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US 12,717,842 B2Granted
Method and system for analyzing, classifying, and node-ranking content in audio tracks
AssigneeMusixmatch S.P.A.
InventorsLoreto Parisi, Marco Paglia, Alessio Albano, Paolo Magnani, Pierfrancesco Melucci, Maria Stella Tavella
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Abstract
In one embodiment, a computer-implemented method is disclosed. The method includes receiving a first content item, transcribing audio included in the first content item to obtain text associated with the audio, determining a plurality of keywords included in the text, classifying, based on the plurality of keywords, the text as one or more nodes in a data structure, and ranking, based on a plurality of factors, the one or more nodes relative to one or more other nodes associated with a second content item.
Claims19
A computer-implemented method comprising:
- receiving a first content item;
- transcribing audio included in the first content item to obtain text associated with the audio;
- determining a plurality of keywords included in the text;
- classifying, based on the plurality of keywords, the text as one or more nodes in a data structure;
- ranking, based on a plurality of factors, the one or more nodes relative to one or more other nodes associated with a second content item;
- generating, via one or machine learning models, one or more tags and associating the one or more tags with the plurality of keywords in the text, wherein at least one of the one or more tags comprises an identity of a speaker;
- and
- causing, via a processing device, a media player to play the first content item and present the one or more tags with the text, wherein the text is time-synchronized with the audio of the first content item, and wherein the one or more tags are displayed proximate to an associated, respective portion of the text in a first section of a user interface, while one or more second tags representing summaries of the text including timestamps of when the summaries are played in the first content item are concurrently displayed in a second portion of the user interface, and wherein the one or more machine learning models generate the summaries of the text.
5 more elements
A tangible, non-transitory computer-readable medium storing instructions that, when executed, cause a processing device to:
- receive a first content item;
- transcribe audio included in the first content item to obtain text associated with the audio;
- determine a plurality of keywords included in the text;
- classify, based on the plurality of keywords, the text as one or more nodes in a data structure;
- rank, based on a plurality of factors, the one or more nodes relative to one or more other nodes associated with a second content item;
- generate, via one or machine learning models, one or more tags and associating the one or more tags with the plurality of keywords in the text, wherein at least one of the one or more tags comprises an identity of a speaker;
- and
- cause, via a processing device, a media player to play the first content item and present the one or more tags with the text, wherein the text is time-synchronized with the audio of the first content item, and wherein the one or more tags are displayed proximate to an associated, respective portion of the text in a first section of a user interface, while one or more second tags representing summaries of the text including timestamps of when the summaries are played in the first content item are concurrently displayed in a second portion of the user interface, and wherein the one or more machine learning models generate the summaries of the text.
5 more elements
A system comprising:
- a memory device storing instructions;
- and
- a processing device communicatively coupled to the memory device, wherein the processing device executes the instructions to:
- receive a first content item;
- transcribe audio included in the first content item to obtain text associated with the audio;
- determine a plurality of keywords included in the text;
- classify, based on the plurality of keywords, the text as one or more nodes in a data structure;
- rank, based on a plurality of factors, the one or more nodes relative to one or more other nodes associated with a second content item;
- generate, via one or machine learning models, one or more tags and associating the one or more tags with the plurality of keywords in the text, wherein at least one of the one or more tags comprises an identity of a speaker;
- and
- cause, via a processing device, a media player to play the first content item and present the one or more tags with the text, wherein the text is time-synchronized with the audio of the first content item, and wherein the one or more tags are displayed proximate to an associated, respective portion of the text in a first section of a user interface, while one or more second tags representing summaries of the text including timestamps of when the summaries are played in the first content item are concurrently displayed in a second portion of the user interface, and wherein the one or more machine learning models generate the summaries of the text.
8 more elements
Dependencies are inferred from the claim text.