PodZinger rejects Jesus is the title of a blog entry by University of Pennsylvania Professor Mark Liberman, who is in both the Linguistics and Computer Science departments.  Prof. Liberman is very knowledgable about the techniques we use to generate our speech-to-text index of podcasts, and wrote about the strengths and weaknesses of our state-of-the-art speech recognition technology.

We use a statistical model of word and n-gram sequences in order to  produce a sequence of words that we think was the most probable word sequence matching the phoneme sequence that we recognized.  If the type of input (like entertainment vs news) is a good match to our corpus or training material, then our word error rates are likely to be quite low.

While we specifically haven’t trained on a corpus of religious texts, we have indexed a tremendous amount of sermons.  The largest podcast series I know of is “Sermon Audio” of which we have indexed 3,860 episodes at this writing, many of which appear to no longer be accessible. 

In total so far, Sermon Audio has 18.8 million words, and total 2706 hours worth of sermons.  So in fact PodZinger has listened to more sermons than anyone I know.