English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We provide the technical report for Ego4D audio-only diarization challenge inECCV 2022. Speaker diarization takes the audio streams as input and outputs thehomogeneous segments according to the speaker's identity. It aims to solve theproblem of "Who spoke when." In this paper, we explore a Detection-based methodto tackle the audio-only speaker diarization task. Our method first extractsaudio features by audio backbone and then feeds the feature to adetection-generate network to get the speaker proposals. Finally, afterpostprocessing, we can get the diarization results. The validation datasetvalidates this method, and our method achieves 53.85 DER on the test dataset.These results rank 3rd on the leaderboard of Ego4D audio-only diarizationchallenge 2022.

Exploring Detection-based Method For Speaker Diarization @ Ego4D Audio-only Diarization Challenge 2022