Modern streaming services are increasingly labeling videos based on their visual or audio
content. This typically augments the use of technologies such as AI and ML by allowing to …

This technical report presents a language-based audio retrieval system that we submitted to
Detection and Classification of Acoustic Scenes and Events (DCASE) Challenge 2022 Task …

The task of speech and music detection aims at the automatic annotation of potentially
overlapping speech and music segments in audio recordings. This metadata extraction …

Language-based audio retrieval aims to retrieve audio recordings based on a queried
caption, formulated as a free-form sentence written in natural language. To perform this task …

Realistic recordings of soundscapes often have multiple sound events co-occurring, such as
car horns, engine and human voices. Sound event retrieval is a type of contentbased search …

Existing audio search engines use one of two approaches: matching text-text or audio-audio
pairs. In the former, text queries are matched to semantically similar words in an index of …

Language-based audio retrieval is a task, where natural language textual captions are used
as queries to retrieve audio signals from a dataset. It has been first introduced into DCASE …

Audio event classification is an urgent Content based Information Retrieval (CBIR) unsolved
problem with numerous applications that it can benefit. This paper is explaining Pindrop's …

Audio-text retrieval based on natural language descriptions is a challenging task. It involves
learning cross-modality alignments between long sequences under inadequate data …

The development of audio event recognition systems require labeled training data, which
are generally hard to obtain. One promising source of recordings of audio events is the large …