{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T20:23:50Z","timestamp":1761164630443,"version":"build-2065373602"},"reference-count":9,"publisher":"Wiley","issue":"5","license":[{"start":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T00:00:00Z","timestamp":1756252800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Internet Technology Letters"],"published-print":{"date-parts":[[2025,9]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>The growing demand for real\u2010time multilingual speech interaction systems poses significant challenges in terms of latency, scalability, and contextual accuracy. Conventional cloud\u2010based solutions suffer from high delays, while edge devices lack computational resources for complex models. Static CDN configurations further exacerbate regional resource underutilization, and existing systems achieve relatively lower intent accuracy in multilingual scenarios. To address these limitations, we propose a three\u2010tier framework integrating predictive CDN and a lightweight tiny machine learning\u2010based audio recognition on which the multi\u2010attention is introduced for context\u2010aware English interaction scenarios. In particular, the LSTM model is leveraged to implement the on\u2010device fine\u2010tuning and context\u2010aware so as to achieve well interactions. The experimental results demonstrate that TinyLSTM achieves superior performance with an error rate of 14.2% and an intent accuracy of 89.7%, while maintaining the lowest latency at 23\u2009ms, making it highly effective for real\u2010time applications on edge devices. Additionally, incorporating quantization, knowledge graphs, and emotion feedback progressively improves model effectiveness and increases engagement scores to 4.9, highlighting the importance of these components in enhancing both technical accuracy and user interaction quality.<\/jats:p>","DOI":"10.1002\/itl2.70105","type":"journal-article","created":{"date-parts":[[2025,8,27]],"date-time":"2025-08-27T15:50:18Z","timestamp":1756309818000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Content Delivery Network Driven Audio Recognition for Enhancing English Interaction Scenarios"],"prefix":"10.1002","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-9457-0035","authenticated-orcid":false,"given":"Liyuan","family":"Teng","sequence":"first","affiliation":[{"name":"Guilin University of Technology  Guilin Guangxi China"}]}],"member":"311","published-online":{"date-parts":[[2025,8,27]]},"reference":[{"key":"e_1_2_7_2_1","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2022.3180592"},{"key":"e_1_2_7_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/TAFFC.2023.3258900"},{"key":"e_1_2_7_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2024.3492921"},{"key":"e_1_2_7_5_1","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3440050"},{"key":"e_1_2_7_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3187434"},{"key":"e_1_2_7_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3234362"},{"key":"e_1_2_7_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2024.3352388"},{"key":"e_1_2_7_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3275106"},{"key":"e_1_2_7_10_1","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2023.3299858"}],"container-title":["Internet Technology Letters"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/itl2.70105","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,21]],"date-time":"2025-10-21T18:25:06Z","timestamp":1761071106000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/itl2.70105"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,27]]},"references-count":9,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["10.1002\/itl2.70105"],"URL":"https:\/\/doi.org\/10.1002\/itl2.70105","archive":["Portico"],"relation":{},"ISSN":["2476-1508","2476-1508"],"issn-type":[{"type":"print","value":"2476-1508"},{"type":"electronic","value":"2476-1508"}],"subject":[],"published":{"date-parts":[[2025,8,27]]},"assertion":[{"value":"2025-04-20","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-26","order":2,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-08-27","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}],"article-number":"e70105"}}