Intelligibility of Time-Compressed Speech with Periodic and Aperiodic Insertions of Silence: Evidence for Endogenous Brain Rhythms in Speech Perception?

Abstract

This study was motivated by the hypothesis that low-frequency cortical oscillations help the brain decode the speech signal. The intelligibility (in terms of word error rate) of natural-sounding, synthetically-generated sentences was measured using a paradigm that alters speech-energy rhythm over a range of modulation frequencies. The material comprised 96 semantically unpredictable sentences (SUS), each approximately 2 s long, generated by a high-quality text-to-speech (TTS) synthesis engine. The TTS waveform was time-compressed by a factor of 3, creating a signal with a syllable rhythm three times faster than the original and whose intelligibility is poor (<50% words correct). A waveform with an artificial rhythm was produced by segmenting the time-compressed waveform into consecutive 40-ms fragments each followed by a silent interval. The parameters varied were the length of the silent interval (0-160 ms) and whether the intervals of silence were equal (“periodic”) or not (“aperiodic”). The performance curve (word error rate as a function of mean duration of silence) was U-shaped. The lowest word error rate occurred when the silence was 80-ms long and inserted periodically. This was also the condition for which word error rate increased when the silence was inserted aperiodically. These data are consistent with a model (“TEMPO”) in which low-frequency brain rhythms influence the ability to decode the speech signal. In TEMPO, optimum intelligibility is achieved when the syllable rhythm is within the range of the high-theta frequency brain rhythms (6-12 Hz), comparable to the rate at which segments and syllables are spoken in conversational speech.