetically-aware deep neural network. In: Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on, IEEE, pp 1695\u20131699.","DOI":"10.1109\/ICASSP.2014.6853887"},{"key":"9795_CR32","unstructured":"Li, C., Ma, X., Jiang, B., Li, X., Zhang, X., Liu, X., Cao, Y., Kannan, A., & Zhu, Z . (2017). Deep speaker: an end-to-end neural speaker embedding system. arXiv preprint arXiv:170502304."},{"key":"9795_CR33","doi-asserted-by":"publisher","first-page":"7907","DOI":"10.1109\/ACCESS.2020.2964048","volume":"8","author":"J Li","year":"2020","unstructured":"Li, J., Sun, M., Zhang, X., & Wang, Y. (2020). Joint decision of anti-spoofing and automatic speaker verification by multi-task learning with contrastive loss. IEEE Access, 8, 7907\u20137915.","journal-title":"IEEE Access"},{"key":"9795_CR34","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.media.2017.07.005","volume":"42","author":"G Litjens","year":"2017","unstructured":"Litjens, G., Kooi, T., Bejnordi, B. E., Setio, A. A. A., Ciompi, F., Ghafoorian, M., et al. (2017). A survey on deep learning in medical image analysis. Medical Image Analysis, 42, 60\u201388.","journal-title":"Medical Image Analysis"},{"key":"9795_CR35","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.specom.2015.07.003","volume":"73","author":"Y Liu","year":"2015","unstructured":"Liu, Y., Qian, Y., Chen, N., Fu, T., Zhang, Y., & Yu, K. (2015). Deep feature for text-dependent speaker verification. Speech Communication, 73, 1\u201313.","journal-title":"Speech Communication"},{"key":"#cr-split#-9795_CR36.1","doi-asserted-by":"crossref","unstructured":"Martinez, J., Perez, H., Escamilla, E., & Suzuki, MM. (2012). Speaker recognition using mel frequency cepstral coefficients (MFCC) and vector quantization","DOI":"10.1109\/CONIELECOMP.2012.6189918"},{"key":"#cr-split#-9795_CR36.2","unstructured":"(VQ) techniques. In: Electrical Communications and Computers (CONIELECOMP), 2012 22nd International Conference on, IEEE, pp 248-251."},{"key":"9795_CR37","doi-asserted-by":"crossref","unstructured":"Mikolov, T., Karafi\u00e1t, M., Burget, L., \u010cernock\u1ef3, J., & Khudanpur, S. (2010). Recurrent neural network based language model. In: Eleventh Annual Conference of the International Speech Communication Association.","DOI":"10.1109\/ICASSP.2011.5947611"},{"key":"9795_CR38","doi-asserted-by":"crossref","unstructured":"Molau, S., Pitz, M., Schluter, R., & Ney, H . (2001) . Computing mel-frequency cepstral coefficients on the power spectrum. In: Acoustics, Speech, and Signal Processing, 2001. Proceedings.(ICASSP\u201901). 2001 IEEE International Conference on, IEEE, vol\u00a01, pp 73\u201376.","DOI":"10.1109\/ICASSP.2001.940770"},{"key":"9795_CR39","unstructured":"Palaz, D., Collobert, R., et al. (2015). Analysis of cnn-based speech recognition system using raw speech as input. Idiap: Tech. Rep."},{"key":"9795_CR40","doi-asserted-by":"crossref","unstructured":"Prasad, NV., & Umesh, S. (2013). Improved cepstral mean and variance normalization using bayesian framework. In: 2013 IEEE Workshop on Automatic Speech Recognition and Understanding, IEEE, pp 156\u2013161.","DOI":"10.1109\/ASRU.2013.6707722"},{"key":"9795_CR41","doi-asserted-by":"crossref","unstructured":"Ravanelli, M., & Bengio, Y. (2018). Speaker recognition from raw waveform with sincnet. In: 2018 IEEE Spoken Language Technology Workshop (SLT), IEEE, pp 1021\u20131028.","DOI":"10.1109\/SLT.2018.8639585"},{"issue":"4","key":"9795_CR42","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1109\/PROC.1976.10158","volume":"64","author":"DR Reddy","year":"1976","unstructured":"Reddy, D. R. (1976). Speech recognition by machine: A review. Proceedings of the IEEE, 64(4), 501\u2013531.","journal-title":"Proceedings of the IEEE"},{"issue":"1\u20133","key":"9795_CR43","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1006\/dspr.1999.0361","volume":"10","author":"DA Reynolds","year":"2000","unstructured":"Reynolds, D. A., Quatieri, T. F., & Dunn, R. B. (2000). Speaker verification using adapted gaussian mixture models. Digital Signal Processing, 10(1\u20133), 19\u201341.","journal-title":"Digital Signal Processing"},{"issue":"10","key":"9795_CR44","doi-asserted-by":"publisher","first-page":"1671","DOI":"10.1109\/LSP.2015.2420092","volume":"22","author":"F Richardson","year":"2015","unstructured":"Richardson, F., Reynolds, D., & Dehak, N. (2015). Deep neural network approaches to speaker and language recognition. IEEE Signal Processing Letters, 22(10), 1671\u20131675.","journal-title":"IEEE Signal Processing Letters"},{"key":"9795_CR45","doi-asserted-by":"crossref","unstructured":"Rozi, A., Wang, D., Zhang, Z., & Zheng, TF. (2015). An open\/free database and benchmark for uyghur speaker recognition. In: Oriental COCOSDA held jointly with 2015 Conference on Asian Spoken Language Research and Evaluation (O-COCOSDA\/CASLRE), 2015 International Conference, IEEE, pp 81\u201385.","DOI":"10.1109\/ICSDA.2015.7357869"},{"key":"9795_CR46","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.specom.2015.04.005","volume":"72","author":"SO Sadjadi","year":"2015","unstructured":"Sadjadi, S. O., & Hansen, J. H. (2015). Mean hilbert envelope coefficients (MHEC) for robust speaker and language identification. Speech Communication, 72, 138\u2013148.","journal-title":"Speech Communication"},{"key":"9795_CR47","doi-asserted-by":"crossref","unstructured":"Sainath, TN., Mohamed, Ar., Kingsbury, B., & Ramabhadran, B. (2013). Deep convolutional neural networks for LVCSR. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, pp 8614\u20138618.","DOI":"10.1109\/ICASSP.2013.6639347"},{"issue":"3","key":"9795_CR48","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3068335","volume":"42","author":"E Schubert","year":"2017","unstructured":"Schubert, E., Sander, J., Ester, M., Kriegel, H. P., & Xu, X. (2017). Dbscan revisited, revisited: Why and how you should (still) use Dbscan. ACM Transactions on Database Systems (TODS), 42(3), 1\u201321.","journal-title":"ACM Transactions on Database Systems (TODS)"},{"key":"9795_CR49","unstructured":"Senoussaoui, M., Dehak, N., Kenny, P., Dehak, R., & Dumouchel, P. (2012). First attempt of boltzmann machines for speaker verification. In: Odyssey 2012-the speaker and language recognition workshop."},{"key":"9795_CR50","unstructured":"Sermanet, P., Chintala, S., & LeCun, Y. (2012). Convolutional neural networks applied to house numbers digit classification. In: Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012), IEEE, pp 3288\u20133291."},{"key":"9795_CR51","doi-asserted-by":"crossref","unstructured":"Shahin, I., & Botros, N .(1998). Speaker identification using dynamic time warping with stress compensation technique. In: Southeastcon\u201998. Proceedings. IEEE, IEEE, pp 65\u201368.","DOI":"10.1109\/SECON.1998.673293"},{"issue":"1","key":"9795_CR52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5120\/2188-2774","volume":"17","author":"S Singh","year":"2011","unstructured":"Singh, S., & Rajan, E. (2011). Vector quantization approach for speaker recognition using MFCC and inverted MFCC. International Journal of Computer Applications, 17(1), 1\u20137.","journal-title":"International Journal of Computer Applications"},{"key":"9795_CR53","doi-asserted-by":"crossref","unstructured":"Skourt, BA., Nikolov, NS., & Majda, A. (2019). Feature-extraction methods for lung-nodule detection: A comparative deep learning study. In: 2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS), IEEE, pp 1\u20136.","DOI":"10.1109\/ISACS48493.2019.9068871"},{"key":"9795_CR54","doi-asserted-by":"crossref","unstructured":"Snyder, D., Garcia-Romero, D., Sell, G., Povey, D., & Khudanpur, S. (2018). X-vectors: Robust dnn embeddings for speaker recognition. 2018 IEEE International Conference on Acoustics (pp. 5329\u20135333). IEEE: Speech and Signal Processing (ICASSP).","DOI":"10.1109\/ICASSP.2018.8461375"},{"issue":"2","key":"9795_CR55","doi-asserted-by":"publisher","first-page":"14","DOI":"10.1002\/j.1538-7305.1987.tb00198.x","volume":"66","author":"FK Soong","year":"1987","unstructured":"Soong, F. K., Rosenberg, A. E., Juang, B. H., & Rabiner, L. R. (1987). Report: A vector quantization approach to speaker recognition. AT&T Technical Journal, 66(2), 14\u201326.","journal-title":"AT&T Technical Journal"},{"key":"9795_CR56","doi-asserted-by":"crossref","unstructured":"Tirumala, SS., & Shahamiri, SR. (2016). A review on deep learning approaches in speaker identification. In: Proceedings of the 8th International Conference on Signal Processing Systems, ACM, pp 142\u2013147.","DOI":"10.1145\/3015166.3015210"},{"key":"9795_CR57","doi-asserted-by":"crossref","unstructured":"T\u00f3th, L. (2014). Combining time-and frequency-domain convolution in convolutional neural network-based phone recognition. 2014 IEEE International Conference on Acoustics (pp. 190\u2013194). IEEE: Speech and Signal Processing (ICASSP).","DOI":"10.1109\/ICASSP.2014.6853584"},{"issue":"3","key":"9795_CR58","doi-asserted-by":"publisher","first-page":"35","DOI":"10.1109\/MCI.2018.2840738","volume":"13","author":"T Young","year":"2018","unstructured":"Young, T., Hazarika, D., Poria, S., & Cambria, E. (2018). Recent trends in deep learning based natural language processing. IEEE Computational Intelligence Magazine, 13(3), 35\u201375.","journal-title":"IEEE Computational Intelligence Magazine"},{"issue":"9","key":"9795_CR59","doi-asserted-by":"publisher","first-page":"1633","DOI":"10.1109\/TASLP.2018.2831456","volume":"26","author":"C Zhang","year":"2018","unstructured":"Zhang, C., Koishida, K., & Hansen, J. H. (2018). Text-independent speaker verification based on triplet convolutional neural network embeddings. IEEE\/ACM Transactions on Audio, Speech, and Language Processing, 26(9), 1633\u20131644.","journal-title":"IEEE\/ACM Transactions on Audio, Speech, and Language Processing"}],"container-title":["International Journal of Speech Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10772-021-09795-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10772-021-09795-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10772-021-09795-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,12]],"date-time":"2022-12-12T19:49:50Z","timestamp":1670874590000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10772-021-09795-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,22]]},"references-count":60,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2021,6]]}},"alternative-id":["9795"],"URL":"https:\/\/doi.org\/10.1007\/s10772-021-09795-2","relation":{},"ISSN":["1381-2416","1572-8110"],"issn-type":[{"type":"print","value":"1381-2416"},{"type":"electronic","value":"1572-8110"}],"subject":[],"published":{"date-parts":[[2021,1,22]]},"assertion":[{"value":"30 July 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 December 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}