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SotA/Speech/Speaker Diarization

Speaker Diarization

23 benchmarks328 papers

Speaker Diarization is the task of segmenting and co-indexing audio recordings by speaker. The way the task is commonly defined, the goal is not to identify known speakers, but to co-index segments that are attributed to the same speaker; in other words, diarization implies finding speaker boundaries and grouping segments that belong to the same speaker, and, as a by-product, determining the number of distinct speakers. In combination with speech recognition, diarization enables speaker-attributed speech-to-text transcription.

<span class="description-source">Source: Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm </span>

Benchmarks

Speaker Diarization on CALLHOME

DER(%)DER(ig olp)FAMICF

Speaker Diarization on NIST-SRE 2000

DER(%)

Speaker Diarization on AMI Lapel

DER(%)

Speaker Diarization on AMI MixHeadset

DER(%)

Speaker Diarization on CH109

DER(%)

Speaker Diarization on DIHARD

DER(%)FAMiss

Speaker Diarization on ETAPE

DER(%)FAMiss

Speaker Diarization on AMI

DER(%)FAMiss

Speaker Diarization on CALLHOME-109

DER(%)

Speaker Diarization on AliMeeting

DER(%)

Speaker Diarization on DIHARD II

DER(%)DER - no overlap

Speaker Diarization on Hub5'00 CallHome

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