Speech rate change detection in martingale framework

Automatic speech recognition of conversational speech has not reached the level of practical use yet. Possible reasons are 1) multiple speakers speak in turn or sometimes at the same time, and 2) they speak very casually. One of key features to characterize conversational speech is the speaking speed. By knowing the speaking speed it becomes possible to adapt a recognition system to speech at that speed. Therefore, in this paper, we aim to estimate the speech rate in real time in order to choose a recognition model suitable for the speech rate. This paper introduces a probabilistic method for estimating the speech rate as well as the changing points of speech rates. We use a martingale framework in two stages to this goal. For examining the effectiveness of our method, two experiments are conducted. First, phoneme-level speech rate change detection is tried in both of reading and conversational speech. Second, the detection of the changing points of word-level speech rates is tried.