{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T02:25:34Z","timestamp":1743042334537,"version":"3.40.3"},"publisher-location":"Cham","reference-count":40,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031417733"},{"type":"electronic","value":"9783031417740"}],"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\/978-3-031-41774-0_34","type":"book-chapter","created":{"date-parts":[[2023,9,21]],"date-time":"2023-09-21T03:25:20Z","timestamp":1695266720000},"page":"430-442","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Kazakh-Uzbek Speech Cascade Machine Translation on Complete Set of Endings"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8371-9613","authenticated-orcid":false,"given":"Tolganay","family":"Balabekova","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0341-0588","authenticated-orcid":false,"given":"Bauyrzhan","family":"Kairatuly","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9878-981X","authenticated-orcid":false,"given":"Ualsher","family":"Tukeyev","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,9,22]]},"reference":[{"key":"34_CR1","doi-asserted-by":"crossref","unstructured":"Koehn, P., Knowles, R.: Six challenges for neural machine translation. In: Proceedings of the First Workshop on Neural Machine Translation, pp. 28\u201339, Vancouver, Canada (2017)","DOI":"10.18653\/v1\/W17-3204"},{"key":"34_CR2","unstructured":"Tukeyev, U.: Automaton models of the morphology analysis and the completeness of the endings of the Kazakh language. In: Proceedings of the international conference \u201cTurkic languages processing\u201d TURKLANG-2015 September 17\u201319, pp. 91\u2013100. Kazan, Tatarstan, Russia (2015). (in Russian)"},{"key":"34_CR3","doi-asserted-by":"publisher","first-page":"741","DOI":"10.1007\/978-3-030-63119-2_60","volume-title":"Advances in Computational Collective Intelligence: 12th International Conference, ICCCI 2020, Da Nang, Vietnam, 30 Nov\u20133 Dec 2020, Proceedings","author":"U Tukeyev","year":"2020","unstructured":"Tukeyev, U., Karibayeva, Ai.: Inferring the complete set of Kazakh endings as a language resource. In: Hernes, M., Wojtkiewicz, K., Szczerbicki, E. (eds.) Advances in Computational Collective Intelligence: 12th International Conference, ICCCI 2020, Da Nang, Vietnam, 30 Nov\u20133 Dec 2020, Proceedings, pp. 741\u2013751. Springer International Publishing, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-63119-2_60"},{"key":"34_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1007\/978-3-319-45246-3_54","volume-title":"Computational Collective Intelligence","author":"U Tukeyev","year":"2016","unstructured":"Tukeyev, U., Sundetova, A., Abduali, B., Akhmadiyeva, Z., Zhanbussunov, N.: Inferring of the morphological chunk transfer rules on the base of complete set of Kazakh endings. In: Nguyen, N.-T., Manolopoulos, Y., Iliadis, L., Trawi\u0144ski, B. (eds.) ICCCI 2016. LNCS (LNAI), vol. 9876, pp. 563\u2013574. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-45246-3_54"},{"issue":"1","key":"34_CR5","doi-asserted-by":"publisher","first-page":"1856500","DOI":"10.1080\/23311916.2020.1856500","volume":"7","author":"U Tukeyev","year":"2020","unstructured":"Tukeyev, U., Karibayeva, A., Zhumanov, Z.: Morphological segmentation method for Turkic language neural machine translation. Cogent Eng. 7(1), 1856500 (2020). https:\/\/doi.org\/10.1080\/23311916.2020.1856500","journal-title":"Cogent Eng."},{"key":"34_CR6","doi-asserted-by":"publisher","first-page":"643","DOI":"10.1007\/978-3-030-88081-1_48","volume-title":"Computational Collective Intelligence: 13th International Conference, ICCCI 2021, Rhodes, Greece, September 29 \u2013 October 1, 2021, Proceedings","author":"U Tukeyev","year":"2021","unstructured":"Tukeyev, U., Karibayeva, A., Turganbayeva, A., Amirova, D.: Universal programs for stemming, segmentation, morphological analysis of Turkic words. In: Thanh Nguyen, N., Iliadis, L., Maglogiannis, I., Trawi\u0144ski, B. (eds.) Computational Collective Intelligence: 13th International Conference, ICCCI 2021, Rhodes, Greece, September 29 \u2013 October 1, 2021, Proceedings, pp. 643\u2013654. Springer International Publishing, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-88081-1_48"},{"key":"34_CR7","doi-asserted-by":"publisher","first-page":"729","DOI":"10.1007\/978-3-030-63119-2_59","volume-title":"Advances in Computational Collective Intelligence: 12th International Conference, ICCCI 2020, Da Nang, Vietnam, 30 Nov\u20133 Dec 2020, Proceedings","author":"S Matlatipov","year":"2020","unstructured":"Matlatipov, S., Tukeyev, U., Aripov, M.: Towards the uzbek language endings as a language resource. In: Hernes, M., Wojtkiewicz, K., Szczerbicki, E. (eds.) Advances in Computational Collective Intelligence: 12th International Conference, ICCCI 2020, Da Nang, Vietnam, 30 Nov\u20133 Dec 2020, Proceedings, pp. 729\u2013740. Springer International Publishing, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-63119-2_59"},{"key":"34_CR8","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1007\/978-3-030-73280-6_26","volume-title":"Intelligent Information and Database Systems: 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, 7\u201310 Apr 2021, Proceedings","author":"A Toleush","year":"2021","unstructured":"Toleush, A., Israilova, N., Tukeyev, U.: Development of morphological segmentation for the kyrgyz language on complete set of endings. In: Nguyen, N.T., Chittayasothorn, S., Niyato, D., Trawi\u0144ski, B. (eds.) Intelligent Information and Database Systems: 13th Asian Conference, ACIIDS 2021, Phuket, Thailand, 7\u201310 Apr 2021, Proceedings, pp. 327\u2013339. Springer International Publishing, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-73280-6_26"},{"key":"34_CR9","doi-asserted-by":"publisher","first-page":"543","DOI":"10.1007\/978-981-19-8234-7_42","volume-title":"Recent Challenges in Intelligent Information and Database Systems: 14th Asian Conference, ACIIDS 2022, Ho Chi Minh City, Vietnam, 28\u201330 Nov 2022, Proceedings","author":"A Qamet","year":"2022","unstructured":"Qamet, A., Zhakypbayeva, K., Turganbayeva, A., Tukeyev, U.: Development Kazakh-Turkish machine translation on the base of complete set of endings model. In: Szczerbicki, E., Wojtkiewicz, K., Van Nguyen, S., Pietranik, M., Kr\u00f3tkiewicz, M. (eds.) Recent Challenges in Intelligent Information and Database Systems: 14th Asian Conference, ACIIDS 2022, Ho Chi Minh City, Vietnam, 28\u201330 Nov 2022, Proceedings, pp. 543\u2013555. Springer Nature Singapore, Singapore (2022). https:\/\/doi.org\/10.1007\/978-981-19-8234-7_42"},{"key":"34_CR10","unstructured":"Lavie, A., et al.: JANUS-III: Speech-to-speech translation in multiple languages. In: Proceedings of the ICASSP 1997 (1997)"},{"volume-title":"Verbmobil: Foundations of Speech-to-Speech Translation","year":"2000","key":"34_CR11","unstructured":"Wahlster, W. (ed.): Verbmobil: Foundations of Speech-to-Speech Translation. Springer, Berlin, Heidelberg (2000)"},{"issue":"2","key":"34_CR12","doi-asserted-by":"publisher","first-page":"365","DOI":"10.1109\/TSA.2005.860774","volume":"14","author":"S Nakamura","year":"2006","unstructured":"Nakamura, S., et al.: The ATR multilingual speech-to-speech translation system. IEEE Trans. Audio Speech Language Process. 14(2), 365\u2013376 (2006)","journal-title":"IEEE Trans. Audio Speech Language Process."},{"key":"34_CR13","unstructured":"Guo, M., Haque, A., Verma, P.: End-to-end spoken language translation, arXiv preprint arXiv:1904.10760 (2019)"},{"key":"34_CR14","doi-asserted-by":"crossref","unstructured":"Jia, Y., et al.: Direct speech-to-speech translation with a sequence-to-sequence model arXiv:1904.06037v2 (2019)","DOI":"10.21437\/Interspeech.2019-1951"},{"key":"34_CR15","doi-asserted-by":"crossref","unstructured":"Papi, S., Gaido, M., Negri, M., Turchi, M.: Speechformer: Reducing Information Loss in Direct Speech Translation arXiv:2109.04574v1 (2021)","DOI":"10.18653\/v1\/2021.emnlp-main.127"},{"key":"34_CR16","doi-asserted-by":"crossref","unstructured":"Kano, T., Sakti, S., Nakamura, S.: Transformer-based direct speech-to-speech translation with transcoder. In: 2021 IEEE Spoken Language Technology Workshop (SLT), pp. 958\u2013965. IEEE (2021)","DOI":"10.1109\/SLT48900.2021.9383496"},{"key":"34_CR17","doi-asserted-by":"crossref","unstructured":"Papi, S., Gaido, M., Karakanta, A., Cettolo, M., Negri, M., Turchi, M.: Direct Speech Translation for Automatic Subtitling. CoRR abs\/2209.13192 (2022)","DOI":"10.1162\/tacl_a_00607"},{"key":"34_CR18","doi-asserted-by":"crossref","unstructured":"Bentivogli, L., et al.: Cascade versus Direct Speech Translation: Do the Differences Still Make a Difference? ACL\/IJCNLP (1) 2021, pp. 2873\u20132887 (2021)","DOI":"10.18653\/v1\/2021.acl-long.224"},{"key":"34_CR19","doi-asserted-by":"crossref","unstructured":"Niehues, J., Salesky, E., Turchi, M., Negri, M.: Tutorial Proposal: End-to-End Speech Translation. EACL (Tutorial Abstracts) 2021, pp. 10\u201313 (2021)","DOI":"10.18653\/v1\/2021.eacl-tutorials.3"},{"key":"34_CR20","unstructured":"Wang, C., et al.: Simple and Effective Unsupervised Speech Translation. arXiv:2210.10191v1 [cs.CL] (2022)"},{"key":"34_CR21","first-page":"1298","volume":"2018","author":"S Bansal","year":"2018","unstructured":"Bansal, S., Kamper, H., Livescu, K., Lopez, A., Goldwater, S.: Low resource speech-to-text translation. Proc. Interspeech 2018, 1298\u20131302 (2018)","journal-title":"Proc. Interspeech"},{"key":"34_CR22","doi-asserted-by":"crossref","unstructured":"Bansal, S., Kamper, H., Livescu, K., Lopez, A., Goldwater, S.: Pretraining on high-resource speech recognition improves low-resource speech-to-text translation. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, vol. 1 (Long and Short Papers), pp. 58\u201368 (2019)","DOI":"10.18653\/v1\/N19-1006"},{"key":"34_CR23","doi-asserted-by":"crossref","unstructured":"Cheng, Y.-F., Hung-Shin Lee, H.-S., Wang, H.-M.: AlloST: Low-Resource Speech Translation Without Source Transcription. In: Proceedings of the Interspeech 2021, pp. 2252\u20132256 (2021)","DOI":"10.21437\/Interspeech.2021-526"},{"key":"34_CR24","doi-asserted-by":"crossref","unstructured":"Chung, Y.-A., Weng, W.-H., Tong, S., James Glass, J.: Towards unsupervised speech-to-text translation. In: ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7170\u20137174. IEEE (2019)","DOI":"10.1109\/ICASSP.2019.8683550"},{"key":"34_CR25","unstructured":"Karakanta, A., Negri, M., Turchi, M.: MuST-Cinema: a Speech-to-Subtitles corpus. LREC 2020, pp. 3727\u20133734 (2020)"},{"key":"34_CR26","unstructured":"Jia, Y., Ramanovich, M.T., Wang, Q., Zen, H.: Cvss corpus and massively multilingual speech-to-speech translation. arXiv preprint arXiv:2201.03713 (2022)"},{"key":"34_CR27","unstructured":"Bentivogli, L., Mauro, C., Marco, G., Alina, K., Matteo, N., Marco, T.: Extending the MuST-C Corpus for a Comparative Evaluation of Speech Translation Technology. EAMT 2022, pp. 359\u2013360 (2022)"},{"key":"34_CR28","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"437","DOI":"10.1007\/978-3-030-87802-3_40","volume-title":"Speech and Computer","author":"M Musaev","year":"2021","unstructured":"Musaev, M., Mussakhojayeva, S., Khujayorov, I., Khassanov, Y., Ochilov, M., Varol, H.A.: USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments. In: Karpov, A., Potapova, R. (eds.) SPECOM 2021. LNCS (LNAI), vol. 12997, pp. 437\u2013447. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-87802-3_40"},{"key":"34_CR29","doi-asserted-by":"publisher","unstructured":"Mussakhojayeva, S., Janaliyeva, A., Mirzakhmetov, A., Khassanov, Y., Varol, H.A.: KazakhTTS: an open-source kazakh text-to-speech synthesis dataset. In: Proceedings of the Interspeech 2021, pp. 2786\u20132790. https:\/\/doi.org\/10.21437\/Interspeech.2021-2124Open-Source Kazakh Text-to-Speech Synthesis Dataset. arXiv preprint arXiv:2104.08459 (2021)","DOI":"10.21437\/Interspeech.2021-2124Open-Source"},{"key":"34_CR30","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/978-3-030-42058-1_33","volume-title":"Intelligent Information and Database Systems","author":"O Mamyrbayev","year":"2020","unstructured":"Mamyrbayev, O., Alimhan, K., Zhumazhanov, B., Turdalykyzy, T., Gusmanova, F.: End-to-End Speech Recognition in Agglutinative Languages. In: Nguyen, N.T., Jearanaitanakij, K., Selamat, A., Trawi\u0144ski, B., Chittayasothorn, S. (eds.) ACIIDS 2020. LNCS (LNAI), vol. 12034, pp. 391\u2013401. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-42058-1_33"},{"key":"34_CR31","doi-asserted-by":"publisher","unstructured":"Mamyrbayev, O., Alimhan, K., Oralbekova, D., Bekarystankyzy A., Zhumazhanov, B.: Identifying the influence of transfer learning methods in developing an end-to-end automatic speech recognition system with a low data level. Eastern-European J. Enterprise Technol. 1(9(115)), 84\u201392 (2022). https:\/\/doi.org\/10.15587\/1729-4061.2022.252801","DOI":"10.15587\/1729-4061.2022.252801"},{"key":"34_CR32","doi-asserted-by":"publisher","unstructured":"Ma\u043c\u044bp\u0431ae\u0432, O.\u0416., Opa\u043b\u0431e\u043ao\u0432a, \u0414.O., A\u043b\u0438\u043cxa\u043d, K., Othman, M., \u0416y\u043ca\u0436a\u043do\u0432, \u0411.: \u041fp\u0438\u043ce\u043de\u043d\u0438e \u0433\u0438\u0431p\u0438\u0434\u043do\u0439 \u0438\u043d\u0442e\u0433pa\u043b\u044c\u043do\u0439 \u043co\u0434e\u043b\u0438 \u0434\u043b\u044f pac\u043fo\u0437\u043da\u0432a\u043d\u0438\u044f \u043aa\u0437axc\u043ao\u0439 pe\u0447\u0438. News of the National academy of sciences of the republic of Kazakhstan. 1(341), 58\u201368 (2022). https:\/\/doi.org\/10.32014\/2022.2518-1726.117","DOI":"10.32014\/2022.2518-1726.117"},{"key":"34_CR33","unstructured":"Khassanov, Y., Mussakhojayeva, S., Mirzakhmetov, A., Adiyev, A., Nurpeiissov, M., Varol, H.A.: A crowdsourced open-source Kazakh speech corpus and initial speech recognition baseline. In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, pp. 697\u2013706. Association for Computational Linguistics (2021). https:\/\/issai.nu.edu.kz\/ru\/%d0%b3%d0%bb%d0%b0%d0%b2%d0%bd%d0%b0%d1%8f\/#research"},{"key":"34_CR34","unstructured":"NLP-KAZNU\/Kazakh-Uzbek machine translation. https:\/\/github.com\/NLP-KazNU\/Kazakh-Uzbek-machine-translation-on-the-base-of-CSE-model. Access date: 1 Mar 2023"},{"key":"34_CR35","doi-asserted-by":"publisher","unstructured":"Wolf, T., et al.: HuggingFace\u2019s Transformers: State-of-the-art Natural Language Processing. arXiv (2020). https:\/\/doi.org\/10.48550\/arXiv.1910.03771","DOI":"10.48550\/arXiv.1910.03771"},{"key":"34_CR36","doi-asserted-by":"publisher","unstructured":"Baevski, A., Zhou H., Mohamed A., Auli, M.: wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations. arXiv (2020). https:\/\/doi.org\/10.48550\/arXiv.2006.11477.","DOI":"10.48550\/arXiv.2006.11477"},{"key":"34_CR37","doi-asserted-by":"crossref","unstructured":"Mussakhojayeva, S., Janaliyeva, A., Mirzakhmetov, A., Khassanov, Y., Varol, H.A.: KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset. arXiv:2104.08459v3 [eess.AS] (2021)","DOI":"10.21437\/Interspeech.2021-2124"},{"key":"34_CR38","doi-asserted-by":"crossref","unstructured":"Shen, J., et al.: Natural TTS synthesis by conditioning Wavenet on MEL spectrogram predictions. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 4779\u20134783. IEEE (2018)","DOI":"10.1109\/ICASSP.2018.8461368"},{"issue":"01","key":"34_CR39","doi-asserted-by":"publisher","first-page":"6706","DOI":"10.1609\/aaai.v33i01.33016706","volume":"33","author":"N Li","year":"2019","unstructured":"Li, N., Liu, S., Liu, Y., Zhao, S., Liu, M.: Neural speech synthesis with transformer network. Proc. AAAI Conf. Artif. Intell. 33(01), 6706\u20136713 (2019). https:\/\/doi.org\/10.1609\/aaai.v33i01.33016706","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"34_CR40","unstructured":"Sacrebleu: https:\/\/github.com\/mjpost\/sacrebleu. Access date 1 Mar 2023"}],"container-title":["Communications in Computer and Information Science","Advances in Computational Collective Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-41774-0_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,22]],"date-time":"2023-12-22T06:32:14Z","timestamp":1703226734000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-41774-0_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031417733","9783031417740"],"references-count":40,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-41774-0_34","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"22 September 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCCI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Collective Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Budapest","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Hungary","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccci2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccci.pwr.edu.pl\/2023\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"218","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":"59","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":"27% - 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":"3.01","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":"1.86","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}