Knowledge-Rich Model Transformations for SpeakerKnowledge-Rich Model Transformations for Speaker Normalization in Speech Recognition

• In this work we extend the test utterance adaptationtechnique used in vocal tract length normalizationto a larger number of speaker characteristicfeatures. We perform partially jointestimation of four features: the VTLN warpingfactor, the corner position of the piece-wise linearwarping function, spectral tilt in voicedsegments, and model variance scaling. In experimentson the Swedish PF-Star children database,joint estimation of warping factor andvariance scaling lowers the recognition errorrate compared to warping factor alone.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Computer Sciences (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Språkteknologi (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Language Technology (hsv//eng)

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