Glossary Library

Technical GlossarySpeech, Voice and Audio AI

Diarization Error Rate

A core evaluation metric that summarizes segmentation, identity, and overlap errors in speaker diarization systems.

Diarization Error Rate is the core metric used to evaluate speaker diarization performance. It captures different types of error, including wrong speaker assignment, missed speech, and false alarm speech. This means it reflects not only how many speakers were found, but how well the structure of the conversation was actually resolved. It is an essential metric for meeting intelligence and enterprise audio analytics.

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A measure, especially common in language models, that summarizes how surprised a probability model is by the data.

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Train / Validation / Test Split

A core data splitting approach used to separate model learning, tuning, and final evaluation in an honest way.

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K-Fold Cross Validation

A method that repeatedly evaluates a model across different data folds to provide a more reliable estimate of performance.