{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T00:23:02Z","timestamp":1760314982367,"version":"build-2065373602"},"publisher-location":"Cham","reference-count":35,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783032079589","type":"print"},{"value":"9783032079596","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T00:00:00Z","timestamp":1760313600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T00:00:00Z","timestamp":1760313600000},"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":[[2026]]},"DOI":"10.1007\/978-3-032-07959-6_11","type":"book-chapter","created":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T09:22:13Z","timestamp":1760260933000},"page":"144-158","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Whistler Identification in\u00a0Whistled Spanish (Silbo): A Case Study"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-9161-2590","authenticated-orcid":false,"given":"Alejandro","family":"L\u00f3pez-Garc\u00eda","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1676-3101","authenticated-orcid":false,"given":"Mar\u00eda","family":"Alfaro-Contreras","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4747-1884","authenticated-orcid":false,"given":"Julien","family":"Meyer","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8667-4070","authenticated-orcid":false,"given":"Jose J.","family":"Valero-Mas","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,10,13]]},"reference":[{"key":"11_CR1","unstructured":"Baevski, A., Zhou, Y., Mohamed, A., Auli, M.: wav2vec 2.0: a framework for self-supervised learning of speech representations. In: Advances in Neural Information Processing Systems, vol. 33, pp. 12449\u201312460 (2020)"},{"key":"11_CR2","doi-asserted-by":"publisher","first-page":"65","DOI":"10.1016\/j.neunet.2021.03.004","volume":"140","author":"Z Bai","year":"2021","unstructured":"Bai, Z., Zhang, X.L.: Speaker recognition based on deep learning: an overview. Neural Netw. 140, 65\u201399 (2021)","journal-title":"Neural Netw."},{"key":"11_CR3","volume-title":"Whistled Languages","author":"RG Busnel","year":"2013","unstructured":"Busnel, R.G., Classe, A.: Whistled Languages, vol. 13. Springer, Cham (2013)"},{"key":"11_CR4","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1613\/jair.953","volume":"16","author":"NV Chawla","year":"2002","unstructured":"Chawla, N.V., Bowyer, K.W., Hall, L.O., Kegelmeyer, W.P.: Smote: synthetic minority over-sampling technique. J. Artif. Intell. Res. 16, 321\u2013357 (2002)","journal-title":"J. Artif. Intell. Res."},{"key":"11_CR5","first-page":"1","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1\u201330 (2006)","journal-title":"J. Mach. Learn. Res."},{"issue":"8","key":"11_CR6","doi-asserted-by":"publisher","first-page":"23367","DOI":"10.1007\/s11042-023-16438-y","volume":"83","author":"AS Dhanjal","year":"2024","unstructured":"Dhanjal, A.S., Singh, W.: A comprehensive survey on automatic speech recognition using neural networks. Multimed. Tools Appl. 83(8), 23367\u201323412 (2024)","journal-title":"Multimed. Tools Appl."},{"key":"11_CR7","volume-title":"Pattern Classification","author":"RO Duda","year":"2006","unstructured":"Duda, R.O., Hart, P.E., et al.: Pattern Classification. Wiley, Hoboken (2006)"},{"key":"11_CR8","unstructured":"Ganchev, T., Fakotakis, N., Kokkinakis, G.: Comparative evaluation of various MFCC implementations on the speaker verification task. In: Proceedings of the International Conference of Speech and Computer (SPECOM), vol.\u00a01, pp. 191\u2013194 (2005)"},{"key":"11_CR9","doi-asserted-by":"crossref","unstructured":"Han, B., Chen, Z., Liu, B., Qian, Y.: MLP-svnet: a multi-layer perceptrons based network for speaker verification. In: International Conference on Acoustics, Speech and Signal Processing, pp. 7522\u20137526 (2022)","DOI":"10.1109\/ICASSP43922.2022.9747172"},{"key":"11_CR10","doi-asserted-by":"crossref","unstructured":"Han, H., Wang, W.Y., Mao, B.H.: Borderline-smote: a new over-sampling method in imbalanced data sets learning. In: International Conference on Intelligent Computing, pp. 878\u2013887 (2005)","DOI":"10.1007\/11538059_91"},{"key":"11_CR11","doi-asserted-by":"crossref","unstructured":"He, H., Bai, Y., Garcia, E.A., Li, S.: Adasyn: adaptive synthetic sampling approach for imbalanced learning. In: International Joint Conference on Neural Networks, pp. 1322\u20131328 (2008)","DOI":"10.1109\/IJCNN.2008.4633969"},{"key":"11_CR12","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114591","volume":"171","author":"R Jahangir","year":"2021","unstructured":"Jahangir, R., Teh, Y.W., Nweke, H.F., Mujtaba, G., Al-Garadi, M.A., Ali, I.: Speaker identification through artificial intelligence techniques: a comprehensive review and research challenges. Expert Syst. Appl. 171, 114591 (2021)","journal-title":"Expert Syst. Appl."},{"key":"11_CR13","doi-asserted-by":"crossref","unstructured":"Jakubiak, A.: Whistle-to-text: automatic recognition of the silbo gomero whistled language. In: Proceedings of the 24th INTERSPEECH Conference, pp. 3402\u20133406 (2023)","DOI":"10.21437\/Interspeech.2023-989"},{"issue":"2","key":"11_CR14","doi-asserted-by":"publisher","first-page":"893","DOI":"10.1121\/1.3609117","volume":"130","author":"AT Johansson","year":"2011","unstructured":"Johansson, A.T., White, P.R.: An adaptive filter-based method for robust, automatic detection and frequency estimation of whistles. J. Acoust. Soc. Am. 130(2), 893\u2013903 (2011)","journal-title":"J. Acoust. Soc. Am."},{"key":"11_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2022.109826","volume":"131","author":"V Karthikeyan","year":"2022","unstructured":"Karthikeyan, V., Suja Priyadharsini, S.: Adaptive boosted random forest-support vector machine based classification scheme for speaker identification. Appl. Soft Comput. 131, 109826 (2022)","journal-title":"Appl. Soft Comput."},{"issue":"17","key":"11_CR16","first-page":"1","volume":"18","author":"G Lema\u00eetre","year":"2017","unstructured":"Lema\u00eetre, G., Nogueira, F., Aridas, C.K.: Imbalanced-learn: a python toolbox to tackle the curse of imbalanced datasets in machine learning. J. Mach. Learn. Res. 18(17), 1\u20135 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR17","doi-asserted-by":"publisher","first-page":"9411","DOI":"10.1007\/s11042-020-10073-7","volume":"80","author":"M Malik","year":"2021","unstructured":"Malik, M., Malik, M.K., Mehmood, K., Makhdoom, I.: Automatic speech recognition: a survey. Multimed. Tools Appl. 80, 9411\u20139457 (2021)","journal-title":"Multimed. Tools Appl."},{"key":"11_CR18","doi-asserted-by":"publisher","first-page":"18","DOI":"10.25080\/Majora-7b98e3ed-003","volume":"2015","author":"B McFee","year":"2015","unstructured":"McFee, B., Raffel, C., Liang, D., Ellis, D.P., McVicar, M., Battenberg, E., Nieto, O.: librosa: audio and music signal analysis in python. SciPy 2015, 18\u201324 (2015)","journal-title":"SciPy"},{"key":"11_CR19","doi-asserted-by":"crossref","unstructured":"Meyer, J.: Whistled languages. A Worldwide Inquiry on Human Whistled Speech (2015)","DOI":"10.1007\/978-3-662-45837-2"},{"issue":"1","key":"11_CR20","doi-asserted-by":"publisher","first-page":"493","DOI":"10.1146\/annurev-linguistics-011619-030444","volume":"7","author":"J Meyer","year":"2021","unstructured":"Meyer, J.: Environmental and linguistic typology of whistled languages. Ann. Rev. Linguist. 7(1), 493\u2013510 (2021)","journal-title":"Ann. Rev. Linguist."},{"key":"11_CR21","doi-asserted-by":"publisher","first-page":"99","DOI":"10.4000\/geolinguistique.373","volume":"17","author":"J Meyer","year":"2017","unstructured":"Meyer, J., D\u00edaz Reyes, D.: Geoling\u00fc\u00edstica de los lenguajes silbados del mundo, con un enfoque en el espa\u00f1ol silbado. G\u00e9olinguistique 17, 99\u2013124 (2017)","journal-title":"G\u00e9olinguistique"},{"key":"11_CR22","doi-asserted-by":"publisher","DOI":"10.3389\/fpsyg.2021.689501","volume":"12","author":"J Meyer","year":"2021","unstructured":"Meyer, J., Magnasco, M.O., Reiss, D.: The relevance of human whistled languages for the analysis and decoding of dolphin communication. Front. Psychol. 12, 689501 (2021)","journal-title":"Front. Psychol."},{"key":"11_CR23","unstructured":"Meyer, J., Rolland, V., Socas, T., D\u00edaz, D.: A sentence comprehension test with whistled Spanish experts. In: ExLing Conferences, pp. 65\u201368 (2024)"},{"issue":"1","key":"11_CR24","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/s10772-021-09876-2","volume":"25","author":"A Mittal","year":"2022","unstructured":"Mittal, A., Dua, M.: Automatic speaker verification systems and spoof detection techniques: review and analysis. Int. J. Speech Technol. 25(1), 105\u2013134 (2022)","journal-title":"Int. J. Speech Technol."},{"key":"11_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2021.107005","volume":"90","author":"R Mohd Hanifa","year":"2021","unstructured":"Mohd Hanifa, R., Isa, K., Mohamad, S.: A review on speaker recognition: technology and challenges. Comput. Electr. Eng. 90, 107005 (2021)","journal-title":"Comput. Electr. Eng."},{"issue":"1","key":"11_CR26","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1186\/s40537-024-00943-4","volume":"11","author":"M Mujahid","year":"2024","unstructured":"Mujahid, M., et al.: Data oversampling and imbalanced datasets: an investigation of performance for machine learning and feature engineering. J. Big Data 11(1), 87 (2024)","journal-title":"J. Big Data"},{"key":"11_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.specom.2024.103058","volume":"159","author":"AT Ngoc","year":"2024","unstructured":"Ngoc, A.T., Meyer, J., Meunier, F.: The effect of musical expertise on whistled vowel identification. Speech Commun. 159, 103058 (2024)","journal-title":"Speech Commun."},{"key":"11_CR28","doi-asserted-by":"crossref","unstructured":"O\u2019brien, B., Marcyzk, A.: A spectrotemporal modulation application for distinguishing modal and whistled speech. Int. J. Speech Technol. 1\u20138 (2025)","DOI":"10.1007\/s10772-025-10185-1"},{"key":"11_CR29","doi-asserted-by":"crossref","unstructured":"Panayotov, V., Chen, G., Povey, D., Khudanpur, S.: Librispeech: an ASR corpus based on public domain audio books. In: International Conference on Acoustics, Speech and Signal Processing, pp. 5206\u20135210 (2015)","DOI":"10.1109\/ICASSP.2015.7178964"},{"key":"11_CR30","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"11_CR31","unstructured":"Radford, A., Kim, J.W., Xu, T., Brockman, G., McLeavey, C., Sutskever, I.: Robust speech recognition via large-scale weak supervision. In: Proceedings of the 40th International Conference on Machine Learning, pp. 28492\u201328518 (2023)"},{"key":"11_CR32","doi-asserted-by":"crossref","unstructured":"Tapiador, F.J.: Heritage: a treasure chest. In: The Geography of Spain: A Complete Synthesis, pp. 405\u2013419 (2020)","DOI":"10.1007\/978-3-030-18907-5_24"},{"key":"11_CR33","doi-asserted-by":"publisher","first-page":"250","DOI":"10.1016\/j.eswa.2017.08.015","volume":"90","author":"SS Tirumala","year":"2017","unstructured":"Tirumala, S.S., Shahamiri, S.R., Garhwal, A.S., Wang, R.: Speaker identification features extraction methods: a systematic review. Expert Syst. Appl. 90, 250\u2013271 (2017)","journal-title":"Expert Syst. Appl."},{"key":"11_CR34","unstructured":"Wolf, T., et\u00a0al.: Transformers: state-of-the-art natural language processing. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing: System Demonstrations, pp. 38\u201345 (2020)"},{"key":"11_CR35","doi-asserted-by":"crossref","unstructured":"Yerramreddy, D.R., et\u00a0al.: Speaker identification using MFCC feature extraction: a comparative study using GMM, CNN, RNN, KNN and random forest classifier. In: International Conference on Trends in Electrical, Electronics, and Computer Engineering, pp. 287\u2013292 (2023)","DOI":"10.1109\/TEECCON59234.2023.10335892"}],"container-title":["Lecture Notes in Computer Science","Speech and Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-07959-6_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T09:22:20Z","timestamp":1760260940000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-07959-6_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10,13]]},"ISBN":["9783032079589","9783032079596"],"references-count":35,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-07959-6_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10,13]]},"assertion":[{"value":"13 October 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"SPECOM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Speech and Computer","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Szeged","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":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 October 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 October 2025","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":"specom2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/specom.inf.u-szeged.hu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}