Recognition of continuously spoken letters by listeners and spectrogram readers

Abstract

Because of acoustic similarities between some letters of the alphabet, automatic recognition of continuously spoken letters is a difficult task. The goal of this study is to determine and compare how well listeners and spectrogram readers can recognize continuously spoken letter strings from multiple speakers. The interest in spectrogram reading results is motivated by the belief that this procedure may help to identify acoustic attributes and decision strategies that are useful for system implementation. Listening and spectrogram reading tests involving eight listeners and six spectrogram readers, respectively, were conducted using a corpus of 1000 wordlike strings designed to minimize the use of lexical knowledge. Results show that listeners' performance was better than readers' (98.4% vs 91.0%). In both experiments, string lengths were determined very accurately (98.1% and 96.2%), presumably due to the large number of glottal stops inserted at letter boundaries to facilitate segmentation. Most of the errors were due to substitution of one letter for another (68% and 92%), and they generally fall into two categories. Asymmetric errors can often be attributed to subjects' disregard for contextual influence, whereas symmetric errors are largely due to acoustic similarities between certain letter pairs. Subsequent acoustic study of four of the most confusable letter pairs has resulted in the identification of a number of distinguishing acoustic attributes. Using these attributes, overall recognition performance better than that of the readers was achieved. [Work supported by NSF and DARPA under contract N00014-82-K-0727, monitored through the Office of Naval Research.]