call_home_american_english_speech Benchmark (Speaker Diarization)

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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.

Source: Improving Diarization Robustness using Diversification, Randomization and the DOVER Algorithm

The archive carries no text for this table; the description above is the archive's text for the task Speaker Diarization. archive 2025-07-28

Results archive 2025-07-28

No rows in the archive for this table at snapshot 2025-07-28. It declares 1 metric (Test DER) but no result was ever recorded against it. That says nothing about whether results exist elsewhere.

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