Analysis of phone errors attributable to phonological effects associated with language acquisition through bottleneck feature visualisations

Previous work aimed to investigate the extent to which errors attributable to phonological effects associated with language acquisition (PEALA) contribute to the output of children’s ASR. Opposite to what was intuitively expected, the proportion of errors predictable from PEALA was positively correlated with recognition accuracy, therefore increased across ages. In order to interpret this finding, the present paper employs a DNN-HMM automatic speech recognition system, built on the CSLU children’s speech corpus, to produce bottleneck feature (BNF) visualisations of phones and examine how these relate with respect to PEALA. The focus is drawn particularly on ASR errors caused by phone confusions, which are compared against phone substitution pairs indicated by PEALA. The ASR results confirm the previously observed interaction between errors predictable from PEALA and rising accuracy, but also suggest that these errors only account for a small percentage of the total phone substitution error. The BNF visualisations for the most part outline the age progression smoothly and demonstrate clear clusters of neighbouring phones consistently. The distance between PEALA related phones can be partitioned in four sets; two that increase with age (at a higher or lower rate), one that roughly remains constant and one that decreases with age.