Effects of training length on adaptation to noise-vocoded speech.

Listeners show rapid perceptual learning of acoustically degraded speech, though the amount of exposure required to maximize speech adaptation is unspecified. The current work used a single-session design to examine the length of auditory training on perceptual learning for normal hearing listeners exposed to eight-channel noise-vocoded speech. Participants completed short, medium, or long training using a two-alternative forced choice sentence identification task with feedback. To assess learning and generalization, a 40-trial pre-test and post-test transcription task was administered using trained and novel sentences. Training results showed all groups performed near ceiling with no reliable differences. For test data, we evaluated changes in transcription accuracy using separate linear mixed models for trained or novel sentences. In both models, we observed a significant improvement in transcription at post-test relative to pre-test. Critically, the three training groups did not differ in the magnitude of improvement following training. Subsequent Bayes factors analysis evaluating the test by group interaction provided strong evidence in support of the null hypothesis. For these stimuli and procedure, results suggest increased training does not necessarily maximize learning outcomes; both passive and trained experience likely supported adaptation. Findings may contribute to rehabilitation recommendations for listeners adapting to degraded speech signals.

Individual differences in visual pattern completion predict adaptation to degraded speech.

Recognizing acoustically degraded speech relies on predictive processing whereby incomplete auditory cues are mapped to stored linguistic representations via pattern recognition processes. While listeners vary in their ability to recognize degraded speech, performance improves when a written transcription is presented, allowing completion of the partial sensory pattern to preexisting representations. Building on work characterizing predictive processing as pattern completion, we examined the relationship between domain-general pattern recognition and individual variation in degraded speech learning. Participants completed a visual pattern recognition task to measure individual-level tendency towards pattern completion. Participants were also trained to recognize noise-vocoded speech with written transcriptions and tested on speech recognition pre- and post-training using a retrieval-based transcription task. Listeners significantly improved in recognizing speech after training, and pattern completion on the visual task predicted improvement for novel items. The results implicate pattern completion as a domain-general learning mechanism that can facilitate speech adaptation in challenging contexts.