activity
20162022
most citedDawn of the transformer era in speech emotion recognition: closing the valence gap

348 citations · 647 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2022★ 25 cited

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…

eess.AS2022★ 348 cited

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,…

cs.CL2020

A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events

Martin Schiersch, Veselina Mironova, Maximilian Schmitt +3

Monitoring mobility- and industry-relevant events is important in areas such as personal travel planning and supply chain management, but extracting events pertaining to specific c…

cs.HC2019★ 1 cited

AVEC 2019 Workshop and Challenge: State-of-Mind, Detecting Depression with AI, and Cross-Cultural Affect Recognition

Fabien Ringeval, Björn Schuller, Michel Valstar +14

The Audio/Visual Emotion Challenge and Workshop (AVEC 2019) "State-of-Mind, Detecting Depression with AI, and Cross-cultural Affect Recognition" is the ninth competition event aime…

cs.HC2019★ 244 cited

SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild

Jean Kossaifi, Robert Walecki, Yannis Panagakis +10

Natural human-computer interaction and audio-visual human behaviour sensing systems, which would achieve robust performance in-the-wild are more needed than ever as digital devices…

stat.ML2018★ 1 cited

Weakly Supervised One-Shot Detection with Attention Similarity Networks

Gil Keren, Maximilian Schmitt, Thomas Kehrenberg +1

Neural network models that are not conditioned on class identities were shown to facilitate knowledge transfer between classes and to be well-suited for one-shot learning tasks. Fo…

cs.CV2016★ 28 cited

openXBOW - Introducing the Passau Open-Source Crossmodal Bag-of-Words Toolkit

Maximilian Schmitt, Björn W. Schuller

We introduce openXBOW, an open-source toolkit for the generation of bag-of-words (BoW) representations from multimodal input. In the BoW principle, word histograms were first used…