Imagined speech recognition is an alternative means to aid individuals with motor disabilities, illnesses and speech disorders, such as the mute and those under the state of coma, to communicate properly through silent communication. Imagined speech or unspoken speech is speech that is only uttered within the mind without the use of any muscle movement. In this study, the proponents compared the effects of linear and nonlinear features in an imagined speech classification model. This model was designed to classify the five vowels namely /a/ /e/ /i/ /o/ and /u/. Electroencephalogram (EEG) signals were measured in each study volunteers while they were imagining the different vowels. Linear and nonlinear features were extracted from the processed EEG signals, and these features were used as inputs to an Artificial Neural Network (ANN) classifier.

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https://doi.org/10.1109/BioSMART58455.2023.10162084
Dihingia LBannulmath PChowdhury APrasanna SDeepak KSheikh T(2023)Preliminary Analysis of Lambani Vowels and Vowel Classification Using Acoustic FeaturesSpeech and Computer10.1007/978-3-031-48312-7_16(195-207)Online publication date: 22-Nov-2023
https://doi.org/10.1007/978-3-031-48312-7_16
Villamizar SSarmiento LLópez OCaballero JBacca J(2020)EEG Vowel Silent Speech Signal Discrimination Based on APIT-EMD and SVDAETA 2019 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application10.1007/978-3-030-53021-1_8(74-83)Online publication date: 11-Aug-2020
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ICBBB '17: Proceedings of the 7th International Conference on Bioscience, Biochemistry and Bioinformatics

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DOI:10.1145/3051166

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Cruz JMarquez JMendoza AReyes JTango VPrado S(2023)EEG-based Characterization and Classification of Severity for the Diagnosis of Post-Traumatic Stress Disorder (PTSD)2023 5th International Conference on Bio-engineering for Smart Technologies (BioSMART)10.1109/BioSMART58455.2023.10162084(1-7)Online publication date: 7-Jun-2023
https://doi.org/10.1109/BioSMART58455.2023.10162084
Dihingia LBannulmath PChowdhury APrasanna SDeepak KSheikh T(2023)Preliminary Analysis of Lambani Vowels and Vowel Classification Using Acoustic FeaturesSpeech and Computer10.1007/978-3-031-48312-7_16(195-207)Online publication date: 22-Nov-2023
https://doi.org/10.1007/978-3-031-48312-7_16
Villamizar SSarmiento LLópez OCaballero JBacca J(2020)EEG Vowel Silent Speech Signal Discrimination Based on APIT-EMD and SVDAETA 2019 - Recent Advances in Electrical Engineering and Related Sciences: Theory and Application10.1007/978-3-030-53021-1_8(74-83)Online publication date: 11-Aug-2020
https://doi.org/10.1007/978-3-030-53021-1_8
Cooney CFolli RCoyle D(2018)Mel Frequency Cepstral Coefficients Enhance Imagined Speech Decoding Accuracy from EEG2018 29th Irish Signals and Systems Conference (ISSC)10.1109/ISSC.2018.8585291(1-7)Online publication date: Jun-2018
https://doi.org/10.1109/ISSC.2018.8585291
Marcelo CPasquin ZPichay ATan MSimon MPrado SBuenaventura CNicasio M(2017)Characterization and comparison of brain wave signals during deception2017IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM)10.1109/HNICEM.2017.8269508(1-6)Online publication date: Dec-2017
https://doi.org/10.1109/HNICEM.2017.8269508

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