Automatic pronunciation verification of english letter-names for early literacy assessment of preliterate children

Children need to master reading letter-names and letter-sounds before reading phrases and sentences. Pronunciation assessment of letter-names and letter-sounds read aloud is an important component of preliterate children´s education, and automating this process can have several advantages. The goal of this work was to automatically verify letter-names spoken by kindergarteners and first graders in realistic classroom noise conditions. We applied the same techniques developed in our previous work on automatic letter-sound verification by comparing and optimizing different acoustic models, dictionaries, and decoding grammars. Our final system was unbiased with respect to the child´s grade, age, and native language and achieved 93.1% agreement (0.813 kappa agreement) with human evaluators, who agreed among themselves 95.4% of the time (0.891 kappa).