Cormac (Patrick Cormac) English
Title: Accommodating Accents: Investigating accent models for spoken language interaction.
The recognition and identification of non-native accents is fundamental to successful human-human speech communication and to communication between humans and machines. Much of current speech recognition now uses deep learning but a recent focus on interpretability allows for a deeper investigation of the common properties of spoken languages and language varieties which underpin different accents. This PhD project proposes to focus on what can be learned about non-canonical accents and to appropriately adjust the speech to accommodate the (machine or human) interlocutors by incorporating results of existing perceptual studies. The project aims to advance the state-of-the-art in spoken language conversational user interaction by exploiting the speaker variation space to accommodate non-native or dialect speakers. This will involve research into what are the salient phonetic properties identified during speech recognition that relate to non-canonical accents, and how can the speech or further dialogue be adjusted to ensure successful communication.