Analysis of the Characteristics of Talk-show TV Programs

We examined the content of 2 talk-show TV programs in order to better understand the challenges posed by this program genre to automatic transcription. Six talk-show episodes were first segmented, transcribed and annotated by experts. Most of the speech content was found in conversational style with a significant portion of overlapped speech, about 18%. Then, automatic speech recognition experiments were conducted showing that recognition performance on talk-show programs is much worse, 28.3% word error rate (WER), in comparison with that achieved on broadcast news programs, 10.9% WER. For talkshows performance varied tangibly between non-overlapped speech, 21.8% WER, and overlapped speech, 58.5% WER. On clean, non-overlapped speech an 18.7% WER is achieved, this result is significantly worse than the result achieved for the dominant condition in broadcast news programs represented by clean read/planned speech from the anchormen, 7.6% WER.