3 accepted papers
Text embeddings are typically evaluated on a narrow set of tasks, limited in terms of languages, domains, and task types. To circumvent this limitation and to provide a more comprehensive evaluation, we introduce the Massive Multilingual Text Embedding Benchmark (MMTEB) -- a large-scale community-dr…
To address the vital problem of selecting the most useful microphones in wireless acoustic sensor networks, this paper proposes a novel, general-purpose approach that accounts for both acoustic and network aspects and remains application-agnostic for broad applicability. The inter-channel correlatio…
The performance of sound reproduction systems for spatial audio is impaired by time-variant, reverberant listening environments. To tackle this issue, the Loudspeaker-Enclosure-Microphone System (LEMS) between the loudspeakers and reference microphones in the listening environment can be identified…