SPATS: Speech Perception Assessment and Training System

摘要

A software system, SPATS (patent pending), that tests and trains important bottom-up and combined bottom-up/top-down speech-perception skills is described. Bottom-up skills are the abilities to identify the constituents of syllables: onsets, nuclei, and codas in quiet and noise as produced by eight talkers. Top-down skills are the abilities to use knowledge of linguistic context to identify words in spoken sentences. The sentence module in SPATS emphasizes combined bottom-up/top-down abilities in perceiving sentences in noise. The word-initial onsets, stressed nuclei, and word-final codas are ranked in importance and grouped into subsets based on their importance. Testing utilizes random presentation of all the items included in a subset. Training in Quiet (SNR = 40 dB) or in Noise (SNR = 5 dB), is adaptively focused on individual listener’s learnable items of intermediate difficulty. Alternatively, SNR-adaption training uses Kaernbach’s algorithm to find the SNR required for a target percent correct. The unique sentence module trains the combination of bottom-up (hearing) with top-down (use of linguistic context) abilities to identify words in meaningful sentences in noise. Scoring in the sentence module is objective and automatic.