{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,10]],"date-time":"2026-05-10T05:08:49Z","timestamp":1778389729875,"version":"3.51.4"},"reference-count":42,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T00:00:00Z","timestamp":1777248000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Key Scientific and Technological Project of Henan Province","award":["252102211045"],"award-info":[{"award-number":["252102211045"]}]},{"name":"he Key Scientific and Technological Project of Henan Province","award":["252102210133"],"award-info":[{"award-number":["252102210133"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Animals"],"abstract":"<jats:p>Continuous monitoring of pig behavior is essential for timely health management and welfare assessment in commercial production systems. Although vision-based methods have been widely studied, their practical application in commercial barns is often limited by variable lighting, frequent occlusion, and high stocking density. Acoustic sensing offers a non-contact alternative that is independent of lighting conditions; however, reliable behavior classification from pig vocalizations remains challenging in commercial environments because of background noise and temporal variability in sound patterns. In this study, an attention-guided acoustic framework, termed ATF-Conformer, was developed for pig vocalization classification under farm conditions. A five-class vocalization dataset was collected from finishing Landrace pigs and multiparous sows on a commercial farm, including cough, scream, estrus, feeding, and normal behavior sounds. The proposed framework combined spectrogram denoising with interactive attention to enhance behavior-related acoustic information, while a time-frequency-decoupled Conformer encoder was introduced to improve feature representation under noisy conditions. Final classification was performed using mask-based temporal pooling with an additive angular margin Softmax objective. In five-fold grouped cross-validation, ATF-Conformer achieved an accuracy of 97.34% \u00b1 0.42 and outperformed several existing acoustic models across multiple evaluation metrics. A similar accuracy of 97.38% was obtained on an independent test set, indicating stable performance across datasets. These results suggest that the proposed method can support continuous, non-invasive pig vocalization-based behavior monitoring and may assist farm owners or workers in pen-level screening of frequent cough or abnormal vocal events, thereby supporting targeted on-site inspection in precision livestock farming.<\/jats:p>","DOI":"10.3390\/ani16091337","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T19:24:51Z","timestamp":1777317891000},"page":"1337","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Conformer-Based Time\u2013Frequency Decoupling Network for Pig Vocalization Behavior Classification"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-8159-1054","authenticated-orcid":false,"given":"Jianping","family":"Wang","sequence":"first","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuqing","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siao","family":"Geng","sequence":"additional","affiliation":[{"name":"School of Foreign Studies, Henan Agricultural University, Zhengzhou 450002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Feng","family":"Wei","sequence":"additional","affiliation":[{"name":"School of Computing, Xinxiang Vocational and Technical College, Xinxiang 453006, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-8886-8811","authenticated-orcid":false,"given":"Haoyu","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuzhen","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingying","family":"Lv","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shugang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qian","family":"Li","sequence":"additional","affiliation":[{"name":"School of Computer Science and Technology, Henan Institute of Science and Technology, Xinxiang 453003, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,4,27]]},"reference":[{"key":"ref_1","first-page":"4907","article-title":"Domestic pig sound classification based on TransformerCNN","volume":"53","author":"Liao","year":"2023","journal-title":"Appl. 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