9 accepted papers
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 encoder needs to capture all information required to detect the type of sound events, as well as the direction and distance of…
Detecting occurrences of keywords with keyword spotting (KWS) systems requires thresholding continuous detection scores. Selecting appropriate thresholds is a non-trivial task, typically relying on optimizing performance on a validation dataset. However, such greedy threshold selection often leads t…
Emitted sounds may drastically change when using different microphones, when properties of the sound sources change, or when recording in different acoustic environments. Ideally, anomalous sound detection (ASD) systems should be able to generalize well to unseen target domains by only providing a f…
Large-scale audio tagging datasets like AudioSet usually suffer from severe class imbalance comprising many audio examples for common sound classes but only few examples of rare sound classes. The latter, however, may yet be equally or even more important to recognize. Therefore, it is common practi…
Anomalous sound detection (ASD) systems are usually compared by using threshold-independent performance measures such as AUCROC. However, for practical applications a decision threshold is needed to decide whether a given test sample is normal or anomalous. Estimating such a threshold is highly non-…
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 learn embeddings that are robust to noise and are ignoring non-target sound events but requires manually annotated meta inf…
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 keywords or their spoken instances, choosing the right window size is a problem: A window should be long enough to contain…
Emitted machine sounds can change drastically due to a change in settings of machines or varying noise conditions resulting in false alarms when monitoring machine conditions with a trained anomalous sound detection (ASD) system. In this work, a conceptually simple state-of-the-art ASD system based…
This paper proposes a novel approach for robustly detecting multiply repeating audio events in monitoring recordings. We consider the practically important case that the sequence of inter onset intervals between subsequent events is not constant but differs by some jitter. In such cases classical ap…