How Well Can Asr Technology Understand Foreign-Accented Speech?

Abstract


 
 
 Following the Covid-19 pandemic, digital technology is more present in classrooms than ever. Automatic Speech Recognition (ASR) offers interesting possibilities for language learners to produce more output in a foreign language (FL). ASR is especially suited for autonomous pronunciation learning when used as a dictation tool that transcribes the learner’s speech (McCROCKLIN, 2016). However, ASR tools are trained with monolingual native speakers in mind, not reflecting the global reality of English speakers. Consequently, the present study examined how well two ASR-based dictation tools understand foreign-accented speech, and which FL speech features cause intelligibility breakdowns. English speech samples of 15 Brazilian Portuguese and 15 Spanish speakers were obtained from an online database (WEINBERGER, 2015) and submitted to two ASR dictation tools: Microsoft Word and VoiceNotebook. The resulting transcriptions were manually inspected, coded and categorized. The results show that overall intelligibility was high for both tools. However, many features of normal FL speech, such as vowel and consonant substitution, caused the ASR dictation tools to misinterpret the message leading to communication breakdowns. The results are discussed from a pedagogical viewpoint.
 
 

Microsoft Reading Progress as Capt Tool

“…More recently, Nushi and Sadeghi (2021) described ELSA Speak, remarking that the focus on the American variety of English might remain problematic for learners who pronounce their utterances with other accents, even if they are native-like. Finally, Souza and Gottardi (2022) examined the ability of dictation tools MS Word and VoiceNotebook to correctly transcribe foreign accented speech. Despite high overall intelligibility, they discovered vowel and consonant substitution, which could lead to communication breakdowns.…”