  Generally audio news broadcast on radio is com- posed of music, commercials,
news from correspondents and recorded statements in addition to the actual news
read by the newsreader. When news transcripts are available, automatic
segmentation of audio news broadcast to time align the audio with the text
transcription to build frugal speech corpora is essential. We address the
problem of identifying segmentation in the audio news broadcast corresponding
to the news read by the newsreader so that they can be mapped to the text
transcripts. The existing techniques produce sub-optimal solutions when used to
extract newsreader read segments. In this paper, we propose a new technique
which is able to identify the acoustic change points reliably using an acoustic
Self Similarity Matrix (SSM). We describe the two pass technique in detail and
verify its performance on real audio news broadcast of All India Radio for
different languages.
