15. A computer system for matching audio sequences, the system comprising: a computer processor; and a non-transitory computer-readable storage medium storing instructions that when executed by the computer processor perform actions comprising: deriving a first probability density function P M outputting a probability that an initial correspondence score for a pair of chroma vectors of an audio sequence indicates a semantic correspondence between the chroma vectors; deriving a second probability density function P R outputting a probability that the initial correspondence score for a pair of chroma vectors of an audio sequence indicates that the chroma vectors have a random correspondence, the deriving of P R comprising; randomly selecting a set of pairs of audio sequences; deriving initial correspondence scores for the set of pairs of audio sequences; and fitting the initial correspondence scores to a probability distribution; deriving, using P M and P R , a match function indicating whether a given pair of chroma vectors of an audio sequence correspond semantically; obtaining a first audio sequence; comparing, using the match function, the first audio sequence with a plurality of known audio sequences; and based on the comparing, identifying a best-matching audio sequence for the first audio sequence from the known audio sequences.
17. The computer system of claim 15 , wherein deriving the match function comprises: identifying a set S M of pairs of audio sequences from audio sequences that have been determined to have a semantic correspondence; identifying a plurality of pairs of chroma vectors from S M , a first chroma vector of the pairs from a first audio sequence of a pair from S M , and a second chroma vector of the pairs from a second audio sequence of the pair from S M ; and iteratively refining the match function by: updating the match function based on the functions P M and P R ; computing scores for the identified plurality of pairs of chroma vectors using the match function; based on the scores, identifying best matching pairs of subsequences of chroma vectors; and updating the function P M by mapping initial correspondence scores, for pairs of chroma vectors in the best matching pairs of subsequences, to a probability distribution function.