Bogdan Vlasenko

发表

On the Influence of Phonetic Content Variation for Acoustic Emotion Recognition

Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll, 2008, PIT.

Enhancing Speech-Based Depression Detection Through Gender Dependent Vowel-Level Formant Features

Björn W. Schuller, Nicholas Cummins, Hesam Sagha, 2017, AIME.

Location of an emotionally neutral region in valence-arousal space: Two-class vs. three-class cross corpora emotion recognition evaluations

Andreas Wendemuth, Bogdan Vlasenko, A. Wendemuth, 2014, 2014 IEEE International Conference on Multimedia and Expo (ICME).

Combining frame and turn-level information for robust recognition of emotions within speech

Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll, 2007, INTERSPEECH.

Language Modeling of Nonverbal Vocalizations in Spontaneous Speech

Andreas Stolcke, Andreas Wendemuth, Bogdan Vlasenko, 2012, TSD.

Determining the Smallest Emotional Unit for Level of Arousal Classification

Andreas Wendemuth, Bogdan Vlasenko, A. Wendemuth, 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.

Exploring dataset similarities using PCA-based feature selection

Ingo Siegert, Andreas Wendemuth, Ronald Böck, 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).

Vowels Formants Analysis Allows Straightforward Detection of High Arousal Acted and Spontaneous Emotions

David Philippou-Hübner, Andreas Wendemuth, Bogdan Vlasenko, 2011, INTERSPEECH.

Combining speech recognition and acoustic word emotion models for robust text-independent emotion recognition

Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll, 2008, 2008 IEEE International Conference on Multimedia and Expo.

Vowels formants analysis allows straightforward detection of high arousal emotions

Ingo Siegert, David Philippou-Hübner, Andreas Wendemuth, 2011, 2011 IEEE International Conference on Multimedia and Expo.

Heading toward to the natural way of human-machine interaction: the nimitek project

Andreas Wendemuth, Bogdan Vlasenko, 2009, 2009 IEEE International Conference on Multimedia and Expo.

Overlapping speech, utterance duration and affective content in HHI and HCI - An comparison

Ingo Siegert, Andreas Wendemuth, Bogdan Vlasenko, 2015, 2015 6th IEEE International Conference on Cognitive Infocommunications (CogInfoCom).

Emotion Recognition from Speech

Günther Palm, Friedhelm Schwenker, Ingo Siegert, 2017, Companion Technology.

Annotators' agreement and spontaneous emotion classification performance

Andreas Wendemuth, Bogdan Vlasenko, A. Wendemuth, 2015, INTERSPEECH.

Implementing Gender-Dependent Vowel-Level Analysis for Boosting Speech-Based Depression Recognition

Björn W. Schuller, Nicholas Cummins, Hesam Sagha, 2017, INTERSPEECH.

Implementing Fusion Techniques for the Classification of Paralinguistic Information

Mathew Magimai-Doss, Bogdan Vlasenko, Jilt Sebastian, 2018, INTERSPEECH.

Modeling phonetic pattern variability in favor of the creation of robust emotion classifiers for real-life applications

Andreas Wendemuth, Ronald Böck, Bogdan Vlasenko, 2014, Comput. Speech Lang..

Emotion recognition within spoken dialog systems

Bogdan Vlasenko, 2011 .

Appropriate emotional labelling of non-acted speech using basic emotions, geneva emotion wheel and self assessment manikins

Ingo Siegert, David Philippou-Hübner, Andreas Wendemuth, 2011, 2011 IEEE International Conference on Multimedia and Expo.

The Performance of the Speaking Rate Parameter in Emotion Recognition from Speech

David Philippou-Hübner, Andreas Wendemuth, Ronald Böck, 2012, 2012 IEEE International Conference on Multimedia and Expo.

Affective Computing and Intelligent Interaction

Michael, Mitsuru Ishizuka, Björn Schuller, 2011, Lecture Notes in Computer Science.

The Performance of the Speaking Rate Parameter in Emotion Recognition from Speech

David Philippou-Hübner, Andreas Wendemuth, Ronald Böck, 2012, 2012 IEEE International Conference on Multimedia and Expo Workshops.

Acoustic emotion recognition: A benchmark comparison of performances

Björn W. Schuller, Andreas Wendemuth, Florian Eyben, 2009, 2009 IEEE Workshop on Automatic Speech Recognition & Understanding.

Tendencies regarding the effect of emotional intensity in inter corpus phoneme-level speech emotion modelling

Björn W. Schuller, Andreas Wendemuth, Bogdan Vlasenko, 2016, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP).

Frame vs. Turn-Level: Emotion Recognition from Speech Considering Static and Dynamic Processing

Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll, 2007, ACII.

Learning Voice Source Related Information for Depression Detection

Mathew Magimai-Doss, S. Pavankumar Dubagunta, Bogdan Vlasenko, 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Processing affected speech within human machine interaction

Andreas Wendemuth, Bogdan Vlasenko, A. Wendemuth, 2009, INTERSPEECH.

Comparing one and two-stage acoustic modeling in the recognition of emotion in speech

Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll, 2007, 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU).

TUNING HIDDEN MARKOV MODEL FOR SPEECH EMOTION RECOGNITION

Andreas Wendemuth, Bogdan Vlasenko, A. Wendemuth, 2007 .

Cross-corpus acoustic emotion recognition: Variances and strategies (Extended abstract)

Björn W. Schuller, Andreas Wendemuth, Florian Eyben, 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).

Balancing spoken content adaptation and unit length in the recognition of emotion and interest

Björn W. Schuller, Andreas Wendemuth, Gerhard Rigoll, 2008, INTERSPEECH.

Analysis of significant dialog events in realistic human–computer interaction

Ingo Siegert, Andreas Wendemuth, Dietmar F. Rösner, 2013, Journal on Multimodal User Interfaces.

Determining optimal features for emotion recognition from speech by applying an evolutionary algorithm

David Philippou-Hübner, Andreas Wendemuth, Bogdan Vlasenko, 2010, INTERSPEECH.

Parameter Optimization Issues for Cross-corpora Emotion Classification

David Philippou-Hübner, Andreas Wendemuth, Bogdan Vlasenko, 2013, 2013 Humaine Association Conference on Affective Computing and Intelligent Interaction.

Fusion of Acoustic and Linguistic Information using Supervised Autoencoder for Improved Emotion Recognition

Mathew Magimai-Doss, Bogdan Vlasenko, RaviShankar Prasad, 2021, MuSe @ ACM Multimedia.

Towards Robust Spontaneous Speech Recognition with Emotional Speech Adapted Acoustic Models

Andreas Wendemuth, Bogdan Vlasenko, Dmytro Prylipko, 2012 .