Difference between revisions of "Information Extraction to Predict Judgement"
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The bigger idea is to analyze conversational speech transcripts of court-room hearings, and extract relevant information that impacts the decision of the hearings. A possible approach is to first identify the bases of making decision on a case from relevant law (e.g. objective of the crime, manner of the crime, etc.), and then do some supervised/semi-supervised learning to identify from the conversation, portions that relate to discussion regarding these bases, and to find whether that portion of the conversation tends to work in the favor of the accused or otherwise. | The bigger idea is to analyze conversational speech transcripts of court-room hearings, and extract relevant information that impacts the decision of the hearings. A possible approach is to first identify the bases of making decision on a case from relevant law (e.g. objective of the crime, manner of the crime, etc.), and then do some supervised/semi-supervised learning to identify from the conversation, portions that relate to discussion regarding these bases, and to find whether that portion of the conversation tends to work in the favor of the accused or otherwise. | ||
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| + | Team:[[User:manajs|Manaj Srivastava]][[User:mridulg|Mridul Gupta]] | ||
Revision as of 18:18, 17 September 2011
Relevant Information Extraction from Court-room Hearings To Predict Judgement
The bigger idea is to analyze conversational speech transcripts of court-room hearings, and extract relevant information that impacts the decision of the hearings. A possible approach is to first identify the bases of making decision on a case from relevant law (e.g. objective of the crime, manner of the crime, etc.), and then do some supervised/semi-supervised learning to identify from the conversation, portions that relate to discussion regarding these bases, and to find whether that portion of the conversation tends to work in the favor of the accused or otherwise.
