Sparse representation of speech using an atomic speech model

Speech perception has been extensively studied using degradation algorithms such as channel vocoding, mosaic speech, and pointillistic speech. Here, an "atomic speech model" is introduced to generate unique sparse time-frequency patterns. It processes speech signals using a bank of bandpass filters, undersamples the signals, and reproduces each sample using a Gaussian-enveloped tone (a Gabor atom). To examine atomic speech intelligibility, adaptive speech reception thresholds (SRTs) are measured as a function of atom rate in normal-hearing listeners, investigating the effects of spectral maxima, binaural integration, and single echo. Experiment 1 showed atomic speech with 4 spectral maxima out of 32 bands remained intelligible even at a low rate under 80 atoms per second. Experiment 2 showed that when atoms were nonoverlappingly assigned to both ears, the mean SRT increased (i.e., worsened) compared to the monaural condition, where all atoms were assigned to one ear. Individual data revealed that a few listeners could integrate information from both ears, performing comparably to the monaural condition. Experiment 3 indicated higher mean SRT with a 100 ms echo delay than that with shorter delays (e.g., 50, 25, and 0 ms). These findings demonstrate the utility of the atomic speech model for investigating speech perception and its underlying mechanisms.