Resumo
Após a pandemia de Covid-19, as tecnologias digitais estão mais presente nas salas de aula do que nunca. O Reconhecimento Automático da Fala (RAF) oferece possibilidades interessantes para os aprendizes de uma língua estrangeira (LE) aumentarem sua produção oral. O RAF é especialmente adequado para a aprendizagem autônoma de pronúncia quando usado como uma ferramenta de ditado que transcreve a fala do estudante (McCROCKLIN, 2016). No entanto, as ferramentas de RAF são treinadas com falantes nativos monolíngues em mente, não refletindo a realidade dos falantes de inglês em uma escala global. Consequentemente, o presente estudo examinou quão bem duas ferramentas de ditado que utilizam ASR entendem a fala com sotaque estrangeiro e quais características causam falhas de inteligibilidade. Amostras de fala em inglês de 15 falantes de português brasileiro e 15 falantes de espanhol foram obtidas de um banco de dados online (WEINBERGER, 2015) e submetidas a duas ferramentas de ASR: Microsoft Word e VoiceNotebook. As transcrições foram manualmente inspecionadas, codificadas e categorizadas. Os resultados mostram que a inteligibilidade geral dos falantes foi alta para ambas as ferramentas. No entanto, muitas características normais, como modificações vocálicas e consonantais, da fala em LE fizeram com que as ferramentas de ditado ASR interpretassem mal a mensagem, levando a falhas de comunicação. Os resultados são discutidos do ponto de vista pedagógico.
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