Figure 1. Schematic of speech segmentations in automatic speech recognition (ASR) system and brain.

Segmenting continuous speech into short frames is the first step in the speech recognition process. In the ASR system, the most widely used speech segmentation approach employs fixed-size external time bins as a reference (‘time-partitioned’). This approach is computationally simple but has a limitation with respect to reflecting a quasi-regular structure of speech. Alternatively, the brain, which does not have an external timing reference, uses an intrinsic slow (neuronal) oscillatory signal as a segmentation reference. This oscillatory signal is phase-locked with the speech envelope during comprehension, which enables the reflection of quasi-regular temporal dynamics of speech in segmentation. The phase of this oscillatory signal is separated into four phase quadrants (φ_i). The speech waveform and speech-induced spike trains are segmented and color-coded by the phase angle of the reference oscillatory signal (‘phased-partitioned’). This segmentation approach can potentially generate unequally sized time bins depending on the temporal dynamics of speech. In this paper, we investigated whether the speech envelope can serve as a potential temporal reference for segmenting speech.