…PSTN profile on the side of the PSTN voiceprint, and the YouTube profile on the side of the YouTube voiceprint). Results Enhancement Modes There are currently 3 modes of result enhancement: Mean Normalization False Acceptance Calibration User Calibration These modes can be used either separately, or in combinations. Possible combinations are: Mean Normalization + False Acceptance Calibration Mean Normalization +…
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…you’ll need a calibration set with at least 1000 recordings from unique speakers, which contain at least 60 seconds of net speech. Mean normalization – compensates for the differences in channel, language etc. This method makes it possible to enhance the SID results. The normalization data set must contain at least 100 speakers. User calibration – enables to change the…
…[G#157] Added endpoint for updating existing Audio Source Profile [G#160] SID4 calibration technology renamed: SID4CALIBSET -> SID4CALIB [G#161] Mean normalization support in Audio Source Profiles [G#169] Added cache for Audio Source Profiles, see server.audio_source_profiles_cache_size property [G#170] Added False Acceptance Calibration cache, see server.bsapi_comparator_fa_cache_size [G#149] Fixed: phxclient prints help if running without parameters [G#150] Fixed: UTF-8 symbols are not escaped in…
…FAQ Phonexia Browser, FAQ Speech Platform Permalink Q: What do LLR, LR and score mean? A: These abbreviations mean the following: LR – likelihood ratio, result from statistical test for two models comparison. It returns a number which expresses how many times more likely the data are under one model than the other. LR meets numbers in interval <0;+inf). LLR…
…range (0,91840). A: It means that this opus file is created improperly and declares internally (in header) much more audio than available in real file. Please check your audio source/originator for proper functionality. Or use ffmpeg / sox utility as preprocessor of the audio and do audio normalization by self-conversion from opus to opus before recordings are processed through SPE….