We present a method to compare songs based solely on their audio content. Our technique forms a signature for each song based on K-means clustering of spectral features. The signatures can then be compared using the Earth Mover’s Distance [14] which allows comparison of histograms with disparate bins. Preliminary objective and subjective results on a database of over 8000 songs are encouraging....

How much did a network change since yesterday? How different is the wiring between Bob’s brain (a lefthanded male) and Alice’s brain (a right-handed female)? Graph similarity with known node correspondence, i.e. the detection of changes in the connectivity of graphs, arises in numerous settings. In this work, we formally state the axioms and desired properties of the graph similarity functions,...

A significant source of errors in Automatic Speech Recognition (ASR) systems is due to pronunciation variations which occur in spontaneous and conversational speech. Usually ASR systems use a finite lexicon that provides one or more pronunciations for each word. In this paper, we focus on learning a similarity function between two pronunciations. The pronunciation can be the canonical and the s...

An agent is asked to assess a real-valued variable y based on certain characteristics x = (x1, ..., xm), and on a database consisting of n observations of (x1, ..., xm, y). A possible approach to combine past observations of x and y with the current values of x to generate an assessment of y is similarity-weighted averaging. It suggests that the predicted value of y, ys n+1, be the weighted ave...

We propose a novel weakly supervised discriminative algorithm for learning context specific registration metrics as a linear combination of conventional similarity measures. Conventional metrics have been extensively used over the past two decades and therefore both their strengths and limitations are known. The challenge is to find the optimal relative weighting (or parameters) of different me...