Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Mohanty, Aniruddha; Cherukuri, Ravindranath Chowdary Title A name given to the resource Whispered speech emotion recognition with gender detection using hybridopti-gendernet Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2026 Source A related resource from which the described resource is derived Multimedia Tools and Applications;Volume;85;Issue;4;Article No.;318; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s11042-026-21463-8" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s11042-026-21463-8</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105035254935?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105035254935?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Mohanty A., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India; Cherukuri R.C., Department of Computer Science and Engineering, CHRIST (Deemed to be University), Bangalore, 560074, India Description An account of the resource The Whispered Speech Emotion Recognition (SER) presents special challenges because it does not involve the vibration of vocal folds and less acoustic information, which makes it more difficult to identify the nuances of emotions and gender-related peculiarities than in normal speech. The research presents a new system, HybridOpti-GenderNet, of concurrent whispered speech emotion and gender recognition. It is a framework of six stages are data collection, pre-processing, feature extraction, feature selection, gender detection, and emotion recognition (ER). A Red Butterfly Optimization Algorithm (RBOA), which uses Butterfly Optimization Algorithm (BOA) and Red Kite Optimization Algorithm (ROA) by adjusting the weight to achieve optimal feature selection, is proposed to achieve a better balance between exploration and exploitation. Gender identification is carried out with the proposed HybridOpti-GenderNet, a new hybridization of Bi-LSTM and DCNN, and ER is accomplished with the help of the Attention-Enhanced Hybrid Belief Network (AHBN) that incorporates Deep Belief Network (DBN), Feedforward Neural Network (FNN) &amp; a tailor-made attention mechanism to detect delicate emotional signals. The innovativeness of the given work is that the gender-informed recognition is combined with a high-level optimization and a hybrid deep learning pipeline that enhances the robustness of the analysis of whispered speech significantly. The system was tested in Python and tested on the GeWEC and EMO-DB data, showing superior performance in cases of privacy preservation, noisy conditions, and real-life human-computer interaction. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2026. Subject The topic of the resource AHBN; Emotion recognition; Gender detection; HybridOpti-GenderNet; RBOA; Whispered speech Publisher An entity responsible for making the resource available Springer Relation A related resource ISSN: 13807501; CODEN: MTAPF Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online