the mel scale is: a nonlinear frequency scale that models human pitch perception

mel-frequency cepstral coefficients (MFCCs) capture: speech features on a perceptual scale

MFCCs capture speech features on a perceptual scale by mimicking human auditory perception

Fisher information

Fisher information measures information about unknown parameters

AI content watermarking

AI content watermarking embeds imperceptible signals

WordPiece tokenization does: similar to BPE but uses likelihood instead of frequency

WordPiece tokenization splits words into subwords based on token likelihood rather than frequency

BLEU vs ROUGE: BLEU measures precision of n-grams, ROUGE measures recall

BLEU measures precision of n-grams, ROUGE measures recall

to normalize features: when features have different scales and you use distance-based methods

Normalize features when they have different scales for distance-based methods