18 citations · 18 across the 11 of their papers we have counts for
13 papers
How Much Does Machine Identity Matter in Anomalous Sound Detection at Test Time?
Kevin Wilkinghoff, Keisuke Imoto, Zheng-Hua Tan
Anomalous sound detection (ASD) benchmarks typically assume that the identity of the monitored machine is known at test time and that recordings are evaluated in a machine-wise man…
DSpAST: Disentangled Representations for Spatial Audio Reasoning with Large Language Models
Kevin Wilkinghoff, Zheng-Hua Tan
Reasoning about spatial audio with large language models requires a spatial audio encoder as an acoustic front-end to obtain audio embeddings for further processing. Such an encode…
Local Density-Based Anomaly Score Normalization for Domain Generalization
Kevin Wilkinghoff, Haici Yang, Janek Ebbers +3
State-of-the-art anomalous sound detection (ASD) systems in domain-shifted conditions rely on projecting audio signals into an embedding space and using distance-based outlier dete…
Quantization-Based Score Calibration for Few-Shot Keyword Spotting with Dynamic Time Warping in Noisy Environments
Kevin Wilkinghoff, Alessia Cornaggia-Urrigshardt, Zheng-Hua Tan
Detecting occurrences of keywords with keyword spotting (KWS) systems requires thresholding continuous detection scores. Selecting appropriate thresholds is a non-trivial task, typ…
ASDKit: A Toolkit for Comprehensive Evaluation of Anomalous Sound Detection Methods
Takuya Fujimura, Kevin Wilkinghoff, Keisuke Imoto +1
In this paper, we introduce ASDKit, a toolkit for anomalous sound detection (ASD) task. Our aim is to facilitate ASD research by providing an open-source framework that collects an…
Handling Domain Shifts for Anomalous Sound Detection: A Review of DCASE-Related Work
Kevin Wilkinghoff, Takuya Fujimura, Keisuke Imoto +3
When detecting anomalous sounds in complex environments, one of the main difficulties is that trained models must be sensitive to subtle differences in monitored target signals, wh…
Multi-Sample Dynamic Time Warping for Few-Shot Keyword Spotting
Kevin Wilkinghoff, Alessia Cornaggia-Urrigshardt
In multi-sample keyword spotting, each keyword class is represented by multiple spoken instances, called samples. A naïve approach to detect keywords in a target sequence consists…
AdaProj: Adaptively Scaled Angular Margin Subspace Projections for Anomalous Sound Detection with Auxiliary Classification Tasks
Kevin Wilkinghoff
The state-of-the-art approach for semi-supervised anomalous sound detection is to first learn an embedding space by using auxiliary classification tasks based on meta information o…
Projected Belief Networks With Discriminative Alignment for Acoustic Event Classification: Rivaling State of the Art CNNs
Paul M. Baggenstoss, Kevin Wilkinghoff, Felix Govaers +1
The projected belief network (PBN) is a generative stochastic network with tractable likelihood function based on a feed-forward neural network (FFNN). The generative function oper…
Self-Supervised Learning for Anomalous Sound Detection
Kevin Wilkinghoff
State-of-the-art anomalous sound detection (ASD) systems are often trained by using an auxiliary classification task to learn an embedding space. Doing so enables the system to lea…
F1-EV Score: Measuring the Likelihood of Estimating a Good Decision Threshold for Semi-Supervised Anomaly Detection
Kevin Wilkinghoff, Keisuke Imoto
Anomalous sound detection (ASD) systems are usually compared by using threshold-independent performance measures such as AUC-ROC. However, for practical applications a decision thr…
Why do Angular Margin Losses work well for Semi-Supervised Anomalous Sound Detection?
Kevin Wilkinghoff, Frank Kurth
State-of-the-art anomalous sound detection systems often utilize angular margin losses to learn suitable representations of acoustic data using an auxiliary task, which usually is…
TACos: Learning Temporally Structured Embeddings for Few-Shot Keyword Spotting with Dynamic Time Warping
Kevin Wilkinghoff, Alessia Cornaggia-Urrigshardt
To segment a signal into blocks to be analyzed, few-shot keyword spotting (KWS) systems often utilize a sliding window of fixed size. Because of the varying lengths of different ke…