348 citations · 467 across the 16 of their papers we have counts for
16 papers
Speech-Based Depressive Mood Detection in the Presence of Multiple Sclerosis: A Cross-Corpus and Cross-Lingual Study
Monica Gonzalez-Machorro, Uwe Reichel, Pascal Hecker +5
Depression commonly co-occurs with neurodegenerative disorders like Multiple Sclerosis (MS), yet the potential of speech-based Artificial Intelligence for detecting depression in s…
Am I Blue or Is My Hobby Counting Teardrops? Expression Leakage in Large Language Models as a Symptom of Irrelevancy Disruption
Berkay Köprü, Mehrzad Mashal, Yigit Gurses +6
Large language models (LLMs) have advanced natural language processing (NLP) skills such as through next-token prediction and self-attention, but their ability to integrate broad c…
Using voice analysis as an early indicator of risk for depression in young adults
Klaus R. Scherer, Felix Burkhardt, Uwe D. Reichel +2
Increasingly frequent publications in the literature report voice quality differences between depressed patients and controls. Here, we examine the possibility of using voice analy…
Wav2Small: Distilling Wav2Vec2 to 72K parameters for Low-Resource Speech emotion recognition
Dionyssos Kounadis-Bastian, Oliver Schrüfer, Anna Derington +4
Speech Emotion Recognition (SER) needs high computational resources to overcome the challenge of substantial annotator disagreement. Today SER is shifting towards dimensional annot…
Are you sure? Analysing Uncertainty Quantification Approaches for Real-world Speech Emotion Recognition
Oliver Schrüfer, Manuel Milling, Felix Burkhardt +2
Uncertainty Quantification (UQ) is an important building block for the reliable use of neural networks in real-world scenarios, as it can be a useful tool in identifying faulty pre…
Testing Correctness, Fairness, and Robustness of Speech Emotion Recognition Models
Anna Derington, Hagen Wierstorf, Ali Özkil +3
Machine learning models for speech emotion recognition (SER) can be trained for different tasks and are usually evaluated based on a few available datasets per task. Tasks could in…
Going Retro: Astonishingly Simple Yet Effective Rule-based Prosody Modelling for Speech Synthesis Simulating Emotion Dimensions
Felix Burkhardt, Uwe Reichel, Florian Eyben +1
We introduce two rule-based models to modify the prosody of speech synthesis in order to modulate the emotion to be expressed. The prosody modulation is based on speech synthesis m…
Speech-based Age and Gender Prediction with Transformers
Felix Burkhardt, Johannes Wagner, Hagen Wierstorf +2
We report on the curation of several publicly available datasets for age and gender prediction. Furthermore, we present experiments to predict age and gender with models based on a…
audb -- Sharing and Versioning of Audio and Annotation Data in Python
Hagen Wierstorf, Johannes Wagner, Florian Eyben +2
Driven by the need for larger and more diverse datasets to pre-train and fine-tune increasingly complex machine learning models, the number of datasets is rapidly growing. audb is…
Probing Speech Emotion Recognition Transformers for Linguistic Knowledge
Andreas Triantafyllopoulos, Johannes Wagner, Hagen Wierstorf +5
Large, pre-trained neural networks consisting of self-attention layers (transformers) have recently achieved state-of-the-art results on several speech emotion recognition (SER) da…
Dawn of the transformer era in speech emotion recognition: closing the valence gap
Johannes Wagner, Andreas Triantafyllopoulos, Hagen Wierstorf +4
Recent advances in transformer-based architectures which are pre-trained in self-supervised manner have shown great promise in several machine learning tasks. In the audio domain,…
Multistage linguistic conditioning of convolutional layers for speech emotion recognition
Andreas Triantafyllopoulos, Uwe Reichel, Shuo Liu +3
In this contribution, we investigate the effectiveness of deep fusion of text and audio features for categorical and dimensional speech emotion recognition (SER). We propose a nove…
The voice of COVID-19: Acoustic correlates of infection
Katrin D. Bartl-Pokorny, Florian B. Pokorny, Anton Batliner +8
COVID-19 is a global health crisis that has been affecting many aspects of our daily lives throughout the past year. The symptomatology of COVID-19 is heterogeneous with a severity…
On Laughter and Speech-Laugh, Based on Observations of Child-Robot Interaction
Anton Batliner, Stefan Steidl, Florian Eyben +1
In this article, we study laughter found in child-robot interaction where it had not been prompted intentionally. Different types of laughter and speech-laugh are annotated and pro…
audEERING's approach to the One-Minute-Gradual Emotion Challenge
Andreas Triantafyllopoulos, Hesam Sagha, Florian Eyben +1
This paper describes audEERING's submissions as well as additional evaluations for the One-Minute-Gradual (OMG) emotion recognition challenge. We provide the results for audio and…
A Broadcast News Corpus for Evaluation and Tuning of German LVCSR Systems
Felix Weninger, Björn Schuller, Florian Eyben +2
Transcription of broadcast news is an interesting and challenging application for large-vocabulary continuous speech recognition (LVCSR). We present in detail the structure of a ma…