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Lecture 11 Speaker Identification 3

Lecture 11 Speaker Identification 3 - LIN 4930 Speaker...

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LIN 4930 Speaker Identification 3: Acoustic Analysis
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Steps in speaker identification by acoustic analysis Acoustic analysis: Automatic extraction of acoustic measures that correlate with speaker identity Specific example: SAUSI system (Semi- automatic speaker identification) Step 1: Vector Analysis Step 2: Normalization Step 3: Comparisons between unknown, known, and foil voices Step 4: Summing vectors Step 5: Rotational replications (repeating procedures two more times with different speech samples)
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Step 1: Vector Analysis Four important “vectors” or sets of cues (in descending order of efficacy): Long-term spectra (LTS) Vowel Formant Tracking (VFT) Speaking fundamental frequency (SFF) Time-Energy Distribution (TED)
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Long-term spectrum (LTS) Definition: A power spectrum taken over a longer sample of speech (e.g., 20 s) that incorporates multiple phonemes Fast Fourier Transform (FFT) of 40 frequency bands spanning up 10 kHz Two voices can be compared by calculating absolute difference for each comparable frequency band
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LTS Example Talker A Talker B
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