Search Results for author: Sven Magg

Found 22 papers, 8 papers with code

Causal State Distillation for Explainable Reinforcement Learning

no code implementations30 Dec 2023 Wenhao Lu, Xufeng Zhao, Thilo Fryen, Jae Hee Lee, Mengdi Li, Sven Magg, Stefan Wermter

This lack of transparency in RL models has been a long-standing problem, making it difficult for users to grasp the reasons behind an agent's behaviour.

reinforcement-learning Reinforcement Learning (RL)

A Closer Look at Reward Decomposition for High-Level Robotic Explanations

no code implementations25 Apr 2023 Wenhao Lu, Xufeng Zhao, Sven Magg, Martin Gromniak, Mengdi Li, Stefan Wermter

Explaining the behaviour of intelligent agents learned by reinforcement learning (RL) to humans is challenging yet crucial due to their incomprehensible proprioceptive states, variational intermediate goals, and resultant unpredictability.

Reinforcement Learning (RL) Vocal Bursts Intensity Prediction

A Sub-Layered Hierarchical Pyramidal Neural Architecture for Facial Expression Recognition

no code implementations23 Mar 2021 Henrique Siqueira, Pablo Barros, Sven Magg, Cornelius Weber, Stefan Wermter

In domains where computational resources and labeled data are limited, such as in robotics, deep networks with millions of weights might not be the optimal solution.

Facial Expression Recognition Facial Expression Recognition (FER)

An Ensemble with Shared Representations Based on Convolutional Networks for Continually Learning Facial Expressions

no code implementations5 Mar 2021 Henrique Siqueira, Pablo Barros, Sven Magg, Stefan Wermter

Social robots able to continually learn facial expressions could progressively improve their emotion recognition capability towards people interacting with them.

Emotion Recognition

Disambiguating Affective Stimulus Associations for Robot Perception and Dialogue

no code implementations5 Mar 2021 Henrique Siqueira, Alexander Sutherland, Pablo Barros, Mattias Kerzel, Sven Magg, Stefan Wermter

In this paper, we utilize the NICO robot's appearance and capabilities to give the NICO the ability to model a coherent affective association between a perceived auditory stimulus and a temporally asynchronous emotion expression.

Efficient Facial Feature Learning with Wide Ensemble-based Convolutional Neural Networks

1 code implementation17 Jan 2020 Henrique Siqueira, Sven Magg, Stefan Wermter

Experiments on large-scale datasets suggest that ESRs reduce the remaining residual generalization error on the AffectNet and FER+ datasets, reach human-level performance, and outperform state-of-the-art methods on facial expression recognition in the wild using emotion and affect concepts.

Ranked #9 on Facial Expression Recognition (FER) on FER+ (using extra training data)

Facial Expression Recognition Facial Expression Recognition (FER)

Hierarchical Control for Bipedal Locomotion using Central Pattern Generators and Neural Networks

1 code implementation2 Sep 2019 Sayantan Auddy, Sven Magg, Stefan Wermter

Artificial central pattern generators (CPGs) can produce synchronized joint movements and have been used in the past for bipedal locomotion.

Evaluating Defensive Distillation For Defending Text Processing Neural Networks Against Adversarial Examples

1 code implementation21 Aug 2019 Marcus Soll, Tobias Hinz, Sven Magg, Stefan Wermter

Adversarial examples are artificially modified input samples which lead to misclassifications, while not being detectable by humans.

Adversarial Text General Classification +3

Improving interactive reinforcement learning: What makes a good teacher?

no code implementations15 Apr 2019 Francisco Cruz, Sven Magg, Yukie Nagai, Stefan Wermter

Interactive reinforcement learning has become an important apprenticeship approach to speed up convergence in classic reinforcement learning problems.

reinforcement-learning Reinforcement Learning (RL)

KT-Speech-Crawler: Automatic Dataset Construction for Speech Recognition from YouTube Videos

1 code implementation EMNLP 2018 Egor Lakomkin, Sven Magg, Cornelius Weber, Stefan Wermter

In this paper, we describe KT-Speech-Crawler: an approach for automatic dataset construction for speech recognition by crawling YouTube videos.

speech-recognition Speech Recognition

Incorporating End-to-End Speech Recognition Models for Sentiment Analysis

no code implementations28 Feb 2019 Egor Lakomkin, Mohammad Ali Zamani, Cornelius Weber, Sven Magg, Stefan Wermter

We argue that using ground-truth transcriptions during training and evaluation phases leads to a significant discrepancy in performance compared to real-world conditions, as the spoken text has to be recognized on the fly and can contain speech recognition mistakes.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +4

Assessing the Contribution of Semantic Congruency to Multisensory Integration and Conflict Resolution

no code implementations15 Oct 2018 Di Fu, Pablo Barros, German I. Parisi, Haiyan Wu, Sven Magg, Xun Liu, Stefan Wermter

The efficient integration of multisensory observations is a key property of the brain that yields the robust interaction with the environment.

Curriculum goal masking for continuous deep reinforcement learning

no code implementations17 Sep 2018 Manfred Eppe, Sven Magg, Stefan Wermter

Deep reinforcement learning has recently gained a focus on problems where policy or value functions are independent of goals.

reinforcement-learning Reinforcement Learning (RL)

Speeding up the Hyperparameter Optimization of Deep Convolutional Neural Networks

no code implementations19 Jul 2018 Tobias Hinz, Nicolás Navarro-Guerrero, Sven Magg, Stefan Wermter

This is independent of the underlying optimization procedure, making the approach promising for many existing hyperparameter optimization algorithms.

Hyperparameter Optimization SMAC+

Discourse-Wizard: Discovering Deep Discourse Structure in your Conversation with RNNs

1 code implementation29 Jun 2018 Chandrakant Bothe, Sven Magg, Cornelius Weber, Stefan Wermter

Spoken language understanding is one of the key factors in a dialogue system, and a context in a conversation plays an important role to understand the current utterance.

Spoken Language Understanding

On the Robustness of Speech Emotion Recognition for Human-Robot Interaction with Deep Neural Networks

no code implementations6 Apr 2018 Egor Lakomkin, Mohammad Ali Zamani, Cornelius Weber, Sven Magg, Stefan Wermter

Speech emotion recognition (SER) is an important aspect of effective human-robot collaboration and received a lot of attention from the research community.

Data Augmentation Speech Emotion Recognition

Reusing Neural Speech Representations for Auditory Emotion Recognition

no code implementations IJCNLP 2017 Egor Lakomkin, Cornelius Weber, Sven Magg, Stefan Wermter

Acoustic emotion recognition aims to categorize the affective state of the speaker and is still a difficult task for machine learning models.

Emotion Recognition General Classification +1

Cannot find the paper you are looking for? You can Submit a new open access paper.