Nina R Benway, PhD CCC-SLP, is a Postdoctoral Fellow in Electrical and Computer Engineering with Dr. Carol Espy-Wilson. Nina's research seeks to validate Dr. Espy-Wilson's acoustic-to-articulatory speech inversion system for child speakers and speakers with speech sound disorders, for the long-term goal of extracting corrective, knowledge-of-performance articulatory feedback from speech sound learner audio.

Nina completed her doctoral training in speech-language pathology (concentration: neuroscience) with Dr. Jonathan Preston at Syracuse University, focusing on clinical trials in children with chronic rhotic speech sound disorders. The three studies of her dissertation resulted in the curation of an open-access 175,000-utterance speech corpus, the engineering of audio classification algorithms predicting speech-language pathologist perception of rhotic speech errors, and the clinical trial validation of an artificial intelligence tool that fully automates a speech sound treatment session. Nina’s doctoral training builds upon her undergraduate training in linguistics (acoustic phonetics) at Cornell University, graduate clinical training at The College of Saint Rose, and six years of clinical practice. Through these experiences Nina has refined a multidisciplinary skill set in speech science, speech signal processing, natural language processing, corpus phonetics, machine learning/artificial intelligence (AI), user interface development, cognitive frameworks of learning, and neurocomputational frameworks of speech production.

She is an alumna of the ASHA Leadership Development Program (2016), a recipient of an American Speech-Language Hearing Foundation New Century Scholars Doctoral Scholarship (2021), and a recipient of a Graduate Dean’s Award for Excellence in Research and Creative Work at Syracuse University (2022). She was awarded an All-University Doctoral Prize (2023) for her dissertation research at Syracuse.

More information about Nina's publications can be found on her website: nrgslp.github.io.