System and methods for recognizing sound and music signals in high noise and distortion

A method for recognizing a media entity from a media sample, comprising:

• receiving a set of sample fingerprints, each sample fingerprint characterizing a particular sample landmark within said media sample;
• obtaining a set of file fingerprints, each file fingerprint characterizing a particular file landmark within a media entity to be identified;
• generating correspondences between said sample landmarks and said obtained file landmarks, wherein corresponding landmarks have equivalent fingerprints;
• and
• identifying said media entity if a plurality of said corresponding landmarks are substantially linearly related.

A method for recognizing a media sample, comprising:

• continually sampling into a sound buffer N seconds of said media sample;
• computing a set of sample fingerprints characterizing a segment of said media sample stored in said sound buffer, wherein said segment has one or more distinct landmarks occurring at reproducible locations of said media sample;
• storing said fingerprints in a rolling buffer;
• obtaining a set of matching fingerprints in a database index, each matching fingerprint characterizing at least one distinct landmark of a media file and is equivalent to at least one fingerprint in said rolling buffer;
• identifying at least one media file having a plurality of matching fingerprints;
• reporting presence of said at least one media file;
• and
• removing at least one sample fingerprint from said rolling buffer.

A program storage device accessible by a computer, tangibly embodying a program of instructions executable by said computer to perform method steps for recognizing a media entity from a media sample, said program of instructions comprising:

• code for computing a set of sample fingerprints, each sample fingerprint characterizing a particular sample landmark within said media sample;
• code for obtaining a set of file fingerprints, each file fingerprint characterizing a particular file landmark within a media entity to be identified;
• code for generating correspondences between said sample landmarks and said obtained file landmarks, wherein corresponding landmarks have equivalent fingerprints;
• and
• code for identifying said media entity if a plurality of said corresponding landmarks are substantially linearly related.

A system for recognizing a media entity from a media sample, comprising:

• a landmarking and fingerprinting object for computing a set of particular sample landmarks within said media sample and a set of sample fingerprints, each sample fingerprint characterizing one of said particular sample landmarks;
• a database index containing file landmarks and corresponding file fingerprints for at least one media entity to be identified;
• and
• an analysis object for:
• locating a set of matching fingerprints in said database index, wherein said matching fingerprints are equivalent to said sample fingerprints;
• generating correspondences between said sample landmarks and said file landmarks, wherein corresponding landmarks have equivalent fingerprints;
• and
• identifying at least one media entity for which a plurality of said corresponding landmarks are substantially linearly related.

A computer-implemented method for recognizing an audio sample, comprising:

• creating a database index of at least one audio file in a database, comprising:
• computing landmarks and fingerprints for each audio file, wherein each landmark occurs at a particular location within said audio file and is associated with a fingerprint;
• associating, for each audio file, said landmarks and fingerprints with an identifier;
• and
• storing said fingerprints, said landmarks, and said identifier in a memory.

A method for recognizing a media entity from a media sample, comprising:

• generating correspondences between landmarks of said media sample and corresponding landmarks of a media entity to be identified, wherein said landmarks of said media sample and said corresponding landmarks of said media entity have equivalent fingerprints;
• and
• identifying said media sample and said media entity if a plurality of said correspondences have a linear relationship defined by
• landmark*n=m*landmarkn+offset,
• where
• landmarkn is a sample landmark,
• landmark*n is a file landmark that corresponds to landmarkn, and
• m represents slope.

A method for recognizing a media sample, comprising

• identifying media files that have file landmarks that are substantially linearly related to sample landmarks of said media sample;
• wherein
• said file landmarks and said sample landmarks have equivalent fingerprints;
• and wherein
• said file landmarks and said sample landmarks have a linear correspondence defined by
• landmark*n=m*landmarkn+offset,
• where
• landmarkn is a sample landmark,
• landmark*n is a file landmark that corresponds to landmarkn, and
• m represents slope.

A method for comparing an audio sample and an audio entity, comprising:

• for each of at least one audio entity to be identified, computing a plurality of entity fingerprints representing said audio entity;
• wherein each entity fingerprint characterizes one or more features of said audio entity at or near an entity landmark in at least one dimensions including time;
• computing a plurality of sample fingerprints representing said audio sample, wherein said sample fingerprints are invariant to time stretching of said audio sample;
• and
• identifying a matching audio entity that has at least a threshold number of said file fingerprints that are equivalent to said sample fingerprints.

A method for comparing an audio sample and an audio entity, comprising:

• for each of at least one audio entity to be identified, computing a plurality of entity landmark/fingerprint pairs representing said audio entity, wherein each landmark occurs at a particular location within said audio entity in at least one dimension including time, and wherein each fingerprint characterizes one or more features of said audio entity at or near said particular location;
• computing a plurality of sample landmark/fingerprint pairs representing said audio sample by
• obtaining time and frequency coordinates of at least one salient point of a spectrogram of said audio sample, wherein each salient point serves as an anchor point defining a sample landmark;
• and
• generating at least one multidimensional sample landmark/fingerprint pair from said at least one salient point, wherein sample landmarks of said audio sample are taken to be time coordinates and wherein corresponding sample fingerprints are computed from at least one of the remaining coordinates;
• and
• identifying a winning audio entity that has at least a threshold number of said file fingerprints that are equivalent to said sample fingerprints.