Methods and apparatus to determine tags for media using multiple media features

A method for tagging unknown media, the method comprising:

• extracting audio features from an audio portion of the unknown media;
• extracting image features from image portions of the unknown media;
• weighting, by executing an instruction with a processor, the audio features with respect to the image features and/or the image features with respect to the audio features, the weighting based at least partially on respective recognition technologies used to extract the features, wherein when weighting the features, a highest weight is given to features extracted by a logo recognition engine, a next highest weight is given to features extracted by an optical character recognition (OCR) engine, a next highest weight is given to features extracted by a speech recognition engine and a lowest weight is given to features extracted by a graphic recognition engine;
• searching, by executing an instruction with the processor, a database of pre-tagged media using the weighted features to generate a list of suggested tags for the unknown media;
• and
• assigning, by executing an instruction with the processor, tags from the list of suggested tags to the unknown media.

An apparatus to tag unknown media, the apparatus comprising:

• a media separator to separate an audio portion from the unknown media and image portions from the unknown media;
• an audio extractor to extract audio features from the audio portion of the unknown media;
• an image extractor to extract image features from the image portions of the unknown media;
• a feature weighter to weight the audio features and the image features based at least partially on respective recognition technologies used to extract the features, the feature weighter to assign a first weight to a first feature extracted by at least one of a logo recognition engine or an optical character recognition (OCR) engine, and to assign a second weight different from the first weight to a second feature extracted by a speech recognition engine;
• one or more database search engines to search a database of pre-tagged media using a combination of the weighted audio features and the weighted image features to generate a list of suggested tags for the unknown media, wherein when a first feature included in the combination of the weighted audio features and the weighted image features is assigned to a first category of a plurality of categories, the search in the database is limited to pre-tagged media having category values matching the first category of the first feature;
• and
• a tag assigner to assign tags from the list of suggested tags to the unknown media.

An apparatus to tag unknown media, the apparatus comprising:

• a media separator to separate an audio portion from the unknown media and image portions from the unknown media;
• an audio extractor to extract audio features from the audio portion of the unknown media;
• an image extractor to extract image features from the image portions of the unknown media;
• a feature weighter to weight the audio features with respect to the image features, and/or to weight the image features with respect to the audio features, based at least partially on respective recognition technologies used to extract the features, wherein the feature weighter is to assign a highest weight to features extracted by a logo recognition engine, a next highest weight to features extracted by an optical character recognition (OCR) engine, a next highest weight to features extracted by a speech recognition engine and a lowest weight to features extracted by a graphic recognition engine;
• one or more database search engines to search a database of pre-tagged media using the weighted features to generate a list of suggested tags for the unknown media;
• a tag assigner to assign tags from the list of suggested tags to the unknown media.

A tangible computer readable medium comprising computer readable instructions which, when executed, cause a processor to at least:

• extract audio features from an audio portion of the unknown media;
• extract image features from image portions of the unknown media;
• weight the audio features and the image features based at least partially on respective recognition technologies used to extract the features, wherein to weight the features, the instructions cause the processor to assign a first weight to a first feature extracted by at least one of a logo recognition engine or an optical character recognition (OCR) engine, and the instructions cause the processor to assign a second weight different from the first weight is given to a second feature extracted by a speech recognition engine;
• search a database of pre-tagged media using a combination of the weighted audio features and the weighted image features to generate a list of suggested tags for the unknown media, wherein when a first feature included in the combination of the weighted audio features and the weighted image features is assigned to a first category of a plurality of categories, the search in the database is limited to pre-tagged media having category values matching the first category of the first feature;
• and
• assign tags from the list of suggested tags to the unknown media.

A tangible computer readable medium comprising computer readable instructions which, when executed, cause a processor to at least:

• extract audio features from an audio portion of the unknown media;
• extract image features from image portions of the unknown media;
• weight the audio features with respect to the image features, and/or weight the image features with respect to the audio features, based at least partially on respective recognition technologies used to extract the features, wherein to weight the features, the instructions cause the processor to assign a highest weight to features extracted by a logo recognition engine, a next highest weight to features extracted by an optical character recognition (OCR) engine, a next highest weight to features extracted by a speech recognition engine and a lowest weight to features extracted by a graphic recognition engine;
• search a database of pre-tagged media using the weighted features to generate a list of suggested tags for the unknown media;
• assign tags from the list of suggested tags to the unknown media.