{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T15:26:50Z","timestamp":1775230010702,"version":"3.50.1"},"publisher-location":"Cham","reference-count":18,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030014179","type":"print"},{"value":"9783030014186","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-01418-6_76","type":"book-chapter","created":{"date-parts":[[2018,9,26]],"date-time":"2018-09-26T14:57:36Z","timestamp":1537973856000},"page":"782-790","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Gender-Aware CNN-BLSTM for Speech Emotion Recognition"],"prefix":"10.1007","author":[{"given":"Linjuan","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Longbiao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwu","family":"Dang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lili","family":"Guo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,9,27]]},"reference":[{"issue":"2","key":"76_CR1","doi-asserted-by":"publisher","first-page":"102","DOI":"10.1111\/j.1467-6494.1985.tb00361.x","volume":"53","author":"LR Brody","year":"1985","unstructured":"Brody, L.R.: Gender differences in emotional development: a review of theories and research. J. Pers. 53(2), 102\u2013149 (1985)","journal-title":"J. Pers."},{"key":"76_CR2","doi-asserted-by":"publisher","unstructured":"Hall, J.A., Carter, J.D., Horgan, T.: Gender differences in nonverbal communication of emotion. In: Gender and Emotion: Social Psychological Perspectives, pp. 97\u2013117 (2000). https:\/\/doi.org\/10.1017\/CBO9780511628191.006","DOI":"10.1017\/CBO9780511628191.006"},{"key":"76_CR3","unstructured":"Sidorov, M., Ultes, S., Schmitt, A.: Comparison of Gender-and Speaker-adaptive Emotion Recognition. In: Language Resources and Evaluation Conference, pp. 3476\u20133480 (2014)"},{"key":"76_CR4","doi-asserted-by":"crossref","unstructured":"Sidorov, M., Ultes, S., Schmitt, A.: Emotions are a personal thing: towards speaker-adaptive emotion recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4803\u20134807 (2014)","DOI":"10.1109\/ICASSP.2014.6854514"},{"key":"76_CR5","unstructured":"Vogt, T., Andr\u00e9, E.: Improving automatic emotion recognition from speech via gender differentiation. In: Language Resources and Evaluation Conference, Genoa (2006)"},{"key":"76_CR6","unstructured":"Sidorov, M., Schmitt, A., Semenkin, E., et al.: Could speaker, gender or age awareness be beneficial in speech-based emotion recognition? In: Language Resources and Evaluation Conference (2016)"},{"key":"76_CR7","doi-asserted-by":"crossref","unstructured":"Schuller, B., Steidl S., Batliner, A.: The INTERSPEECH 2009 emotion challenge. In: Tenth Annual Conference of the International Speech Communication Association (2009)","DOI":"10.21437\/Interspeech.2009-103"},{"key":"76_CR8","unstructured":"Hannun, A., Case, C., Casper, J., et al.: Deep speech: scaling up end-to-end speech recognition. arXiv preprint arXiv:1412.5567 (2014)"},{"key":"76_CR9","unstructured":"Amodei, D., Ananthanarayanan, S., Anubhai, R., et al.: Deep speech 2: end-to-end speech recognition in English and mandarin. In: International Conference on Machine Learning, pp. 173\u2013182 (2016)"},{"key":"76_CR10","doi-asserted-by":"crossref","unstructured":"Lim, W., Jang, D., Lee, T.: Speech emotion recognition using convolutional and recurrent neural networks. In: Signal and Information Processing Association Annual Summit and Conference, Asia-Pacific, pp. 1\u20134. IEEE (2016)","DOI":"10.1109\/APSIPA.2016.7820699"},{"key":"76_CR11","doi-asserted-by":"crossref","unstructured":"Satt, A., Rozenberg, S., Hoory, R.: Efficient emotion recognition from speech using deep learning on spectrograms. In: Proceedings of INTERSPEECH 2017, pp. 1089\u20131093 (2017)","DOI":"10.21437\/Interspeech.2017-200"},{"key":"76_CR12","doi-asserted-by":"crossref","unstructured":"Guo, L., Wang, L., Dang, J., Zhang, L., Guan, H.: A feature fusion method based on extreme learning machine for speech emotion recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 2666\u20132670 (2018)","DOI":"10.1109\/ICASSP.2018.8462219"},{"key":"76_CR13","series-title":"Springer-Lehrbuch","doi-asserted-by":"publisher","first-page":"165","DOI":"10.1007\/978-3-662-08008-5_6","volume-title":"Sozialpsychologie","author":"KR Scherer","year":"2002","unstructured":"Scherer, K.R.: Emotion. In: Stroebe, W., Jonas, K., Hewstone, M. (eds.) Sozialpsychologie. Springer-Lehrbuch, pp. 165\u2013213. Springer, Heidelberg (2002). https:\/\/doi.org\/10.1007\/978-3-662-08008-5_6"},{"key":"76_CR14","doi-asserted-by":"crossref","unstructured":"Grezl, F., Fousek, P.: Optimizing bottle-neck features for LVCSR. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4729\u20134732 (2008)","DOI":"10.1109\/ICASSP.2008.4518713"},{"key":"76_CR15","doi-asserted-by":"crossref","unstructured":"Petrushin, V.A.: Emotion recognition in speech signal: experimental study, development, and application. In: Sixth International Conference on Spoken Language Processing (2000)","DOI":"10.21437\/ICSLP.2000-791"},{"key":"76_CR16","doi-asserted-by":"crossref","unstructured":"Burkhardt, F., Paeschke, A., Rolfes, M., Sendlmeier, W.F., Weiss, B.: A database of German emotional speech. In: Ninth European Conference on Speech Communication and Technology (2005)","DOI":"10.21437\/Interspeech.2005-446"},{"key":"76_CR17","doi-asserted-by":"crossref","unstructured":"Yu, D., et al.: Deep convolutional neural networks with layer-wise context expansion and attention. In: INTERSPEECH, pp. 17\u201321 (2016)","DOI":"10.21437\/Interspeech.2016-251"},{"key":"76_CR18","doi-asserted-by":"crossref","unstructured":"Lee, J., Tashev, I.: High-level feature representation using recurrent neural network for speech emotion recognition. In: INTERSPEECH (2015)","DOI":"10.21437\/Interspeech.2015-336"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2018"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-01418-6_76","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,2]],"date-time":"2022-09-02T19:53:48Z","timestamp":1662148428000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-01418-6_76"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030014179","9783030014186"],"references-count":18,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-01418-6_76","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rhodes","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 October 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 October 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2018\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Open","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"easyacademia.org","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"360","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"139","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"28","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"39% - 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"}},{"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"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"In addition there are 41 full poster papers and 11 short poster papers included in the proceedings","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}