Alignment of Metadata
Methods and apparatus, including computer program products, for alignment of metadata. A method includes receiving two or more variations of an underlying piece of content, each piece of content including metadata, using a text alignment technique to correlate the metadata of the two or more variations, and merging multiple sets of the metadata into one multi-track set from the correlation.
1 . A method comprising:
receiving two or more variations of an underlying piece of content, each variation including metadata;
using a text alignment technique to correlate the metadata of the two or more variations; and
merging multiple sets of the metadata into one multi-track set from the correlation.
2 . The method of claim 1 wherein the content includes one or more of digital text, digital audio and digital video.
3 . The method of claim 1 wherein the text alignment technique is a dynamic programming process optimizing a metric.
4 . The method of claim 3 wherein the metric is a metric that minimizes a number of word substitutions, insertions and deletions.
5 . The method of claim 3 wherein the metric is a metric that weights different words differently.
6 . The method of claim 3 wherein the metric assigns different penalties to different errors and minimizes a total weighted penalty.
7 . The method of claim 3 wherein the metric is calculated in conjunction with natural language processing.
8 . The method of claim 3 wherein the metric is calculated using a Viterbi dynamic programming process for finding the most likely sequence of hidden states.
9 . The method of claim 1 wherein receiving two or more variations of the underlying piece of content further comprises applying pattern-based normalization on the two or more variations.
10 . The method of claim 9 wherein applying pattern-based normalization comprises removing time stamps from closed-captioning.
11 . The method of claim 1 wherein the one multi-track set includes external non-aligned metadata.
12 . The method of claim 11 wherein the external non-aligned metadata is selected based on aligned metadata.
13 . The method of claim 1 wherein the content is digital audio.
14 . The method of claim 13 wherein speech-to-text is performed on the digital audio.
15 . The method of claim 1 wherein the text alignment technique comprises text aligning to one or more time alignments to align the metadata of the two or more variations.
16 . An apparatus comprising:
a local computing system linked to a network of interconnected computer systems, the local computing system comprising a processor, a memory and a storage device;
the memory comprising an operating system and a metadata alignment process, the metadata alignment process comprising:
receiving two or more variations of an underlying piece of content, each piece of content including metadata;
using a text alignment technique to correlate the metadata of the two or more variations; and
merging multiple sets of the metadata into one multi-track set from the correlation.
17 . The apparatus of claim 16 wherein the content includes one or more of digital text, digital audio and digital video.
18 . The apparatus of claim 16 wherein the text alignment technique is a dynamic programming process optimizing a metric.
19 . The apparatus of claim 18 wherein the metric is a metric that minimizes a number of word substitutions, insertions and deletions.
20 . The apparatus of claim 18 wherein the metric is a metric that weights different words differently.
21 . The apparatus of claim 18 wherein the metric is calculated in conjunction with natural language processing.
22 . The apparatus of claim 18 wherein the metric is calculated using a Viterbi dynamic programming process for finding the most likely sequence of hidden states.
23 . The apparatus of claim 16 wherein receiving two variations of the underlying piece of content further comprises applying pattern-based normalization on the two variations.
24 . The apparatus of claim 23 wherein applying pattern-based normalization comprises removing time stamps from closed-captioning.
25 . The apparatus of claim 16 wherein the one multi-track set includes external non-aligned metadata.
26 . The apparatus of claim 25 wherein the external non-aligned metadata is selected based on aligned metadata.
27 . The apparatus of claim 16 wherein the content is digital audio.
28 . The apparatus of claim 27 wherein speech-to-text is performed on the digital audio.
29 . A method comprising:
receiving variations of an underlying piece of content, each piece of content including metadata;
using a text alignment technique to correlate the metadata of a first variation to a third variation, the correlated metadata including timestamps;
using the text alignment technique to correlate the metadata of a second variation to the third variation, the correlated metadata including timestamps; and
merging the correlated metadata into one multi-track set.
30 . The method of claim 29 wherein the content includes one or more of digital text, digital audio and digital video.
31 . The method of claim 29 wherein the text alignment technique is a dynamic programming process optimizing a metric.
32 . The method of claim 29 wherein the content is digital audio.
33 . The method of claim 32 wherein speech-to-text is performed on the digital audio.