Extracting the acoustic features of interruption points using non-lexical prosodic analysis

Non-lexical prosodic analysis is our term for the process of extracting prosodic structure from a speech waveform without reference to the lexical contents of the speech. It has been shown that human subjects are able to perceive prosodic structure within speech without lexical cues. There is some evidence that this extends to the perception of disfluency, for example, the detection interruption points (IPs) in low pass filtered speech samples. In this paper, we apply non-lexical prosodic analysis to a corpus of data collected for a speaker in a multi-person meeting environment. We show how nonlexical prosodic analysis can help structure corpus data of this kind, and reinforce previous findings that non-lexical acoustic cues can help detect IPs. These cues can be described by changes in amplitude and f0 after the IP and they can be related to the acoustic characteristics of hyper-articulated speech.