Kevin Wilkinghoff



Kevin Wilkinghoff

I am a postdoctoral researcher at Aalborg University, Denmark with the Pioneer Centre for AI, Copenhagen, Denmark and an active member of the DCASE community. From 2017 to 2024, I was a research associate at the Fraunhofer FKIE, Wachtberg, Germany, and in 2024 I was a visiting research scientist at MERL, Cambridge, MA, USA. I received my B.Sc. degree in mathematics at the University of Münster, Germany, in 2014 and my M.Sc. and Ph.D. degree in computer science at the University of Bonn, Germany, in 2017 and 2024, respectively.

My research focuses on anomaly and out-of-distribution detection for audio data, with applications such as acoustic machine condition monitoring, keyword spotting and sound event detection.

Resume: (last update: 09/2025) 
Full CV: (last update: 09/2025) 






You can also find me on Google Scholar and dblp.


Preprints

Local Density-Based Anomaly Score Normalization for Domain Generalization
K. Wilkinghoff, H. Yang, J. Ebbers, F. G. Germain, G. Wichern, J. Le Roux. Under review.
Handling Domain Shifts for Anomalous Sound Detection: A Review of DCASE-Related Work
K. Wilkinghoff, T. Fujimura, K. Imoto, J. Le Roux, Z.-H. Tan, T. Toda. arXiv:2503.10435, accepted for presentation at DCASE.
ASDKit: A Toolkit for Comprehensive Evaluation of Anomalous Sound Detection Methods
T. Fujimura, K. Wilkinghoff, K. Imoto, T. Toda. arXiv:2507.10264, accepted for presentation at DCASE.
Personalized Speech Synthesis for Zero-Shot Keyword Spotting
F. Gökgöz, A. Cornaggia-Urrigshardt, K. Wilkinghoff. Accepted for presentation at ITG Speech.

Articles in Peer-Reviewed Journals

2024

Why do Angular Margin Losses Work Well for Semi-Supervised Anomalous Sound Detection?
K. Wilkinghoff, F. Kurth. IEEE ACM Trans. Audio Speech Lang. Process.

Articles in Peer-Reviewed Conference and Workshop Proceedings

2025

Keeping the Balance: Anomaly Score Calculation for Domain Generalization
K. Wilkinghoff, H. Yang, J. Ebbers, F. G. Germain, G. Wichern, J. Le Roux. ICASSP.
No Class Left Behind: A Closer Look at Class Balancing for Audio Tagging
J. Ebbers, F. G. Germain, K. Wilkinghoff, G. Wichern, J. Le Roux. ICASSP.

2024

F1-EV Score: Measuring the Likelihood of Estimating a Good Decision Threshold for Semi-Supervised Anomaly Detection
K. Wilkinghoff, K. Imoto. ICASSP.
Self-Supervised Learning for Anomalous Sound Detection
K. Wilkinghoff. ICASSP.
TACos: Learning Temporally Structured Embeddings for Few-Shot Keyword Spotting with Dynamic Time Warping
K. Wilkinghoff, A. Cornaggia-Urrigshardt. ICASSP.
Multi-Sample Dynamic Time Warping for Few-Shot Keyword Spotting
K. Wilkinghoff, A. Cornaggia-Urrigshardt. EUSIPCO.
AdaProj: Adaptively Scaled Angular Margin Subspace Projections for Anomalous Sound Detection with Auxiliary Classification Tasks
K. Wilkinghoff. DCASE.
Analyzing the Impact of HF-Specific Signal Degradation on Automatic Speech Recognition
F. Fritz, A. Cornaggia-Urrigshardt, L. Henneke, F. Kurth, K. Wilkinghoff. ICMCIS.
Strong Label Generation for Preparing Speech Data in Military Applications Using CTC Loss
F. Gökgöz, A. Cornaggia-Urrigshardt, K. Wilkinghoff. ICMCIS.

2023

Design Choices for Learning Embeddings from Auxiliary Tasks for Domain Generalization in Anomalous Sound Detection
K. Wilkinghoff. ICASSP.
Novel Generative Classifier for Acoustic Events
P. M. Baggenstoss, K. Wilkinghoff. EUSIPCO.
On Using Pre-Trained Embeddings for Detecting Anomalous Sounds with Limited Training Data
K. Wilkinghoff, F. Fritz. EUSIPCO.
Language Recognition for SSB modulated HF Radio Signals of Short Duration
A. Cornaggia-Urrigshardt, F. Fritz, L. Henneke, F. Kurth, C. Schlich, K. Wilkinghoff. ITG Speech.

2022

Towards Human-Machine Integration for Signal Intelligence Applications
J. D. Rockbach, L.-F. Bluhm, I. Schlangen, L. Over, S. Apfeld, L. Henneke, K. Wilkinghoff. SDF.
SCALA-Speech: An Interactive System for Finding and Analyzing Speech Content in Audio Data
A. Cornaggia-Urrigshardt, N. Jarocky, F. Kurth, S. Urrigshardt, K. Wilkinghoff. GI-Jahrestagung.
Speech Recognition Lab
A. Cornaggia-Urrigshardt, F. Gökgöz, F. Kurth, H.-C. Schmitz, K. Wilkinghoff. ICMCIS.

2021

Sub-Cluster AdaCos: Learning Representations for Anomalous Sound Detection
K. Wilkinghoff. IJCNN.
Combining Multiple Distributions based on Sub-Cluster AdaCos for Anomalous Sound Detection under Domain Shifted Conditions
K. Wilkinghoff. DCASE.
Best Paper Award.
Two-Dimensional Embeddings for Low-Resource Keyword Spotting Based on Dynamic Time Warping
K. Wilkinghoff, A. Cornaggia-Urrigshardt, F. Gökgöz. ITG Speech.

2020

On Open-Set Classification with L3-Net Embeddings for Machine Listening Applications.
K. Wilkinghoff. EUSIPCO.
Using Look, Listen, and Learn Embeddings for Detecting Anomalous Sounds in Machine Condition Monitoring
K. Wilkinghoff. DCASE.
On Open-Set Speaker Identification with I-Vectors
K. Wilkinghoff. Odyssey.
Towards Robust Speech Interfaces for the ISS
H.-C. Schmitz, F. Kurth, K. Wilkinghoff, U. Müllerschkowski, C. Karrasch, V. Schmid. IUI Companion.

2019

Open-Set Acoustic Scene Classification with Deep Convolutional Autoencoders
K. Wilkinghoff, F. Kurth. DCASE.
Calm Interfaces for Integrated C2 Systems
H.-C. Schmitz, A. Cornaggia-Urrigshardt, F. Gökgöz, S. Kent, K. Wilkinghoff. ICCRTS.

2018

Robust Detection of Jittered Multiply Repeating Audio Events Using Iterated Time-Warped ACF
F. Kurth, K. Wilkinghoff. ICASSP.
General-Purpose Audio Tagging by Ensembling Convolutional Neural Networks based on Multiple Features
K. Wilkinghoff. DCASE.
Accurately Capturing Speech Feature Distributions by Extending Supervectors for Robust Speaker Recognition
K. Wilkinghoff. ITG Speech.
Robust Speaker Identification by Fusing Classification Scores with a Neural Network
K. Wilkinghoff, P. M. Baggenstoss, A. Cornaggia-Urrigshardt, F. Kurth. ITG Speech.

2017

Glottal Mixture Model (GLOMM) for Speaker Identification on Telephone Channels
P. M. Baggenstoss, K. Wilkinghoff, F. Kurth. EUSIPCO.

Invited Articles in Conference Proceedings without Peer-Review

2025

Handling Domain Shifts for Anomalous Sound Detection: A Review
K. Wilkinghoff, T. Fujimura, K. Imoto, J. Le Roux. DAS/DAGA.

2022

On Choosing Decision Thresholds for Anomalous Sound Detection in Machine Condition Monitoring
K. Wilkinghoff, A. Cornaggia-Urrigshardt. ICA.

Technical Reports for Academic Challenges

2024

FKIE-VUB System for DCASE2024 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
K. Wilkinghoff, Y. Bel-Hadj. DCASE2024 Challenge, Ranked 19/28.

2023

Fraunhofer FKIE Submission for Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
K. Wilkinghoff. DCASE2023 Challenge, Ranked 4/24.
Fraunhofer FKIE Submission for Task 5: Few-Shot Bioacoustic Event Detection
K. Wilkinghoff, A. Cornaggia-Urrigshardt. DCASE2023 Challenge, Ranked 6/8.

2022

An Outlier Exposed Anomalous Sound Detection System for Domain Generalization in Machine Condition Monitoring
K. Wilkinghoff. DCASE2022 Challenge, Ranked 10/32.

2021

Utilizing Sub-Cluster Adacos for Anomalous Sound Detection under Domain Shifted Conditions
K. Wilkinghoff. DCASE2021 Challenge, Ranked 3/27.
Judges' Award.

2020

Anomalous Sound Detection with Look, Listen, and Learn Embeddings
K. Wilkinghoff. DCASE2020 Challenge, Ranked 8/40.

2019

Open-Set Acoustic Scene Classification with Deep Convolutional Autoencoders
K. Wilkinghoff, F. Kurth. DCASE2019 Challenge, Ranked 19/39 and 3/7.

2018

Open-Set Speaker Recognition with Augmented i-Vectors
K. Wilkinghoff. MCE2018 Challenge, Ranked 8/13 and 6/13.
General-Purpose Audio Tagging by Ensembling Convolutional Neural Networks based on Multiple Features
K. Wilkinghoff. DCASE2018 Challenge, Ranked 14/39.

Theses

2024

Audio Embeddings for Semi-Supervised Anomalous Sound Detection
Doctoral Thesis. Faculty of Mathematics and Natural Sciences, University of Bonn.

2017

Neural Networks in Speaker Identification
Master's Thesis. Institute of Computer Science, University of Bonn.
Kölner VDI Förderpreis 2018.
AFCEA Bonn Studienpreis 2018.

2013

Homogenisierung nichtlinearer elliptischer Differentialgleichungen
Bachelor's Thesis. Mathematical Institute, University of Münster.