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. Author manuscript; available in PMC: 2024 Sep 25.
Published in final edited form as: Int IEEE EMBS Conf Neural Eng. 2023 May 19;2023:10.1109/ner52421.2023.10123751. doi: 10.1109/ner52421.2023.10123751

Fig. 1. Approach overview.

Fig. 1.

This work focuses on developing an ASR tool to score the intelligibility of synthesized speech, which would fill an important gap in the overall effort to build a speech restoration brain-computer interface. An important next step is to validate that this automated metric scores intelligibility in a way that is similar to actual human listeners.