5. A computer-implemented method, comprising: analyzing audio, using a processor, to extract features from the audio and identify voice segments in the audio where a human voice is present by analyzing other classified audio of a same genre or including a similar voice and to identify non-voice segments in proximity to the voice segments based on the extracted features; identifying segmented text associated with the audio, the segmented text having text segments; using machine learning to use a support vector machine learning algorithm to learn to identify the voice segment based on the other classified audio; and synchronizing the text segments to the voice segments using the processor.
5. A computer-implemented method, comprising: analyzing audio, using a processor, to extract features from the audio and identify voice segments in the audio where a human voice is present by analyzing other classified audio of a same genre or including a similar voice and to identify non-voice segments in proximity to the voice segments based on the extracted features; identifying segmented text associated with the audio, the segmented text having text segments; using machine learning to use a support vector machine learning algorithm to learn to identify the voice segment based on the other classified audio; and synchronizing the text segments to the voice segments using the processor. 6. The method of claim 5 , further comprising soliciting group-sourced corrections to correct the synchronizing of the text segments to the voice segments.