42 citations · 125 across the 24 of their papers we have counts for
40 papers
Audio Enhancement for Computer Audition -- An Iterative Training Paradigm Using Sample Importance
Manuel Milling, Shuo Liu, Andreas Triantafyllopoulos +2
Neural network models for audio tasks, such as automatic speech recognition (ASR) and acoustic scene classification (ASC), are susceptible to noise contamination for real-life appl…
Abusive Speech Detection in Indic Languages Using Acoustic Features
Anika A. Spiesberger, Andreas Triantafyllopoulos, Iosif Tsangko +1
Abusive content in online social networks is a well-known problem that can cause serious psychological harm and incite hatred. The ability to upload audio data increases the import…
Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking Dataset
Rui Liu, Haolin Zuo, Zheng Lian +3
Emotion and Intent Joint Understanding in Multimodal Conversation (MC-EIU) aims to decode the semantic information manifested in a multimodal conversational history, while inferrin…
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…
Exploring Gender-Specific Speech Patterns in Automatic Suicide Risk Assessment
Maurice Gerczuk, Shahin Amiriparian, Justina Lutz +4
In emergency medicine, timely intervention for patients at risk of suicide is often hindered by delayed access to specialised psychiatric care. To bridge this gap, we introduce a s…
This Paper Had the Smartest Reviewers -- Flattery Detection Utilising an Audio-Textual Transformer-Based Approach
Lukas Christ, Shahin Amiriparian, Friederike Hawighorst +5
Flattery is an important aspect of human communication that facilitates social bonding, shapes perceptions, and influences behavior through strategic compliments and praise, levera…