{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T15:55:39Z","timestamp":1743004539837,"version":"3.40.3"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031346187"},{"type":"electronic","value":"9783031346194"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-34619-4_29","type":"book-chapter","created":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T19:01:31Z","timestamp":1686423691000},"page":"358-370","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Bangla Speech-Based Person Identification Using LSTM Networks"],"prefix":"10.1007","author":[{"given":"Rahad","family":"Khan","sequence":"first","affiliation":[]},{"given":"Saddam","family":"Hossain","sequence":"additional","affiliation":[]},{"given":"Akbor","family":"Hossain","sequence":"additional","affiliation":[]},{"given":"Fazlul Hasan","family":"Siddiqui","sequence":"additional","affiliation":[]},{"given":"Sabah Binte","family":"Noor","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,6,11]]},"reference":[{"issue":"1","key":"29_CR1","first-page":"11","volume":"5","author":"S Chakroborty","year":"2009","unstructured":"Chakroborty, S., Saha, G.: Improved text-independent speaker identification using fused MFCC & IMFCC feature sets based on gaussian filter. Int. J. Signal Process. 5(1), 11\u201319 (2009)","journal-title":"Int. J. Signal Process."},{"key":"29_CR2","unstructured":"colah: Understanding LSTM networks (2015). http:\/\/colah.github.io\/posts\/2015-08-Understanding-LSTMs\/"},{"key":"29_CR3","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.apacoust.2019.07.033","volume":"156","author":"F Ertam","year":"2019","unstructured":"Ertam, F.: An effective gender recognition approach using voice data via deeper LSTM networks. Appl. Acoust. 156, 351\u2013358 (2019)","journal-title":"Appl. Acoust."},{"key":"29_CR4","unstructured":"Karatas, T., Hirsa, A.: Two-stage sector rotation methodology using machine learning and deep learning techniques. arXiv preprint arXiv:2108.02838 (2021)"},{"issue":"10","key":"29_CR5","doi-asserted-by":"publisher","first-page":"13487","DOI":"10.1016\/j.eswa.2011.04.069","volume":"38","author":"P Krishnamoorthy","year":"2011","unstructured":"Krishnamoorthy, P., Jayanna, H., Prasanna, S.M.: Speaker recognition under limited data condition by noise addition. Expert Syst. Appl. 38(10), 13487\u201313490 (2011)","journal-title":"Expert Syst. Appl."},{"issue":"1","key":"29_CR6","doi-asserted-by":"publisher","first-page":"492","DOI":"10.3390\/make1010030","volume":"1","author":"IE Livieris","year":"2019","unstructured":"Livieris, I.E., Pintelas, E., Pintelas, P.: Gender recognition by voice using an improved self-labeled algorithm. Mach. Learn. Knowl. Extract. 1(1), 492\u2013503 (2019)","journal-title":"Mach. Learn. Knowl. Extract."},{"key":"29_CR7","doi-asserted-by":"crossref","unstructured":"Lukic, Y., Vogt, C., D\u00fcrr, O., Stadelmann, T.: Speaker identification and clustering using convolutional neural networks. In: 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), pp. 1\u20136. IEEE (2016)","DOI":"10.1109\/MLSP.2016.7738816"},{"key":"29_CR8","unstructured":"Olugbenga, T.O.: Deep learning techniques for electrical load forecasting. Ph.D. thesis, University of New Brunswick (2022)"},{"key":"29_CR9","doi-asserted-by":"crossref","unstructured":"Pondhu, L.N., Kummari, G.: Performance analysis of machine learning algorithms for gender classification. In: 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), pp. 1626\u20131628. IEEE (2018)","DOI":"10.1109\/ICICCT.2018.8473192"},{"issue":"1","key":"29_CR10","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1109\/89.365379","volume":"3","author":"DA Reynolds","year":"1995","unstructured":"Reynolds, D.A., Rose, R.C.: Robust text-independent speaker identification using gaussian mixture speaker models. IEEE Trans. Speech Audio Process. 3(1), 72\u201383 (1995)","journal-title":"IEEE Trans. Speech Audio Process."},{"key":"29_CR11","doi-asserted-by":"crossref","unstructured":"Saeidi, R., et al.: Signal-to-signal ratio independent speaker identification for co-channel speech signals. In: 2010 20th International Conference on Pattern Recognition, pp. 4565\u20134568. IEEE (2010)","DOI":"10.1109\/ICPR.2010.1131"},{"key":"29_CR12","doi-asserted-by":"crossref","unstructured":"Shahin, I.: Speaker identification in emotional environments (2009)","DOI":"10.1109\/ISSPIT.2009.5407568"},{"key":"29_CR13","doi-asserted-by":"crossref","unstructured":"Sharma, G., Umapathy, K., Krishnan, S.: Trends in audio signal feature extraction methods. Appl. Acoust. 158, 107020 (2020)","DOI":"10.1016\/j.apacoust.2019.107020"},{"issue":"4","key":"29_CR14","doi-asserted-by":"publisher","first-page":"235","DOI":"10.2478\/jaiscr-2019-0006","volume":"9","author":"A Shewalkar","year":"2019","unstructured":"Shewalkar, A.: Performance evaluation of deep neural networks applied to speech recognition: RNN, LSTM and GRU. J. Artif. Intell. Soft Comput. Res. 9(4), 235\u2013245 (2019)","journal-title":"J. Artif. Intell. Soft Comput. Res."},{"key":"29_CR15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-62582-5","volume-title":"Malware Analysis Using Artificial Intelligence and Deep Learning","author":"M Stamp","year":"2021","unstructured":"Stamp, M., Alazab, M., Shalaginov, A.: Malware Analysis Using Artificial Intelligence and Deep Learning. Springer, Heidelberg (2021). https:\/\/doi.org\/10.1007\/978-3-030-62582-5"},{"key":"29_CR16","doi-asserted-by":"crossref","unstructured":"Tandel, N.H., Prajapati, H.B., Dabhi, V.K.: Voice recognition and voice comparison using machine learning techniques: a survey. In: 2020 6th International Conference on Advanced Computing and Communication Systems (ICACCS), pp. 459\u2013465. IEEE (2020)","DOI":"10.1109\/ICACCS48705.2020.9074184"},{"issue":"8","key":"29_CR17","doi-asserted-by":"publisher","first-page":"3603","DOI":"10.3390\/app11083603","volume":"11","author":"F Ye","year":"2021","unstructured":"Ye, F., Yang, J.: A deep neural network model for speaker identification. Appl. Sci. 11(8), 3603 (2021)","journal-title":"Appl. Sci."},{"key":"29_CR18","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Miao, R.: Network media public opinion and social governance supported by the internet-of-things big data. Secur. Commun. Netw. 2022 (2022)","DOI":"10.1155\/2022\/2459815"}],"container-title":["Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering","Machine Intelligence and Emerging Technologies"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-34619-4_29","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,10]],"date-time":"2023-06-10T19:08:01Z","timestamp":1686424081000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-34619-4_29"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031346187","9783031346194"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-34619-4_29","relation":{},"ISSN":["1867-8211","1867-822X"],"issn-type":[{"type":"print","value":"1867-8211"},{"type":"electronic","value":"1867-822X"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"11 June 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MIET","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Machine Intelligence and Emerging Technologies","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Noakhali","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bangladesh","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"miet2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/confmiet.org","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Confy plus","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"272","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"104","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}