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dc.contributor.authorZambrano Vizuete, Oscar Marcelo-
dc.date.accessioned2026-08-14T16:55:54Z-
dc.date.available2026-08-14T16:55:54Z-
dc.date.issued2024-06-29-
dc.identifier.isbn9783031634345-
dc.identifier.urihttps://repositorio.ister.edu.ec//handle/68000/818-
dc.descriptionThe project aims to create an emotion recognition system based on voice using deep learning techniques. The system is based on supervised learning with artificial neural networks, enabling it to accurately predict emotions. The system’s potential usage in detecting depression pathologies in the psychological area gives rise to its devel opment. The system is designed using the KDD (Knowledge Discovery in Database) methodology and utilizes an existing database containing audio with various emotions. These audios are subjected to Multilevel Wavelet transform, decomposing the original signal into sub-signals with specific characteristics for each audio to form a training data set that is subsequently normalized, followed by the generation of the LSTM neural network architecture. Performance tests are eventually conducted on patients with depressive pathology, involving the application of the “Beck test”, which indicates the severity of depression experienced by the patient. As a result, the individual reads a text that is recorded, followed by the process of feature extraction and emotion recognition performed with the pre-trained neural network. The outcome indicates that 50% of the patients exhibit severe depression, while the remainder displays milder symptoms, which is supported by the emotions detected by the system alongside the administered test.es_ES
dc.format.extent32 p.es_ES
dc.language.isoenes_ES
dc.publisherSangolquí, Ecuador. Instituto Tecnológico Universitario Rumiñahuies_ES
dc.rightsopenAccesses_ES
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectEMOTION RECOGNITIONes_ES
dc.subjectWAVELET TRANSFORMes_ES
dc.subjectDEEP LEARNINGes_ES
dc.subjectEMOTION RECOGNITIONes_ES
dc.subject.otherEmotion recognitiones_ES
dc.subject.otherVoice-based systemses_ES
dc.subject.otherArtificial intelligencees_ES
dc.subject.otherSpeech processinges_ES
dc.titleInnovation and Research – Smart Technologies & Systems Proceedings of the CI3 2023, Volume 1es_ES
dc.title.alternativeA Voice-Based Emotion Recognition System Using Deep Learning Techniqueses_ES
dc.typeLibroes_ES
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