Automated video summarization using speech transcripts

Compact representations of video data can enable efficient video browsing. Such representations provide the user with information about tile content of the particular sequence being examined while preserving the essential message. We propose a method to automatically generate video summaries for long videos. Our video summarization approach involves mainly two tasks: first, segmenting the video into small, coherent segments and second, ranking the resulting segments. Our proposed algorithm scores segments based on word frequency analysis of speech transcripts. Then a summary is generated by selecting tile segments with the highest score to duration ratios and these are concatenating them. We have designed and performed a user study to evaluate the quality of summaries generated. Comparisons are made using our proposed algorithm and a random segment selection scheme based on statistical analysis of the user study results. Finally we discuss various issues that arise in summary evaluation with user studies.