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It reduces human perceived Quality of Experience (QoE). Along this line, this article proposes a novel speech quality prediction metric that can meet human\u2019s desired QoE level. Our motivation is driven by the lack of evidence showing speech quality metrics that can distinguish different noise degradations before predicting the quality of speech. The quality of speech in noisy environments is improved by speech enhancement algorithms, and for measuring and monitoring the quality of speech, objective speech quality metrics are used. With the integration of these components, a novel no-reference context-aware QoE prediction metric (CAQoE) is proposed in this article, which initially identifies the context or noise type or degradation type of the input noisy speech signal and then predicts context-specific speech quality for that input speech signal. It will have of great importance in deciding the speech enhancement algorithms if the types of degradations causing poor speech quality are known along with the quality metric. Results demonstrate that the proposed CAQoE metric outperforms in different contexts as compared to the metric where contexts are not identified before predicting the quality of speech, even in the presence of limited size speech corpus having different contexts available from the NOIZEUS speech database.<\/jats:p>","DOI":"10.1145\/3529394","type":"journal-article","created":{"date-parts":[[2022,4,13]],"date-time":"2022-04-13T11:55:16Z","timestamp":1649850916000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["CAQoE: A Novel No-Reference Context-aware Speech Quality Prediction Metric"],"prefix":"10.1145","volume":"19","author":[{"given":"Rahul Kumar","family":"Jaiswal","sequence":"first","affiliation":[{"name":"Department of Information and Communication Technology, Faculty of Engineering and Science, University of Agder, Grimstad, Norway"}]},{"given":"Rajesh Kumar","family":"Dubey","sequence":"additional","affiliation":[{"name":"Department of Electrical Engineering, School of Engineering and Technology, Central University of Haryana, Mahendragarh, India"}]}],"member":"320","published-online":{"date-parts":[[2023,2,3]]},"reference":[{"key":"e_1_3_2_2_2","unstructured":"ITU-T Rec. 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