Follow
Kevin Wilkinghoff
Title
Cited by
Cited by
Year
Sub-Cluster AdaCos: Learning Representations for Anomalous Sound Detection
K Wilkinghoff
International Joint Conference on Neural Networks (IJCNN), 2021
362021
Design Choices for Learning Embeddings from Auxiliary Tasks for Domain Generalization in Anomalous Sound Detection
K Wilkinghoff
International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2023
212023
Utilizing sub-cluster AdaCos for anomalous sound detection under domain shifted conditions
K Wilkinghoff
Tech. Rep., DCASE2021 Challenge, 2021
202021
Open-Set Acoustic Scene Classification with Deep Convolutional Autoencoders
K Wilkinghoff, F Kurth
Detection and Classification of Acoustic Scenes and Events Workshop (DCASE …, 2019
182019
Fraunhofer FKIE Submission for Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring
K Wilkinghoff
Tech. Rep., DCASE2023 Challenge, 2023
122023
On Open-Set Speaker Identification with I-Vectors
K Wilkinghoff
Odyssey - The Speaker and Language Recognition Workshop (Odyssey), 408-414, 2020
122020
On Open-Set Classification with L3-Net Embeddings for Machine Listening Applications
K Wilkinghoff
28th European Signal Processing Conference (EUSIPCO), 800-804, 2020
122020
Combining Multiple Distributions based on Sub-Cluster AdaCos for Anomalous Sound Detection under Domain Shifted Conditions
K Wilkinghoff
Detection and Classification of Acoustic Scenes and Events Workshop (DCASE …, 2021
102021
Self-Supervised Learning for Anomalous Sound Detection
K Wilkinghoff
International Conference on Acoustics, Speech and Signal Processing (ICASSP …, 2024
92024
Towards Robust Speech Interfaces for the ISS
HC Schmitz, F Kurth, K Wilkinghoff, U Müllerschkowski, C Karrasch, ...
25th International Conference on Intelligent User Interfaces Companion, 110-111, 2020
92020
An Outlier Exposed Anomalous Sound Detection System for Domain Generalization in Machine Condition Monitoring
K Wilkinghoff
Tech. Rep., DCASE2022 Challenge, 2022
62022
Why Do Angular Margin Losses Work Well for Semi-Supervised Anomalous Sound Detection?
K Wilkinghoff, F Kurth
IEEE/ACM Transactions on Audio, Speech, and Language Processing 32, 608-622, 2024
52024
Two-Dimensional Embeddings for Low-Resource Keyword Spotting Based on Dynamic Time Warping
K Wilkinghoff, A Cornaggia-Urrigshardt, F Gökgöz
14th ITG Conference on Speech Communication, 9-13, 2021
52021
Anomalous Sound Detection with Look, Listen, and Learn Embeddings
K Wilkinghoff
Tech. report in DCASE2020 Challenge Task, 2020
52020
Using Look, Listen, and Learn Embeddings for Detecting Anomalous Sounds in Machine Condition Monitoring
K Wilkinghoff
Detection and Classification of Acoustic Scenes and Events Workshop (DCASE …, 2020
52020
Calm Interfaces for Integrated C2 Systems
HC Schmitz, A Cornaggia-Urrigshardt, F Gökgöz, S Kent, K Wilkinghoff
International Command and Control Research and Technology Symposium (ICCRTS), 2019
52019
On using pre-trained embeddings for detecting anomalous sounds with limited training data
K Wilkinghoff, F Fritz
31st European Signal Processing Conference (EUSIPCO), 186-190, 2023
42023
Speech Recognition Lab
A Cornaggia-Urrigshardt, F Gökgöz, F Kurth, HC Schmitz, K Wilkinghoff
International Conference on Military Communications and Information Systems …, 2022
42022
General-Purpose Audio Tagging by Ensembling Convolutional Neural Networks based on Multiple Features
K Wilkinghoff
Detection and Classification of Acoustic Scenes and Events Workshop (DCASE …, 2018
42018
On choosing decision thresholds for anomalous sound detection in machine condition monitoring
K Wilkinghoff, A Cornaggia-Urrigshardt
24th International Congress on Acoustics (ICA), 2022
32022
The system can't perform the operation now. Try again later.
Articles 1–20