{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,7]],"date-time":"2026-03-07T17:43:23Z","timestamp":1772905403779,"version":"3.50.1"},"reference-count":95,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T00:00:00Z","timestamp":1604880000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T00:00:00Z","timestamp":1604880000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61902154"],"award-info":[{"award-number":["61902154"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"publisher","award":["BK2019043526"],"award-info":[{"award-number":["BK2019043526"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["JUSRP11924"],"award-info":[{"award-number":["JUSRP11924"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology","award":["FM-2019-06"],"award-info":[{"award-number":["FM-2019-06"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Artif Intell Rev"],"published-print":{"date-parts":[[2021,6]]},"DOI":"10.1007\/s10462-020-09932-4","type":"journal-article","created":{"date-parts":[[2020,11,9]],"date-time":"2020-11-09T16:07:06Z","timestamp":1604938026000},"page":"3575-3597","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":64,"title":["Bioacoustic signal denoising: a review"],"prefix":"10.1007","volume":"54","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7707-9963","authenticated-orcid":false,"given":"Jie","family":"Xie","sequence":"first","affiliation":[]},{"given":"Juan G.","family":"Colonna","sequence":"additional","affiliation":[]},{"given":"Jinglan","family":"Zhang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2020,11,9]]},"reference":[{"key":"9932_CR1","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.eswa.2016.12.019","volume":"72","author":"JB Alonso","year":"2017","unstructured":"Alonso JB, Cabrera J, Shyamnani R, Travieso CM, Bola\u00f1os F, Garc\u00eda A, Villegas A, Wainwright M (2017) Automatic anuran identification using noise removal and audio activity detection. Expert Syst Appl 72:83\u201392","journal-title":"Expert Syst Appl"},{"issue":"3","key":"9932_CR2","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1046\/j.1439-0310.2003.00866.x","volume":"109","author":"MC Baker","year":"2003","unstructured":"Baker MC, Logue DM (2003) Population differentiation in a complex bird sound: a comparison of three bioacoustical analysis procedures. Ethology 109(3):223\u2013242","journal-title":"Ethology"},{"issue":"3","key":"9932_CR3","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1111\/j.1557-9263.2007.00109.x","volume":"78","author":"MC Baker","year":"2007","unstructured":"Baker MC, Logue DM (2007) A comparison of three noise reduction procedures applied to bird vocal signals. J Field Ornithol 78(3):240\u2013253","journal-title":"J Field Ornithol"},{"issue":"12","key":"9932_CR4","doi-asserted-by":"crossref","first-page":"1524","DOI":"10.1016\/j.patrec.2009.09.014","volume":"31","author":"R Bardeli","year":"2010","unstructured":"Bardeli R, Wolff D, Kurth F, Koch M, Tauchert KH, Frommolt KH (2010) Detecting bird sounds in a complex acoustic environment and application to bioacoustic monitoring. Pattern Recognit Lett 31(12):1524\u20131534","journal-title":"Pattern Recognit Lett"},{"key":"9932_CR5","doi-asserted-by":"crossref","unstructured":"Barmatz H, Klein D, Vortman Y, Toledo S, Lavner Y (2019) A method for automatic segmentation and parameter estimation of bird vocalizations. In: 2019 International Conference on Systems, Signals and Image Processing (IWSSIP), pp 211\u2013216","DOI":"10.1109\/IWSSIP.2019.8787282"},{"issue":"5","key":"9932_CR6","doi-asserted-by":"crossref","first-page":"2889","DOI":"10.1121\/1.3562166","volume":"129","author":"MF Baumgartner","year":"2011","unstructured":"Baumgartner MF, Mussoline SE (2011) A generalized baleen whale call detection and classification system. J Acoust Soc Am 129(5):2889\u20132902","journal-title":"J Acoust Soc Am"},{"key":"9932_CR7","doi-asserted-by":"crossref","first-page":"200","DOI":"10.1016\/j.ecoinf.2014.08.009","volume":"24","author":"C Bedoya","year":"2014","unstructured":"Bedoya C, Isaza C, Daza JM, L\u00f3pez JD (2014) Automatic recognition of anuran species based on syllable identification. Ecol Inf 24:200\u2013209","journal-title":"Ecol Inf"},{"issue":"1","key":"9932_CR8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-019-47335-w","volume":"9","author":"C Bergler","year":"2019","unstructured":"Bergler C, Schr\u00f6ter H, Cheng RX, Barth V, Weber M, N\u00f6th E, Hofer H, Maier A (2019) Orca-spot: an automatic killer whale sound detection toolkit using deep learning. Sci Rep 9(1):1\u201317","journal-title":"Sci Rep"},{"issue":"1","key":"9932_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-018-37186-2","volume":"9","author":"PC Bermant","year":"2019","unstructured":"Bermant PC, Bronstein MM, Wood RJ, Gero S, Gruber DF (2019) Deep machine learning techniques for the detection and classification of sperm whale bioacoustics. Sci Rep 9(1):1\u201310","journal-title":"Sci Rep"},{"issue":"2","key":"9932_CR10","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1109\/TASSP.1979.1163209","volume":"27","author":"S Boll","year":"1979","unstructured":"Boll S (1979) Suppression of acoustic noise in speech using spectral subtraction. IEEE Trans Acoust Speech Sig Process 27(2):113\u2013120","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"issue":"6","key":"9932_CR11","doi-asserted-by":"crossref","first-page":"1173","DOI":"10.1109\/TASL.2008.925872","volume":"16","author":"TS Brandes","year":"2008","unstructured":"Brandes TS (2008) Feature vector selection and use with hidden markov models to identify frequency-modulated bioacoustic signals amidst noise. IEEE Trans Audio Speech Language Process 16(6):1173\u20131180","journal-title":"IEEE Trans Audio Speech Language Process"},{"key":"9932_CR12","doi-asserted-by":"crossref","first-page":"5010","DOI":"10.1109\/ACCESS.2017.2782778","volume":"6","author":"A Brown","year":"2017","unstructured":"Brown A, Garg S, Montgomery J (2017) Automatic and efficient denoising of bioacoustics recordings using mmse stsa. IEEE Access 6:5010\u20135022","journal-title":"IEEE Access"},{"key":"9932_CR13","doi-asserted-by":"crossref","first-page":"105501","DOI":"10.1016\/j.asoc.2019.105501","volume":"81","author":"A Brown","year":"2019","unstructured":"Brown A, Garg S, Montgomery J (2019) Automatic rain and cicada chorus filtering of bird acoustic data. Appl Soft Comput 81:105501","journal-title":"Appl Soft Comput"},{"key":"9932_CR14","doi-asserted-by":"publisher","unstructured":"Cai J, Ee D, Pham B, Roe P, Zhang J (2007) Sensor network for the monitoring of ecosystem: Bird species recognition. In: 2007 3rd International Conference on Intelligent Sensors, Sensor Networks and Information, pp 293\u2013298, https:\/\/doi.org\/10.1109\/ISSNIP.2007.4496859","DOI":"10.1109\/ISSNIP.2007.4496859"},{"key":"9932_CR15","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/TMM.2019.2925956","volume":"22","author":"S Chandrakala","year":"2019","unstructured":"Chandrakala S, Jayalakshmi S (2019) Generative model-driven representation learning in a hybrid framework for environmental audio scene and sound event recognition. IEEE Trans Multimed 22:3\u201314","journal-title":"IEEE Trans Multimed"},{"issue":"5","key":"9932_CR16","doi-asserted-by":"crossref","first-page":"1270","DOI":"10.1016\/j.camwa.2012.03.071","volume":"64","author":"WP Chen","year":"2012","unstructured":"Chen WP, Chen SS, Lin CC, Chen YZ, Lin WC (2012) Automatic recognition of frog calls using a multi-stage average spectrum. Comp Math Appl 64(5):1270\u20131281","journal-title":"Comp Math Appl"},{"key":"9932_CR17","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.dsp.2018.07.009","volume":"82","author":"JG Colonna","year":"2018","unstructured":"Colonna JG, Nakamura EF (2018) Unsupervised selection of the singular spectrum components based on information theory for bioacoustic signal filtering. Dig Sig Process 82:64\u201379","journal-title":"Dig Sig Process"},{"issue":"5","key":"9932_CR18","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1111\/btp.12593","volume":"50","author":"JL Deichmann","year":"2018","unstructured":"Deichmann JL, Acevedo-Charry O, Barclay L, Burivalova Z, Campos-Cerqueira M, d\u2019Horta F, Game ET, Gottesman BL, Hart PJ, Kalan AK et al (2018) It\u2019s time to listen: there is much to be learned from the sounds of tropical ecosystems. Biotropica 50(5):713\u2013718","journal-title":"Biotropica"},{"key":"9932_CR19","volume-title":"Proakis JG (2000) Discrete-time processing of speech signals. Institute of Electrical and Electronics Engineers","author":"JR Deller","year":"1993","unstructured":"Deller JR, Hansen JHL (1993) Proakis JG (2000) Discrete-time processing of speech signals. Institute of Electrical and Electronics Engineers. Macmillan, New York"},{"issue":"3","key":"9932_CR20","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1016\/j.specom.2008.09.003","volume":"51","author":"H Ding","year":"2009","unstructured":"Ding H, Soon Y, Koh SN, Yeo CK (2009) A spectral filtering method based on hybrid wiener filters for speech enhancement. Speech Commun 51(3):259\u2013267","journal-title":"Speech Commun"},{"issue":"4","key":"9932_CR21","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1109\/TASLP.2019.2894909","volume":"27","author":"N Dionelis","year":"2019","unstructured":"Dionelis N, Brookes M (2019) Modulation-domain kalman filtering for monaural blind speech denoising and dereverberation. IEEE\/ACM Trans Audio Speech Language Process 27(4):799\u2013814","journal-title":"IEEE\/ACM Trans Audio Speech Language Process"},{"issue":"3","key":"9932_CR22","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1093\/biomet\/81.3.425","volume":"81","author":"DL Donoho","year":"1994","unstructured":"Donoho DL, Johnstone JM (1994) Ideal spatial adaptation by wavelet shrinkage. Biometrika 81(3):425\u2013455","journal-title":"Biometrika"},{"issue":"6","key":"9932_CR23","doi-asserted-by":"crossref","first-page":"1109","DOI":"10.1109\/TASSP.1984.1164453","volume":"32","author":"Y Ephraim","year":"1984","unstructured":"Ephraim Y, Malah D (1984) Speech enhancement using a minimum-mean square error short-time spectral amplitude estimator. IEEE Trans Acoust Speech Sig Process 32(6):1109\u20131121","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"issue":"2","key":"9932_CR24","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1109\/TASSP.1985.1164550","volume":"33","author":"Y Ephraim","year":"1985","unstructured":"Ephraim Y, Malah D (1985) Speech enhancement using a minimum mean-square error log-spectral amplitude estimator. IEEE Trans Acoust Speech Sig Process 33(2):443\u2013445","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"key":"9932_CR25","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.apacoust.2017.01.025","volume":"120","author":"M Esfahanian","year":"2017","unstructured":"Esfahanian M, Erdol N, Gerstein E, Zhuang H (2017) Two-stage detection of north atlantic right whale upcalls using local binary patterns and machine learning algorithms. Appl Acoust 120:158\u2013166","journal-title":"Appl Acoust"},{"key":"9932_CR26","series-title":"Springer handbook of acoustics","first-page":"785","volume-title":"Animal bioacoustics","author":"N Fletcher","year":"2007","unstructured":"Fletcher N (2007) Animal bioacoustics. Springer handbook of acoustics. Springer, Berlin, pp 785\u2013804"},{"key":"9932_CR27","doi-asserted-by":"crossref","unstructured":"Fu SW, Tsao Y, Lu X (2016) SNR-aware convolutional neural network modeling for speech enhancement. In: Proceedings of the Annual Conference of the International Speech Communication Association, Interspeech, pp 3768\u20133772","DOI":"10.21437\/Interspeech.2016-211"},{"key":"9932_CR28","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1007\/978-3-030-00353-1_27","volume-title":"Applied Computer Sciences in Engineering","author":"A G\u00f3mez","year":"2018","unstructured":"G\u00f3mez A, Ugarte JP, G\u00f3mez DMM (2018) Bioacoustic signals denoising using the undecimated discrete wavelet transform. In: Figueroa-Garc\u00eda JC, Villegas JG, Orozco-Arroyave JR, Maya Duque PA (eds) Applied Computer Sciences in Engineering. Springer, Cham, pp 300\u2013308"},{"issue":"1","key":"9932_CR29","doi-asserted-by":"crossref","first-page":"188","DOI":"10.1121\/1.2735111","volume":"122","author":"BM Gur","year":"2007","unstructured":"Gur BM, Niezrecki C (2007) Autocorrelation based denoising of manatee vocalizations using the undecimated discrete wavelet transform. J Acoust Soc Am 122(1):188\u2013199","journal-title":"J Acoust Soc Am"},{"issue":"4","key":"9932_CR30","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1121\/1.3557031","volume":"129","author":"MB Gur","year":"2011","unstructured":"Gur MB, Niezrecki C (2011) A wavelet packet adaptive filtering algorithm for enhancing manatee vocalizations. J Acoust Soc Am 129(4):2059\u20132067","journal-title":"J Acoust Soc Am"},{"key":"9932_CR31","unstructured":"H\u00e4rm\u00e4 A (2003) Automatic identification of bird species based on sinusoidal modeling of syllables. In: Acoustics, Speech, and Signal Processing, 2003. Proceedings.(ICASSP\u201903). 2003 IEEE International Conference on, IEEE, vol\u00a05, pp V\u2013545"},{"key":"9932_CR32","doi-asserted-by":"crossref","first-page":"557","DOI":"10.1080\/09524622.2019.1621776","volume":"29","author":"O Heim","year":"2019","unstructured":"Heim O, Heim DM, Marggraf L, Voigt CC, Zhang X, Luo Y, Zheng J (2019) Variant maps for bat echolocation call identification algorithms. Bioacoustics 29:557\u2013571","journal-title":"Bioacoustics"},{"issue":"11","key":"9932_CR33","doi-asserted-by":"crossref","first-page":"5451","DOI":"10.1016\/j.eswa.2014.02.021","volume":"41","author":"A Henr\u00edquez","year":"2014","unstructured":"Henr\u00edquez A, Alonso JB, Travieso CM, Rodr\u00edguez-Herrera B, Bola\u00f1os F, Alp\u00edzar P, L\u00f3pez-de Ipina K, Henr\u00edquez P (2014) An automatic acoustic bat identification system based on the audible spectrum. Expert Syst Appl 41(11):5451\u20135465","journal-title":"Expert Syst Appl"},{"key":"9932_CR34","doi-asserted-by":"publisher","unstructured":"Hu W, Van Nghia Tran, Bulusu N, Chou CT, Jha S, Taylor A (2005) The design and evaluation of a hybrid sensor network for cane-toad monitoring. In: IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005., pp 503\u2013508, https:\/\/doi.org\/10.1109\/IPSN.2005.1440984","DOI":"10.1109\/IPSN.2005.1440984"},{"key":"9932_CR35","doi-asserted-by":"crossref","unstructured":"Hu Y, Loizou PC (2006) Evaluation of objective measures for speech enhancement. In: Ninth International Conference on Spoken Language Processing","DOI":"10.21437\/Interspeech.2006-84"},{"key":"9932_CR36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.asoc.2014.01.030","volume":"19","author":"CJ Huang","year":"2014","unstructured":"Huang CJ, Chen YJ, Chen HM, Jian JJ, Tseng SC, Yang YJ, Hsu PA (2014) Intelligent feature extraction and classification of anuran vocalizations. Appl Soft Comput 19:1\u20137","journal-title":"Appl Soft Comput"},{"issue":"2","key":"9932_CR37","first-page":"1","volume":"3","author":"W Hussein","year":"2012","unstructured":"Hussein W, Hussein M, Becker T (2012) Spectrogram enhancement by edge detection approach applied to bioacoustics calls classification. Sig Image Process 3(2):1","journal-title":"Sig Image Process"},{"issue":"11","key":"9932_CR38","doi-asserted-by":"crossref","first-page":"1800","DOI":"10.1109\/TASLP.2015.2443983","volume":"23","author":"MT Islam","year":"2015","unstructured":"Islam MT, Shahnaz C, Zhu WP, Ahmad MO (2015) Speech enhancement based on student $$ t $$ modeling of teager energy operated perceptual wavelet packet coefficients and a custom thresholding function. IEEE\/ACM Trans Audio Speech Language Process 23(11):1800\u20131811","journal-title":"IEEE\/ACM Trans Audio Speech Language Process"},{"key":"9932_CR39","doi-asserted-by":"crossref","unstructured":"Kandia V, Stylianou Y, Dutoit T (2008) Improve the accuracy of tdoa measurement using the teager-kaiser energy operator. In: 2008 New Trends for Environmental Monitoring Using Passive Systems, pp 1\u20136","DOI":"10.1109\/PASSIVE.2008.4786987"},{"issue":"5","key":"9932_CR40","doi-asserted-by":"crossref","first-page":"2484","DOI":"10.1121\/1.4743167","volume":"108","author":"HG Kim","year":"2000","unstructured":"Kim HG, Obermayer K, Bode M, Ruwisch D (2000) Real-time noise canceling based on spectral minimum detection and diffusive gain factors. J Acoust Soc Am 108(5):2484\u20132484","journal-title":"J Acoust Soc Am"},{"key":"9932_CR41","doi-asserted-by":"crossref","unstructured":"Klatt D (1982) Prediction of perceived phonetic distance from critical-band spectra: A first step. In: ICASSP\u201982. IEEE International Conference on Acoustics, Speech, and Signal Processing, IEEE, vol\u00a07, pp 1278\u20131281","DOI":"10.1109\/ICASSP.1982.1171512"},{"key":"9932_CR42","doi-asserted-by":"crossref","first-page":"337","DOI":"10.1080\/09524622.2019.1606734","volume":"29","author":"EC Knight","year":"2019","unstructured":"Knight EC, Poo Hernandez S, Bayne EM, Bulitko V, Tucker BV (2019) Pre-processing spectrogram parameters improve the accuracy of bioacoustic classification using convolutional neural networks. Bioacoustics 29:337\u2013355","journal-title":"Bioacoustics"},{"issue":"6","key":"9932_CR43","doi-asserted-by":"crossref","first-page":"1183","DOI":"10.1109\/TASLP.2017.2690562","volume":"25","author":"NR Koluguri","year":"2017","unstructured":"Koluguri NR, Meenakshi GN, Ghosh PK (2017) Spectrogram enhancement using multiple window savitzky-golay (mwsg) filter for robust bird sound detection. IEEE\/ACM Trans Audio Speech Language Process 25(6):1183\u20131192","journal-title":"IEEE\/ACM Trans Audio Speech Language Process"},{"key":"9932_CR44","doi-asserted-by":"publisher","unstructured":"Kong Q, Xu Y, Plumbley MD (2017) Joint detection and classification convolutional neural network on weakly labelled bird audio detection. In: 2017 25th European Signal Processing Conference (EUSIPCO), pp 1749\u20131753, https:\/\/doi.org\/10.23919\/EUSIPCO.2017.8081509","DOI":"10.23919\/EUSIPCO.2017.8081509"},{"issue":"4","key":"9932_CR45","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1109\/TASSP.1981.1163642","volume":"29","author":"L Lamel","year":"1981","unstructured":"Lamel L, Rabiner L, Rosenberg A, Wilpon J (1981) An improved endpoint detector for isolated word recognition. IEEE Trans Acoust Speech Sig Process 29(4):777\u2013785","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"key":"9932_CR46","doi-asserted-by":"publisher","unstructured":"Le Roux J, Hershey JR, Weninger F (2015) Deep nmf for speech separation. In: 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp 66\u201370, https:\/\/doi.org\/10.1109\/ICASSP.2015.7177933","DOI":"10.1109\/ICASSP.2015.7177933"},{"key":"9932_CR47","doi-asserted-by":"crossref","unstructured":"Lefkimmiatis S (2018) Universal denoising networks: a novel cnn architecture for image denoising. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 3204\u20133213","DOI":"10.1109\/CVPR.2018.00338"},{"issue":"5","key":"9932_CR48","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1016\/j.specom.2010.04.009","volume":"53","author":"J Li","year":"2011","unstructured":"Li J, Sakamoto S, Hongo S, Akagi M, Suzuki Y (2011) Two-stage binaural speech enhancement with wiener filter for high-quality speech communication. Speech Commun 53(5):677\u2013689","journal-title":"Speech Commun"},{"issue":"3","key":"9932_CR49","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1109\/TASSP.1978.1163086","volume":"26","author":"J Lim","year":"1978","unstructured":"Lim J, Oppenheim A (1978) All-pole modeling of degraded speech. IEEE Trans Acoust Speech Sig Process 26(3):197\u2013210","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"key":"9932_CR50","doi-asserted-by":"crossref","unstructured":"Lin T, Yang H, Huang J, Yao C, Lien Y, Wang P, Hu F (2019) Evaluating changes in the marine soundscape of an offshore wind farm via the machine learning-based source separation. In: 2019 IEEE Underwater Technology (UT), pp 1\u20136","DOI":"10.1109\/UT.2019.8734295"},{"key":"9932_CR51","doi-asserted-by":"crossref","unstructured":"Lin TH, Tsao Y (2019) Source separation in ecoacoustics: A roadmap towards versatile soundscape information retrieval. Remote Sens Ecol Conserv 1\u201312","DOI":"10.1002\/rse2.141"},{"issue":"3","key":"9932_CR52","doi-asserted-by":"crossref","first-page":"2477","DOI":"10.1121\/1.4816572","volume":"134","author":"TH Lin","year":"2013","unstructured":"Lin TH, Chou LS, Akamatsu T, Chan HC, Chen CF (2013) An automatic detection algorithm for extracting the representative frequency of cetacean tonal sounds. J Acoust Soc Am 134(3):2477\u20132485","journal-title":"J Acoust Soc Am"},{"issue":"1","key":"9932_CR53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1038\/s41598-016-0028-x","volume":"7","author":"TH Lin","year":"2017","unstructured":"Lin TH, Fang SH, Tsao Y (2017) Improving biodiversity assessment via unsupervised separation of biological sounds from long-duration recordings. Sci Rep 7(1):1\u201310","journal-title":"Sci Rep"},{"key":"9932_CR54","doi-asserted-by":"crossref","unstructured":"Lostanlen V, Palmer K, Knight E, Clark C, Klinck H, Farnsworth A, Wong T, Cramer J, Bello JP (2019) Long-distance detection of bioacoustic events with per-channel energy normalization. arXiv preprint arXiv:191100417","DOI":"10.33682\/ts6e-sn53"},{"key":"9932_CR55","doi-asserted-by":"crossref","unstructured":"Lu X, Tsao Y, Matsuda S, Hori C (2013) Speech enhancement based on deep denoising autoencoder. In: Proceedings Interspeech, pp 436\u2013440","DOI":"10.21437\/Interspeech.2013-130"},{"key":"9932_CR56","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.eswa.2017.11.016","volume":"95","author":"A Luque","year":"2018","unstructured":"Luque A, Romero-Lemos J, Carrasco A, Barbancho J (2018) Non-sequential automatic classification of anuran sounds for the estimation of climate-change indicators. Expert Syst Appl 95:248\u2013260","journal-title":"Expert Syst Appl"},{"issue":"2","key":"9932_CR57","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1109\/TASSP.1980.1163394","volume":"28","author":"R McAulay","year":"1980","unstructured":"McAulay R, Malpass M (1980) Speech enhancement using a soft-decision noise suppression filter. IEEE Trans Acoust Speech Sig Process 28(2):137\u2013145","journal-title":"IEEE Trans Acoust Speech Sig Process"},{"issue":"2","key":"9932_CR58","first-page":"55","volume":"32","author":"DK Mellinger","year":"2004","unstructured":"Mellinger DK (2004) A comparison of methods for detecting right whale calls. Can Acoust 32(2):55\u201365","journal-title":"Can Acoust"},{"key":"9932_CR59","doi-asserted-by":"crossref","unstructured":"Neal L, Briggs F, Raich R, Fern XZ (2011) Time-frequency segmentation of bird song in noisy acoustic environments. In: Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on, IEEE, pp 2012\u20132015","DOI":"10.1109\/ICASSP.2011.5946906"},{"issue":"2","key":"9932_CR60","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1121\/1.5087827","volume":"145","author":"T Oikarinen","year":"2019","unstructured":"Oikarinen T, Srinivasan K, Meisner O, Hyman JB, Parmar S, Fanucci-Kiss A, Desimone R, Landman R, Feng G (2019) Deep convolutional network for animal sound classification and source attribution using dual audio recordings. J Acoust Soc Am 145(2):654\u2013662","journal-title":"J Acoust Soc Am"},{"key":"9932_CR61","unstructured":"Pandey PC, Pratapwar SS, Lehana PK (2004) Enhancement of electrolaryngeal speech by reducing leakage noise using spectral subtraction with quantile based dynamic estimation of noise. In: Proceeding of the 18th international congress on acoustics ICA 2004, pp 3029\u20133032"},{"key":"9932_CR62","doi-asserted-by":"crossref","unstructured":"Patti A, Williamson GA (2013) Methods for classification of nocturnal migratory bird vocalizations using pseudo wigner-ville transform. In: 2013 IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, pp 758\u2013762","DOI":"10.1109\/ICASSP.2013.6637750"},{"issue":"3","key":"9932_CR63","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1525\/bio.2011.61.3.6","volume":"61","author":"BC Pijanowski","year":"2011","unstructured":"Pijanowski BC, Villanueva-Rivera LJ, Dumyahn SL, Farina A, Krause BL, Napoletano BM, Gage SH, Pieretti N (2011) Soundscape ecology: the science of sound in the landscape. BioScience 61(3):203\u2013216","journal-title":"BioScience"},{"key":"9932_CR64","unstructured":"Pourhomayoun M, Dugan P, Popescu M, Clark C (2013) Bioacoustic signal classification based on continuous region processing, grid masking and artificial neural network. arXiv preprint arXiv:13053635"},{"issue":"1","key":"9932_CR65","doi-asserted-by":"crossref","first-page":"e0146790","DOI":"10.1371\/journal.pone.0146790","volume":"11","author":"N Priyadarshani","year":"2016","unstructured":"Priyadarshani N, Marsland S, Castro I, Punchihewa A (2016) Birdsong denoising using wavelets. PloS One 11(1):e0146790","journal-title":"PloS One"},{"issue":"5","key":"9932_CR66","doi-asserted-by":"crossref","first-page":"01445","DOI":"10.1111\/jav.01447","volume":"49","author":"N Priyadarshani","year":"2018","unstructured":"Priyadarshani N, Marsland S, Castro I (2018) Automated birdsong recognition in complex acoustic environments: a review. J Avian Biol 49(5):jav\u201301447","journal-title":"J Avian Biol"},{"key":"9932_CR67","unstructured":"Quackenbush SR (1995) Objective measures of speech quality. PhD thesis, Georgia Institute of Technology"},{"issue":"1","key":"9932_CR68","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1121\/1.2932070","volume":"124","author":"Y Ren","year":"2008","unstructured":"Ren Y, Johnson MT, Tao J (2008) Perceptually motivated wavelet packet transform for bioacoustic signal enhancement. J Acoust Soc Am 124(1):316\u2013327","journal-title":"J Acoust Soc Am"},{"key":"9932_CR69","doi-asserted-by":"crossref","unstructured":"Rethage D, Pons J, Serra X (2018) A wavenet for speech denoising. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp 5069\u20135073","DOI":"10.1109\/ICASSP.2018.8462417"},{"key":"9932_CR70","doi-asserted-by":"crossref","unstructured":"Rix AW, Beerends JG, Hollier MP, Hekstra AP (2001) Perceptual evaluation of speech quality (pesq)-a new method for speech quality assessment of telephone networks and codecs. In: 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No. 01CH37221), IEEE, vol\u00a02, pp 749\u2013752","DOI":"10.1109\/ICASSP.2001.941023"},{"key":"9932_CR71","first-page":"113","volume-title":"Unsupervised Bioacoustic Segmentation by Hierarchical Dirichlet Process Hidden Markov Model","author":"V Roger","year":"2018","unstructured":"Roger V, Bartcus M, Chamroukhi F, Glotin H (2018) Unsupervised Bioacoustic Segmentation by Hierarchical Dirichlet Process Hidden Markov Model. Springer, Cham, pp 113\u2013130"},{"issue":"2","key":"9932_CR72","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1007\/s11265-016-1155-0","volume":"90","author":"JF Ruiz-Mu\u00f1oz","year":"2018","unstructured":"Ruiz-Mu\u00f1oz JF, You Z, Raich R, Fern XZ (2018) Dictionary learning for bioacoustics monitoring with applications to species classification. J Sig Process Syst 90(2):233\u2013247","journal-title":"J Sig Process Syst"},{"issue":"6","key":"9932_CR73","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pone.0217977","volume":"14","author":"TO Sim\u00f5es Amorim","year":"2019","unstructured":"Sim\u00f5es Amorim TO, Rezende de Castro F, Rodrigues Moron J, Ribeiro Duque B, Couto Di Tullio J, Resende Secchi E, Andriolo A (2019) Integrative bioacoustics discrimination of eight delphinid species in the western south atlantic ocean. PLOS ONE 14(6):1\u201317","journal-title":"PLOS ONE"},{"key":"9932_CR74","doi-asserted-by":"crossref","unstructured":"Souza LS, Gatto BB, Fukui K (2018) Grassmann singular spectrum analysis for bioacoustics classification. In: 2018 IEEE International Conference on Acoustics. Speech and Signal Processing (ICASSP), IEEE, pp 256\u2013260","DOI":"10.1109\/ICASSP.2018.8461610"},{"key":"9932_CR75","doi-asserted-by":"crossref","unstructured":"Souza LS, Gatto BB, Fukui K (2019) Classification of bioacoustic signals with tangent singular spectrum analysis. In: ICASSP 2019\u20132019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, pp 351\u2013355","DOI":"10.1109\/ICASSP.2019.8682493"},{"issue":"3","key":"9932_CR76","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1111\/2041-210X.13103","volume":"10","author":"D Stowell","year":"2019","unstructured":"Stowell D, Wood MD, Pamu\u0142a H, Stylianou Y, Glotin H (2019) Automatic acoustic detection of birds through deep learning: the first bird audio detection challenge. Methods Ecol Evol 10(3):368\u2013380","journal-title":"Methods Ecol Evol"},{"key":"9932_CR77","unstructured":"Sun R, Marye Y, Zhao HA (2013) Wavelet transform digital sound processing to identify wild bird species. In: Wavelet Analysis and Pattern Recognition (ICWAPR), 2013 International Conference on, pp 306\u2013309"},{"issue":"2","key":"9932_CR78","first-page":"107","volume":"21","author":"MW Towsey","year":"2012","unstructured":"Towsey MW, Planitz B, Nantes A, Wimmer J, Roe P (2012) A toolbox for animal call recognition. Bioacoust Int J Animal Sound Record 21(2):107\u2013125","journal-title":"Bioacoust Int J Animal Sound Record"},{"key":"9932_CR79","doi-asserted-by":"crossref","unstructured":"Xie J, Towsey M, Zhang J, Roe P (2015) Image processing and classification procedure for the analysis of australian frog vocalisations. In: Proceedings of the 2Nd International Workshop on Environmental Multimedia Retrieval, ACM, Shanghai, China, EMR \u201915, pp 15\u201320","DOI":"10.1145\/2764873.2764878"},{"key":"9932_CR80","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/j.apacoust.2016.06.029","volume":"113","author":"J Xie","year":"2016","unstructured":"Xie J, Towsey M, Zhang J, Roe P (2016a) Acoustic classification of australian frogs based on enhanced features and machine learning algorithms. Appl Acoust 113:193\u2013201","journal-title":"Appl Acoust"},{"key":"9932_CR81","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.ecoinf.2016.01.007","volume":"32","author":"J Xie","year":"2016","unstructured":"Xie J, Towsey M, Zhang J, Roe P (2016b) Adaptive frequency scaled wavelet packet decomposition for frog call classification. Ecol Inf 32:134\u2013144","journal-title":"Ecol Inf"},{"issue":"3","key":"9932_CR82","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1007\/s10462-016-9529-z","volume":"49","author":"J Xie","year":"2018","unstructured":"Xie J, Towsey M, Zhang J, Roe P (2018) Frog call classification: a survey. Artif Intell Rev 49(3):375\u2013391","journal-title":"Artif Intell Rev"},{"issue":"15","key":"9932_CR83","doi-asserted-by":"crossref","first-page":"3153","DOI":"10.3390\/app9153153","volume":"9","author":"J Xie","year":"2019","unstructured":"Xie J, Li X, Xing Z, Zhang B, Bao W, Zhang J (2019) Improved distributed minimum variance distortionless response (mvdr) beamforming method based on a local average consensus algorithm for bird audio enhancement in wireless acoustic sensor networks. Appl Sci 9(15):3153","journal-title":"Appl Sci"},{"key":"9932_CR84","doi-asserted-by":"crossref","unstructured":"Xie J, Hu K, Zhu M, Guo Y (2020) Bioacoustic signal classification in continuous recordings: syllable-segmentation vs. sliding-window. Expert Sys Appl 152:113390","DOI":"10.1016\/j.eswa.2020.113390"},{"issue":"6","key":"9932_CR85","doi-asserted-by":"crossref","first-page":"3566","DOI":"10.1121\/1.1904385","volume":"117","author":"Z Yan","year":"2005","unstructured":"Yan Z, Niezrecki C, Beusse DO (2005) Background noise cancellation for improved acoustic detection of manatee vocalizations. J Acoust Soc Am 117(6):3566\u20133573","journal-title":"J Acoust Soc Am"},{"issue":"1","key":"9932_CR86","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1121\/1.2202885","volume":"120","author":"Z Yan","year":"2006","unstructured":"Yan Z, Niezrecki C, Cattafesta LN III, Beusse DO (2006) Background noise cancellation of manatee vocalizations using an adaptive line enhancer. J Acoust Soc Am 120(1):145\u2013152","journal-title":"J Acoust Soc Am"},{"issue":"6","key":"9932_CR87","doi-asserted-by":"crossref","first-page":"1348","DOI":"10.1109\/TMI.2018.2827462","volume":"37","author":"Q Yang","year":"2018","unstructured":"Yang Q, Yan P, Zhang Y, Yu H, Shi Y, Mou X, Kalra MK, Zhang Y, Sun L, Wang G (2018) Low-dose ct image denoising using a generative adversarial network with wasserstein distance and perceptual loss. IEEE Trans Med Imag 37(6):1348\u20131357","journal-title":"IEEE Trans Med Imag"},{"issue":"6","key":"9932_CR88","doi-asserted-by":"crossref","first-page":"V333","DOI":"10.1190\/geo2018-0668.1","volume":"84","author":"S Yu","year":"2019","unstructured":"Yu S, Ma J, Wang W (2019) Deep learning for denoising. Geophysics 84(6):V333\u2013V350","journal-title":"Geophysics"},{"issue":"11","key":"9932_CR89","doi-asserted-by":"crossref","first-page":"1011","DOI":"10.1016\/j.apacoust.2010.05.005","volume":"71","author":"S Zaugg","year":"2010","unstructured":"Zaugg S, Van Der Schaar M, Hou\u00e9gnigan L, Gervaise C, Andr\u00e9 M (2010) Real-time acoustic classification of sperm whale clicks and shipping impulses from deep-sea observatories. Appl Acoust 71(11):1011\u20131019","journal-title":"Appl Acoust"},{"key":"9932_CR90","unstructured":"Zavarehei E (2020a) Berouti spectral subtraction (https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/7675-boll-spectral-subtraction). MATLAB Central File Exchange Retrieved July 23, 2020"},{"key":"9932_CR91","unstructured":"Zavarehei E (2020b) Boll spectral subtraction (https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/7675-boll-spectral-subtraction). MATLAB Central File Exchange Retrieved July 23, 2020"},{"key":"9932_CR92","unstructured":"Zavarehei E (2020c) Mmse stsa (https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/10143-mmse-stsa). MATLAB Central File Exchange Retrieved July 23, 2020"},{"key":"9932_CR93","unstructured":"Zavarehei E (2020d) Wiener filter (https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/7673-wiener-filter). MATLAB Central File Exchange Retrieved July 23, 2020"},{"key":"9932_CR94","doi-asserted-by":"crossref","unstructured":"Zeppelzauer M, St\u00f6ger AS, Breiteneder C (2013) Acoustic detection of elephant presence in noisy environments. In: Proceedings of the 2nd ACM international workshop on Multimedia analysis for ecological data, ACM, pp 3\u20138","DOI":"10.1145\/2509896.2509900"},{"issue":"7","key":"9932_CR95","doi-asserted-by":"crossref","first-page":"3142","DOI":"10.1109\/TIP.2017.2662206","volume":"26","author":"K Zhang","year":"2017","unstructured":"Zhang K, Zuo W, Chen Y, Meng D, Zhang L (2017) Beyond a gaussian denoiser: residual learning of deep cnn for image denoising. IEEE Trans Image Process 26(7):3142\u20133155","journal-title":"IEEE Trans Image Process"}],"container-title":["Artificial Intelligence Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-020-09932-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10462-020-09932-4\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10462-020-09932-4.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,27]],"date-time":"2022-11-27T10:51:16Z","timestamp":1669546276000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10462-020-09932-4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,9]]},"references-count":95,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,6]]}},"alternative-id":["9932"],"URL":"https:\/\/doi.org\/10.1007\/s10462-020-09932-4","relation":{},"ISSN":["0269-2821","1573-7462"],"issn-type":[{"value":"0269-2821","type":"print"},{"value":"1573-7462","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,9]]},"assertion":[{"value":"9 November 2020","order":1,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}