{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,24]],"date-time":"2025-04-24T05:51:23Z","timestamp":1745473883195,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031534676"},{"type":"electronic","value":"9783031534683"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-53468-3_31","type":"book-chapter","created":{"date-parts":[[2024,2,19]],"date-time":"2024-02-19T13:03:57Z","timestamp":1708347837000},"page":"363-373","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improving Low-Latency Mono-Channel Speech Enhancement by\u00a0Compensation Windows in\u00a0STFT Analysis"],"prefix":"10.1007","author":[{"given":"Minh N.","family":"Bui","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dung N.","family":"Tran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kazuhito","family":"Koishida","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Trac D.","family":"Tran","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peter","family":"Chin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,2,20]]},"reference":[{"issue":"3","key":"31_CR1","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1109\/TASSP.1977.1162950","volume":"25","author":"J Allen","year":"1977","unstructured":"Allen, J.: Short term spectral analysis, synthesis, and modification by discrete Fourier transform. IEEE Trans. Acoust. Speech Signal Process. 25(3), 235\u2013238 (1977). https:\/\/doi.org\/10.1109\/TASSP.1977.1162950","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"31_CR2","doi-asserted-by":"publisher","unstructured":"Braun, S., Gamper, H., Reddy, C.K.A., Tashev, I.: Towards efficient models for real-time deep noise suppression (2021). https:\/\/doi.org\/10.48550\/ARXIV.2101.09249, https:\/\/arxiv.org\/abs\/2101.09249","DOI":"10.48550\/ARXIV.2101.09249"},{"key":"31_CR3","unstructured":"Dubey, H., et al.: Deep speech enhancement challenge at ICASSP 2023. In: ICASSP (2023)"},{"key":"31_CR4","doi-asserted-by":"crossref","unstructured":"Dubey, H., et al.: ICASSP 2022 deep noise suppression challenge. In: ICASSP (2022)","DOI":"10.1109\/ICASSP43922.2022.9747230"},{"key":"31_CR5","doi-asserted-by":"crossref","unstructured":"Graetzer, S., et al.: Clarity-2021 challenges: machine learning challenges for advancing hearing aid processing. In: Interspeech (2021)","DOI":"10.21437\/Interspeech.2021-1574"},{"key":"31_CR6","doi-asserted-by":"crossref","unstructured":"Li, C.Y., Vu, N.T.: Improving speech recognition on noisy speech via speech enhancement with multi-discriminators CycleGAN. In: 2021 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU), pp. 830\u2013836 (2021). https:\/\/api.semanticscholar.org\/CorpusID:245123920","DOI":"10.1109\/ASRU51503.2021.9688310"},{"key":"31_CR7","doi-asserted-by":"publisher","unstructured":"Li, Q., Gao, F., Guan, H., Ma, K.: Real-time monaural speech enhancement with short-time discrete cosine transform (2021). https:\/\/doi.org\/10.48550\/ARXIV.2102.04629, https:\/\/arxiv.org\/abs\/2102.04629","DOI":"10.48550\/ARXIV.2102.04629"},{"key":"31_CR8","doi-asserted-by":"publisher","unstructured":"Pandey, A., Liu, C., Wang, Y., Saraf, Y.: Dual application of speech enhancement for automatic speech recognition. In: IEEE Spoken Language Technology Workshop, SLT 2021, Shenzhen, China, 19-22 January 2021, pp. 223\u2013228. IEEE (2021). https:\/\/doi.org\/10.1109\/SLT48900.2021.9383624, https:\/\/doi.org\/10.1109\/SLT48900.2021.9383624","DOI":"10.1109\/SLT48900.2021.9383624"},{"key":"31_CR9","unstructured":"Rix, A.W., Beerends, J.G., Hollier, M., Hekstra, A.P.: 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), vol. 2, pp. 749\u2013752 (2001). https:\/\/api.semanticscholar.org\/CorpusID:5325454"},{"key":"31_CR10","doi-asserted-by":"crossref","unstructured":"Schr\u00f6ter, H., Escalante, A.N., Rosenkranz, T., Maier, A.K.: DeepFilternet: a low complexity speech enhancement framework for full-band audio based on deep filtering. In: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7407\u20137411 (2021). https:\/\/api.semanticscholar.org\/CorpusID:238634774","DOI":"10.1109\/ICASSP43922.2022.9747055"},{"key":"31_CR11","doi-asserted-by":"publisher","unstructured":"Taal, C., Hendriks, R., Heusdens, R., Jensen, J.: A short-time objective intelligibility measure for time-frequency weighted noisy speech, pp. 4214 \u2013 4217 (2010). https:\/\/doi.org\/10.1109\/ICASSP.2010.5495701","DOI":"10.1109\/ICASSP.2010.5495701"},{"key":"31_CR12","doi-asserted-by":"crossref","unstructured":"Taherian, H., Eskimez, S.E., Yoshioka, T., Wang, H., Chen, Z., Huang, X.: One model to enhance them all: array geometry agnostic multi-channel personalized speech enhancement. In: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 271\u2013275 (2021). https:\/\/api.semanticscholar.org\/CorpusID:239049883","DOI":"10.1109\/ICASSP43922.2022.9747395"},{"key":"31_CR13","unstructured":"Valentini-Botinhao, C.: Noisy speech database for training speech enhancement algorithms and TTS models (2017)"},{"key":"31_CR14","doi-asserted-by":"publisher","first-page":"666","DOI":"10.1016\/j.procs.2016.06.032","volume":"89","author":"S Vihari","year":"2016","unstructured":"Vihari, S., Murthy, A., Soni, P., Naik, D.: Comparison of speech enhancement algorithms. Procedia Comput. Sci. 89, 666\u2013676 (2016). https:\/\/doi.org\/10.1016\/j.procs.2016.06.032","journal-title":"Procedia Comput. Sci."},{"key":"31_CR15","doi-asserted-by":"crossref","unstructured":"Wang, Z.Q., Wichern, G., Watanabe, S., Roux, J.L.: STFT-domain neural speech enhancement with very low algorithmic latency. IEEE\/ACM Trans. Audio Speech Lang. Process. 31, 397\u2013410 (2022). https:\/\/api.semanticscholar.org\/CorpusID:248300088","DOI":"10.1109\/TASLP.2022.3224285"},{"key":"31_CR16","doi-asserted-by":"publisher","unstructured":"Westhausen, N.L., Meyer, B.T.: Acoustic Echo Cancellation with the Dual-Signal Transformation LSTM Network. In: ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 7138\u20137142 (2021). https:\/\/doi.org\/10.1109\/ICASSP39728.2021.9413510","DOI":"10.1109\/ICASSP39728.2021.9413510"},{"key":"31_CR17","unstructured":"Wisdom, S., Hershey, J.R., Wilson, K.W., Thorpe, J., Chinen, M., Patton, B., Saurous, R.A.: Differentiable consistency constraints for improved deep speech enhancement. CoRR abs\/1811.08521 (2018). http:\/\/arxiv.org\/abs\/1811.08521"},{"key":"31_CR18","doi-asserted-by":"publisher","unstructured":"Wood, S.U.N., Rouat, J.: Unsupervised low latency speech enhancement with RT-GCC-NMF. IEEE Journal of Selected Topics in Signal Processing 13(2), 332\u2013346 (2019). https:\/\/doi.org\/10.1109\/jstsp.2019.2909193","DOI":"10.1109\/jstsp.2019.2909193"},{"key":"31_CR19","doi-asserted-by":"publisher","unstructured":"Zhang, G., Yu, L., Wang, C., Wei, J.: Multi-scale temporal frequency convolutional network with axial attention for speech enhancement. In: ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 9122\u20139126 (2022). https:\/\/doi.org\/10.1109\/ICASSP43922.2022.9746610","DOI":"10.1109\/ICASSP43922.2022.9746610"},{"key":"31_CR20","doi-asserted-by":"publisher","unstructured":"Zhang, Z., Zhang, L., Zhuang, X., Qian, Y., Li, H., Wang, M.: FB-MSTCN: a full-band single-channel speech enhancement method based on multi-scale temporal convolutional network (2022). https:\/\/doi.org\/10.48550\/ARXIV.2203.07684, https:\/\/arxiv.org\/abs\/2203.07684","DOI":"10.48550\/ARXIV.2203.07684"},{"key":"31_CR21","doi-asserted-by":"publisher","unstructured":"Zhao, S., Ma, B., Watcharasupat, K.N., Gan, W.S.: FRCRN: boosting feature representation using frequency recurrence for monaural speech enhancement (2022). https:\/\/doi.org\/10.48550\/ARXIV.2206.07293, https:\/\/arxiv.org\/abs\/2206.07293","DOI":"10.48550\/ARXIV.2206.07293"}],"container-title":["Studies in Computational Intelligence","Complex Networks &amp; Their Applications XII"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-53468-3_31","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,17]],"date-time":"2024-06-17T13:12:55Z","timestamp":1718629975000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-53468-3_31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031534676","9783031534683"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-53468-3_31","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"20 February 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"COMPLEX NETWORKS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Complex Networks and Their Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Menton","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"France","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":"28 November 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 November 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iwcna2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.complexnetworks.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}