Umut AvciGamze AkkurtDevrim ÜnayUnay, DevrimAvci, UmutAkkurt, GamzeA.A. Salah , A.A. Salah , A. Karpov , R. Potapova2025-10-0620199789819698936, 9789819698042, 9789819698110, 9789819698905, 9789819512324, 9783032026019, 9783032008909, 9783031915802, 9789819698141, 97830319841369783030260606978303026061316113349, 030297431611-33490302-974310.1007/978-3-030-26061-3_62-s2.0-85071450258https://www.scopus.com/inward/record.uri?eid=2-s2.0-85071450258&doi=10.1007%2F978-3-030-26061-3_6&partnerID=40&md5=aa078a2a62f3ee44f3d2290dd8ffab35https://gcris.yasar.edu.tr/handle/123456789/9471https://doi.org/10.1007/978-3-030-26061-3_6We address the problem of recognizing emotions from speech using features derived from emotional patterns. Because much work in the field focuses on using low-level acoustic features we explicitly study whether high-level features are useful for classifying emotions. For this purpose we convert a continuous speech signal to a discretized signal and extract discriminative patterns that are capable of distinguishing distinct emotions from each other. Extracted patterns are then used to create a feature set to be fed into a classifier. Experimental results show that patterns alone are good predictors of emotions. When used to build a classifier pattern features achieve accuracy gains up to 25% compared to state-of-the-art acoustic features. © 2019 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessEmotion Recognition, Feature Extraction, Pattern Mining, Speech Processing, Classification (of Information), Data Mining, Extraction, Feature Extraction, Signal Processing, Speech Processing, Acoustic Features, Continuous Speech, Emotion Recognition, Emotion Recognition From Speech, Emotional Patterns, High-level Features, Pattern Mining, Recognizing Emotions, Speech RecognitionClassification (of information), Data mining, Extraction, Feature extraction, Signal processing, Speech processing, Acoustic features, Continuous speech, Emotion recognition, Emotion recognition from speech, Emotional patterns, High-level features, Pattern mining, Recognizing emotions, Speech recognitionSpeech ProcessingPattern MiningEmotion RecognitionFeature ExtractionConference Object