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2020 – today
- 2024
[c34]Bogdan Vlasenko, Sargam Vyas, Mathew Magimai-Doss:
Comparing data-Driven and Handcrafted Features for Dimensional Emotion Recognition. ICASSP 2024: 11841-11845- 2023
- [c33]Tilak Purohit, Sarthak Yadav, Bogdan Vlasenko, S. Pavankumar Dubagunta, Mathew Magimai-Doss:
Towards Learning Emotion Information from Short Segments of Speech. ICASSP 2023: 1-5 - [c32]Tilak Purohit, Bogdan Vlasenko, Mathew Magimai-Doss
:
Implicit phonetic information modeling for speech emotion recognition. INTERSPEECH 2023: 1883-1887 - 2022
- [c31]Zohreh Mostaani, RaviShankar Prasad, Bogdan Vlasenko, Mathew Magimai-Doss:
Modeling of Pre-Trained Neural Network Embeddings Learned From Raw Waveform for COVID-19 Infection Detection. ICASSP 2022: 8482-8486 - [c30]Sarthak Yadav, Tilak Purohit, Zohreh Mostaani, Bogdan Vlasenko, Mathew Magimai-Doss:
Comparing Biosignal and Acoustic feature Representation for Continuous Emotion Recognition. MuSe @ ACM Multimedia 2022: 37-45 - [i1]Tilak Purohit, Imen Ben Mahmoud, Bogdan Vlasenko, Mathew Magimai-Doss:
Comparing supervised and self-supervised embedding for ExVo Multi-Task learning track. CoRR abs/2206.11968 (2022) - 2021
- [c29]Bogdan Vlasenko, RaviShankar Prasad, Mathew Magimai-Doss:
Fusion of Acoustic and Linguistic Information using Supervised Autoencoder for Improved Emotion Recognition. MuSe @ ACM Multimedia 2021: 51-59
2010 – 2019
- 2019
- [c28]S. Pavankumar Dubagunta, Bogdan Vlasenko, Mathew Magimai-Doss:
Learning Voice Source Related Information for Depression Detection. ICASSP 2019: 6525-6529 - 2018
- [c27]Bogdan Vlasenko, Jilt Sebastian, Pavan Kumar D. S., Mathew Magimai-Doss:
Implementing Fusion Techniques for the Classification of Paralinguistic Information. INTERSPEECH 2018: 526-530 - 2017
- [c26]Nicholas Cummins, Bogdan Vlasenko, Hesam Sagha, Björn W. Schuller:
Enhancing Speech-Based Depression Detection Through Gender Dependent Vowel-Level Formant Features. AIME 2017: 209-214 - [c25]Bogdan Vlasenko, Hesam Sagha, Nicholas Cummins, Björn W. Schuller:
Implementing Gender-Dependent Vowel-Level Analysis for Boosting Speech-Based Depression Recognition. INTERSPEECH 2017: 3266-3270 - [p1]Andreas Wendemuth, Bogdan Vlasenko, Ingo Siegert, Ronald Böck, Friedhelm Schwenker, Günther Palm:
Emotion Recognition from Speech. Companion Technology 2017: 409-428 - 2016
- [c24]Bogdan Vlasenko, Björn W. Schuller, Andreas Wendemuth:
Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling. MLSP 2016: 1-6 - 2015
- [c23]Ingo Siegert, Ronald Böck, Andreas Wendemuth, Bogdan Vlasenko:
Exploring dataset similarities using PCA-based feature selection. ACII 2015: 387-393 - [c22]Björn W. Schuller, Bogdan Vlasenko, Florian Eyben, Martin Wöllmer, André Stuhlsatz, Andreas Wendemuth, Gerhard Rigoll:
Cross-corpus acoustic emotion recognition: Variances and strategies (Extended abstract). ACII 2015: 470-476 - [c21]Ingo Siegert, Ronald Böck, Andreas Wendemuth, Bogdan Vlasenko, Kerstin Ohnemus:
Overlapping speech, utterance duration and affective content in HHI and HCI - An comparison. CogInfoCom 2015: 83-88 - [c20]Bogdan Vlasenko, Andreas Wendemuth:
Annotators' agreement and spontaneous emotion classification performance. INTERSPEECH 2015: 1546-1550 - 2014
- [j3]Bogdan Vlasenko, Dmytro Prylipko, Ronald Böck, Andreas Wendemuth:
Modeling phonetic pattern variability in favor of the creation of robust emotion classifiers for real-life applications. Comput. Speech Lang. 28(2): 483-500 (2014) - [j2]Dmytro Prylipko, Dietmar F. Rösner, Ingo Siegert, Stephan Günther, Rafael Friesen, Matthias Haase, Bogdan Vlasenko, Andreas Wendemuth:
Analysis of significant dialog events in realistic human-computer interaction. J. Multimodal User Interfaces 8(1): 75-86 (2014) - [c19]Bogdan Vlasenko, Andreas Wendemuth:
Location of an emotionally neutral region in valence-arousal space: Two-class vs. three-class cross corpora emotion recognition evaluations. ICME 2014: 1-6 - 2013
- [c18]Bogdan Vlasenko, David Philippou-Hübner, Andreas Wendemuth:
Parameter Optimization Issues for Cross-corpora Emotion Classification. ACII 2013: 454-459 - [c17]Bogdan Vlasenko, Andreas Wendemuth:
Determining the Smallest Emotional Unit for Level of Arousal Classification. ACII 2013: 734-739 - 2012
- [c16]David Philippou-Hübner, Bogdan Vlasenko, Ronald Böck, Andreas Wendemuth:
The Performance of the Speaking Rate Parameter in Emotion Recognition from Speech. ICME 2012: 248-253 - [c15]David Philippou-Hübner, Bogdan Vlasenko, Ronald Böck, Andreas Wendemuth:
The Performance of the Speaking Rate Parameter in Emotion Recognition from Speech. ICME Workshops 2012: 296-301 - [c14]Dmytro Prylipko, Bogdan Vlasenko, Andreas Stolcke, Andreas Wendemuth:
Language Modeling of Nonverbal Vocalizations in Spontaneous Speech. TSD 2012: 488-495 - 2011
- [b1]Bogdan Vlasenko:
Emotion recognition within spoken dialog systems. Otto von Guericke University Magdeburg, 2011 - [c13]Ingo Siegert, Ronald Böck, Bogdan Vlasenko, David Philippou-Hübner, Andreas Wendemuth:
Appropriate emotional labelling of non-acted speech using basic emotions, geneva emotion wheel and self assessment manikins. ICME 2011: 1-6 - [c12]Bogdan Vlasenko, David Philippou-Hübner, Dmytro Prylipko, Ronald Böck, Ingo Siegert, Andreas Wendemuth:
Vowels formants analysis allows straightforward detection of high arousal emotions. ICME 2011: 1-6 - [c11]Bogdan Vlasenko, Dmytro Prylipko, David Philippou-Hübner, Andreas Wendemuth:
Vowels Formants Analysis Allows Straightforward Detection of High Arousal Acted and Spontaneous Emotions. INTERSPEECH 2011: 1577-1580 - 2010
- [j1]Björn W. Schuller, Bogdan Vlasenko, Florian Eyben, Martin Wöllmer, André Stuhlsatz, Andreas Wendemuth, Gerhard Rigoll:
Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies. IEEE Trans. Affect. Comput. 1(2): 119-131 (2010) - [c10]David Philippou-Hübner, Bogdan Vlasenko, Tobias Grosser, Andreas Wendemuth:
Determining optimal features for emotion recognition from speech by applying an evolutionary algorithm. INTERSPEECH 2010: 2358-2361
2000 – 2009
- 2009
- [c9]Björn W. Schuller, Bogdan Vlasenko, Florian Eyben, Gerhard Rigoll, Andreas Wendemuth:
Acoustic emotion recognition: A benchmark comparison of performances. ASRU 2009: 552-557 - [c8]Bogdan Vlasenko, Andreas Wendemuth:
Heading toward to the natural way of human-machine interaction: the nimitek project. ICME 2009: 950-953 - [c7]Bogdan Vlasenko, Andreas Wendemuth:
Processing affected speech within human machine interaction. INTERSPEECH 2009: 2039-2042 - 2008
- [c6]Björn W. Schuller, Bogdan Vlasenko, Dejan Arsic, Gerhard Rigoll, Andreas Wendemuth:
Combining speech recognition and acoustic word emotion models for robust text-independent emotion recognition. ICME 2008: 1333-1336 - [c5]Bogdan Vlasenko, Björn W. Schuller, Kinfe Tadesse Mengistu, Gerhard Rigoll, Andreas Wendemuth:
Balancing spoken content adaptation and unit length in the recognition of emotion and interest. INTERSPEECH 2008: 805-808 - [c4]Bogdan Vlasenko, Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll:
On the Influence of Phonetic Content Variation for Acoustic Emotion Recognition. PIT 2008: 217-220 - 2007
- [c3]Bogdan Vlasenko, Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll:
Frame vs. Turn-Level: Emotion Recognition from Speech Considering Static and Dynamic Processing. ACII 2007: 139-147 - [c2]Björn W. Schuller, Bogdan Vlasenko, Ricardo Minguez, Gerhard Rigoll, Andreas Wendemuth:
Comparing one and two-stage acoustic modeling in the recognition of emotion in speech. ASRU 2007: 596-600 - [c1]Bogdan Vlasenko, Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll:
Combining frame and turn-level information for robust recognition of emotions within speech. INTERSPEECH 2007: 2249-2252
Coauthor Index
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