Current state-of-the-art audio analysis systems rely on pre-trained embedding models, often
used off-the-shelf as (frozen) feature extractors. Choosing the best one for a set of tasks is …

This work presents a text-to-audio-retrieval system based on pre-trained text and
spectrogram transformers. Our method projects recordings and textual descriptions into a …

Solving tasks such as speaker recognition, music classification, or semantic audio event
tagging with deep learning models typically requires computationally demanding networks …

This technical report describes CP-JKU's submission to the naturallanguage-based audio
retrieval task of the 2023 DCASE Challenge (Task 6b). Our proposed system uses …

Common knowledge distillation methods require the teacher model and the student model
to be trained on the same task. However, the usage of embeddings as teachers has also …

Abstract Machine auditory perception is a critical component in the development of artificial
intelligence systems capable of comprehending their surroundings. Perceiving and …