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# Overview

NOTE:

IDOL Speech Server offers two sets of speaker identification tasks, based on different technologies. This section uses examples of the iVector-based tasks, but the original set of tasks are still available. The two sets of tasks have identical parameters and options unless otherwise specified. The previous tasks are maintained mainly for backwards compatibility, but in some cases might work better than new iVector tasks. The original tasks have same name as the iVector-based tasks, but without the `Iv` prefix.

The speaker identification operation identifies sections of audio that contain speech from known speakers. IDOL Speech Server lets you build a set of speaker templates to be identified based on audio samples that represent each speaker. This speaker set can be considered as either an open-set, or a closed-set:

- An open-set allows for the possibility of speakers in the audio that are unknown. Sections of speech that do not match any of the known speakers are identified as being from an unknown speaker. To achieve this, a score threshold is estimated for each speaker. A hit is considered genuine only if the score is over the threshold estimated for the specific speaker template. Having trained the speaker templates, the thresholds are calculated based on typical true and false hit scores for each template generated from a further set of audio samples.
- A closed-set assumes that all speakers in the audio being processed are from the closed speaker set. There are no score thresholds applied in this case.

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