{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:27:25Z","timestamp":1740122845466,"version":"3.37.3"},"reference-count":30,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T00:00:00Z","timestamp":1674432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Basic Research Program of China","doi-asserted-by":"publisher","award":["2014CB744600"],"award-info":[{"award-number":["2014CB744600"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Speech Technol"],"published-print":{"date-parts":[[2023,7]]},"DOI":"10.1007\/s10772-023-10017-0","type":"journal-article","created":{"date-parts":[[2023,1,23]],"date-time":"2023-01-23T04:16:44Z","timestamp":1674447404000},"page":"371-378","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A radius-incorporated localized multiple kernel learning algorithm for detecting depression in speech"],"prefix":"10.1007","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4109-4061","authenticated-orcid":false,"given":"Haihua","family":"Jiang","sequence":"first","affiliation":[]},{"given":"Bin","family":"Hu","sequence":"additional","affiliation":[]},{"given":"Zhenyu","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Gang","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Lan","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,1,23]]},"reference":[{"key":"10017_CR1","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1080\/14015430701855333","volume":"33","author":"M Airas","year":"2008","unstructured":"Airas, M. (2008). TKK Aparat: An environment for voice inverse filtering and parameterization. Logopedics Phoniatrics Vocology, 33, 49\u201364.","journal-title":"Logopedics Phoniatrics Vocology"},{"key":"10017_CR2","doi-asserted-by":"crossref","unstructured":"Alghowinem, S., Goecke, R., Wagner, M., Epps, J., Gedeon, T., Breakspear, M., & Parker, G. (2013). A comparative study of different classifiers for detecting depression from spontaneous speech. In Proceedings of ICASSP 2013, (pp. 8022\u20138026). IEEE","DOI":"10.1109\/ICASSP.2013.6639227"},{"key":"10017_CR3","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1023\/A:1012450327387","volume":"46","author":"O Chapelle","year":"2002","unstructured":"Chapelle, O., Vapnik, V., Bousquet, O., & Mukherjee, S. (2002). Choosing multiple parameters for support vector machines. Machine Learning, 46, 31\u2013159.","journal-title":"Machine Learning"},{"key":"10017_CR4","doi-asserted-by":"publisher","first-page":"29","DOI":"10.1007\/s10462-010-9200-z","volume":"36","author":"J Chen","year":"2011","unstructured":"Chen, J., & Liu, Y. (2011). Locally linear embedding: A survey. Artificial Intelligence Review, 36, 29\u201348.","journal-title":"Artificial Intelligence Review"},{"key":"10017_CR5","doi-asserted-by":"publisher","first-page":"2643","DOI":"10.1162\/089976603322385108","volume":"15","author":"KM Chung","year":"2003","unstructured":"Chung, K. M., Kao, W. C., Sun, C. L., Wang, L. L., & Lin, C. J. (2003). Radius margin bounds for support vector machines with the RBF kernel. Neural Computation, 15, 2643\u20132681.","journal-title":"Neural Computation"},{"key":"10017_CR6","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.specom.2015.03.004","volume":"71","author":"N Cummins","year":"2015","unstructured":"Cummins, N., Scherer, S., Krajewski, J., Schnieder, S., Epps, J., & Quatieri, T. F. (2015). A review of depression and suicide risk assessment using speech analysis. Speech Communication, 71, 10\u201349.","journal-title":"Speech Communication"},{"key":"10017_CR7","doi-asserted-by":"crossref","unstructured":"Cummins, N., Epps, J., Sethu, V., & Krajewski, J. (2014). Variability compensation in small data: Oversampled extraction of I-vectors for the classification of depressed speech. In Proceedings of ICASSP 2014, (pp. 970\u2013974). IEEE","DOI":"10.1109\/ICASSP.2014.6853741"},{"key":"10017_CR8","unstructured":"Dua, D., & Karra Taniskidou, E. UCI machine learning repository. University of California, School of Information and Computer Science. Retrieved 2021, from http:\/\/archive.ics.uci.edu\/ml."},{"key":"10017_CR9","doi-asserted-by":"crossref","unstructured":"Eyben, F., W\u00f6llmer, M., & Schuller, B. (2010). Opensmile-The Munich versatile and fast open-source audio feature extractor. In Proceedings of the 18th ACM international conference on multimedia, (pp. 1459\u20131462). Association for Computing Machinery","DOI":"10.1145\/1873951.1874246"},{"key":"10017_CR11","doi-asserted-by":"crossref","unstructured":"G\u00f6nen, M., & Alpaydin, E. (2008). Localized multiple kernel learning. In Proceedings of the 5th international conference on machine learning, (pp. 352\u2013359). Springer-Verlag","DOI":"10.1145\/1390156.1390201"},{"key":"10017_CR10","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1016\/j.patcog.2012.09.002","volume":"46","author":"M G\u00f6nen","year":"2013","unstructured":"G\u00f6nen, M., & Alpayd\u0131n, E. (2013). Localized algorithms for multiple kernel learning. Pattern Recognition, 46, 795\u2013807.","journal-title":"Pattern Recognition"},{"key":"10017_CR12","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1016\/j.jad.2013.01.004","volume":"147","author":"K Hawton","year":"2013","unstructured":"Hawton, K., Comabella, C. C. I., Haw, C., & Saunders, K. (2013). Risk factors for suicide in individuals with depression: A systematic review. Journal of Affective Disorders, 147, 17\u201328.","journal-title":"J. Affect. Disorders."},{"key":"10017_CR13","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.jbi.2018.05.007","volume":"83","author":"L He","year":"2018","unstructured":"He, L., & Cao, C. (2018). Automated depression analysis using convolutional neural networks from speech. Journal of Biomedical Informatics, 83, 103\u2013111.","journal-title":"Journal of Biomedical Informatics"},{"key":"10017_CR14","doi-asserted-by":"publisher","first-page":"827","DOI":"10.1109\/TNN.2009.2014229","volume":"20","author":"M Hu","year":"2009","unstructured":"Hu, M., Chen, Y., & Kwok, J. T. Y. (2009). Building sparse multiple kernel SVM classifiers. IEEE Transactions on Neural Networks, 20, 827\u2013839.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10017_CR15","doi-asserted-by":"publisher","first-page":"393","DOI":"10.1109\/TAFFC.2018.2803178","volume":"11","author":"KY Huang","year":"2020","unstructured":"Huang, K. Y., Wu, C. H., Su, M. H., & Kuo, Y. T. (2020). Detecting unipolar and bipolar depressive disorders from elicited speech responses using latent affective structure model. IEEE Transcactions on Affective Computing, 11, 393\u2013404.","journal-title":"IEEE Transcactions on Affective Computing"},{"key":"10017_CR16","first-page":"1","volume":"9","author":"HH Jiang","year":"2018","unstructured":"Jiang, H. H., Hu, B., Liu, Z. Y., Wang, G., Zhang, L., Li, X. Y., & Kang, H. Y. (2018). Detecting depression using an ensemble logistic regression model based on multiple speech features. Computational and Mathematical Method, 9, 1\u20139.","journal-title":"Computational and Mathematical Method"},{"key":"10017_CR17","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.specom.2017.04.001","volume":"90","author":"HH Jiang","year":"2017","unstructured":"Jiang, H. H., Hu, B., Liu, Z. Y., Yan, L. H., Wang, T. Y., Liu, F., Kang, H. Y., & Li, X. Y. (2017). Investigation of different speech types and emotions for detecting depression using different classifiers. Speech Communication, 90, 39\u201346.","journal-title":"Speech Communication"},{"key":"10017_CR18","doi-asserted-by":"publisher","first-page":"557","DOI":"10.1109\/TSMCB.2012.2212243","volume":"43","author":"XW Liu","year":"2013","unstructured":"Liu, X. W., Wang, L., Yin, J. P., Zhu, E., & Zhang, J. (2013). An efficient approach to integrating radius information into multiple kernel learning. IEEE Transactions on Cybernetics., 43, 557\u2013569.","journal-title":"IEEE Transactions on Cybernetics."},{"key":"10017_CR19","doi-asserted-by":"publisher","first-page":"574","DOI":"10.1109\/TBME.2010.2091640","volume":"58","author":"LA Low","year":"2011","unstructured":"Low, L. A., Maddage, N. C., Lech, M., Sheeber, L. B., & Allen, N. B. (2011). Detection of clinical depression in adolescents\u2019 speech during family interactions. IEEE Transactions on Bio-Medical Engineering, 58, 574\u2013586.","journal-title":"IEEE Transactions on Bio-Medical Engineering"},{"key":"10017_CR20","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1109\/TBME.2007.900562","volume":"55","author":"E Moore","year":"2008","unstructured":"Moore, E., Clements, M., Peifer, J. W., & Weisser, L. (2008). Critical analysis of the impact of glottal features in the classification of clinical depression in speech. IEEE Transactions on Bio-Medical Engineering, 55, 96\u2013107.","journal-title":"IEEE Transactions on Bio-Medical Engineering"},{"key":"10017_CR21","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1037\/0033-2909.115.3.424","volume":"115","author":"S Nolenhoeksema","year":"1994","unstructured":"Nolenhoeksema, S., & Girgus, J. S. (1994). The emergence of gender differences in depression during adolescence. Psychological Bulletin, 115, 424\u2013443.","journal-title":"Psychological Bulletin"},{"key":"10017_CR22","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.bspc.2014.08.006","volume":"14","author":"KEB Ooi","year":"2014","unstructured":"Ooi, K. E. B., Lech, M., & Allen, N. B. (2014). Prediction of major depression in adolescents using an optimized multi-channel weighted speech classification system. Biomedical Signal Processing, 14, 228\u2013239.","journal-title":"Biomed. Signal Proces."},{"key":"10017_CR23","first-page":"2491","volume":"9","author":"A Rakotomamonjy","year":"2008","unstructured":"Rakotomamonjy, A., Bach, F., Grandvalet, Y., & Canu, S. (2008). SimpleMKL. Journal of Machine Learning Research, 9, 2491\u20132521.","journal-title":"Journal of Machine Learning Research"},{"key":"10017_CR24","first-page":"847","volume":"2013","author":"S Scherer","year":"2013","unstructured":"Scherer, S., Stratou, G., Gratch, J., & Morency, L. P. (2013). Investigating voice quality as a speaker-independent indicator of depression and PTSD. In\u00a0Proceedings of Interspeech, 2013, (pp. 847\u2013851). ISCA","journal-title":"In Proceedings of Interspeech"},{"key":"10017_CR25","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1176\/ajp.154.1.4","volume":"154","author":"C Sobin","year":"1997","unstructured":"Sobin, C., & Sackeim, H. A. (1997). Psychomotor symptoms of depression. American Journal of Psychiatry., 154, 4\u201317.","journal-title":"Am. J. Psychiat."},{"key":"10017_CR26","doi-asserted-by":"publisher","first-page":"1534","DOI":"10.1109\/TPAMI.2007.70799","volume":"30","author":"L Wang","year":"2008","unstructured":"Wang, L. (2008). Feature selection with kernel class separability. IEEE Transactions on Pattern Analysis, 30, 1534\u20131546.","journal-title":"IEEE Transactions on Pattern Analysis"},{"key":"10017_CR27","unstructured":"World Health Organization. (2021, September 13). Depression fact sheet. WHO, Geneva, Switzerland. Retrieved January 27, 2022, from http:\/\/www.who.int\/en\/news-room\/fact-sheets\/detail\/depression."},{"key":"10017_CR28","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1109\/TNNLS.2012.2237183","volume":"24","author":"X Xu","year":"2013","unstructured":"Xu, X., Tsang, I. W., & Xu, D. (2013). Soft margin multiple kernel learning. IEEE Transactions on Neural Networks, 24, 749\u2013761.","journal-title":"IEEE Transactions on Neural Networks"},{"key":"10017_CR29","unstructured":"Xu, Z., Jin, R., Yang, H., King, I., & Lyu, M. R. (2010). Simple and efficient multiple kernel learning by group Lasso. In Proceedings of the 27th international conference on machine learning, (pp. 1175\u20131182). Omnipress"},{"key":"10017_CR30","doi-asserted-by":"crossref","unstructured":"Zhao, Z., Bao, Z., Zhang, Z., Cummins, N., & Schuller, B. (2020). Hierarchical attention transfer networks for depression assessment from speech. In Proceedings of ICASSP 2020, (pp. 7159\u20137163). IEEE","DOI":"10.1109\/ICASSP40776.2020.9053207"}],"container-title":["International Journal of Speech Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10772-023-10017-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10772-023-10017-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10772-023-10017-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T11:13:39Z","timestamp":1690802019000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10772-023-10017-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,1,23]]},"references-count":30,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2023,7]]}},"alternative-id":["10017"],"URL":"https:\/\/doi.org\/10.1007\/s10772-023-10017-0","relation":{},"ISSN":["1381-2416","1572-8110"],"issn-type":[{"type":"print","value":"1381-2416"},{"type":"electronic","value":"1572-8110"}],"subject":[],"published":{"date-parts":[[2023,1,23]]},"assertion":[{"value":"27 January 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 January 2023","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 January 2023","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 declare that there are no conflicts of interest regarding the publication of this paper.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}