  The COVID-19 pandemic has led to an increased use of remote telephonic
interviews, making it important to distinguish between scripted and spontaneous
speech in audio recordings. In this paper, we propose a novel scheme for
identifying read and spontaneous speech. Our approach uses a pre-trained
DeepSpeech audio-to-alphabet recognition engine to generate a sequence of
alphabets from the audio. From these alphabets, we derive features that allow
us to discriminate between read and spontaneous speech. Our experimental
results show that even a small set of self-explanatory features can effectively
classify the two types of speech very effectively.
