--no%20markings.jpg)
HANNAH ROWE
Hello! I am a speech scientist and certified speech-language pathologist interested in speech motor control in neurologically impaired populations. I completed my PhD in Rehabilitation Sciences at the MGH Institute of Health Professions (advisor: Dr. Jordan Green) and am currently a postdoctoral research fellow in speech neuroscience at Boston University (advisor: Dr. Frank Guenther).
My overarching goal is to further the field of personalized medicine in speech motor-impaired populations, with a particular focus on adults who stutter and individuals with neurodegenerative diseases. Specifically, I aim to use comprehensive, multimodal measures (i.e., behavioral assessments, physiological recordings, and neurological measures) in speech motor-impaired populations to (1) improve differential diagnosis, (2) motivate the development of individualized treatments/technologies, and (3) provide granular outcome measures for monitoring disease progression and evaluating treatment efficacy. Click here for a complete list of publications:
https://www.ncbi.nlm.nih.gov/myncbi/hannah.rowe.2/bibliography/public/
​
I live with my husband and our dog (/child) in Boston, and my life interests include playing music and running, hiking, and skiing in beautiful places.
FEATURED PUBLICATIONS
THE EFFICACY OF ACOUSTIC-BASED ARTICULATORY PHENOTYPING FOR CHARACTERIZING AND CLASSIFYING DIVERGENT
NEURODEGENERATIVE DISEASES
Rowe, H.P., Gochyyev, P., Lammert, A.C., Lowit, A., Spencer, K.A., Dickerson, B.C., Berry, J., & Green, J.R. (2022). Journal of Neural Transmission.
This study sought to assess the articulatory phenotypes of four neurodegenerative populations known to have divergent speech motor deficits and determine the efficacy of articulatory phenotyping for classifying different diseases. We aimed to address a primary limitation of the current differential diagnosis literature by expanding the range of neurological/pathophysiological deficits and articulatory characteristics examined in one study. We found evidence of distinct articulatory phenotypes for the four clinical groups (i.e., ALS, PA, PD, and nfPPA + PAOS), which highlights the phenotypic variability present across neurodegenerative diseases. Additionally, the phenotypes demonstrated strong classification accuracy for characterizing neurodegenerative diseases, which emphasizes the potential clinical utility of using a comprehensive profile of articulation.
QUANTIFYING ARTICULATORY
IMPAIRMENTS IN NEURODEGENERATIVE MOTOR DISEASES: A SCOPING REVIEW AND META-ANALYSIS OF INTERPRETABLE
ACOUSTIC FEATURES
Rowe, H.P., Shellikeri, S., Yunusova, Y., Chenausky, K., & Green, J.R. (2022). International Journal of Speech-Language Pathology.
Overall, our findings revealed a strong focus in the speech motor literature on acoustic features that represent precision and an underrepresentation of studies on features that represent coordination, consistency, speed, and repetition rate. In light of the need for research across all articulatory components to elucidate articulatory phenotypes, the restricted focus on precision is problematic. Furthermore, while the limited data in our meta-analysis precluded us from making specific recommendations regarding the most promising feature for each population, our results revealed phenotypic variability in articulatory impairments across speech motor subtypes. This finding motivates the need to employ more impairment-specific knowledge in algorithm development, which may significantly extend the impact such models have for individuals with NMDs. However, there remains a significant need to broaden and deepen our understanding of the articulatory phenotypes underlying NMDs.
CHARACTERIZING DYSARTHRIA DIVERSITY FOR AUTOMATIC SPEECH RECOGNITION: A CLINICAL PERSPECTIVE
Rowe, H.P., Gutz, S.E., Maffei, M.F., Tomanek, K., & Green, J.R. (2022). Frontiers in Computer Science.
Improving ASR accuracy for dysarthric speech may have significant implications for communication and quality of life. This article outlined the sources of diversity inherent to speech motor disorders, their potential impact on ASR performance, and the importance of their representation in training sets. Representing dysarthric speech variability in ASR corpora may be an important step for improving disordered speech ASR and is consistent with the call to action in the artificial intelligence community to reduce bias in the training data by increasing diversity.
VALIDATION OF AN ACOUSTIC-BASED FRAMEWORK OF SPEECH MOTOR CONTROL: ASSESSING CRITERION AND CONSTRUCT VALIDITY USING KINEMATIC AND PERCEPTUAL MEASURES
Rowe, H.P., Stipancic, K.L., Lammert, A.C., & Green, J.R. (2021). Journal of Speech, Language, and Hearing Research.
The results of this study demonstrate that our acoustically driven framework has potential as an objective, valid, and clinically useful tool for profiling articulatory deficits in individuals with speech motor disorders. Our findings also suggest that compared to clinician ratings, instrumental measures may be more sensitive to subtle differences in articulatory function. With further research, this framework could provide accurate and reliable characterizations of articulatory impairment, which may eventually increase the efficacy of diagnosis and treatment for patients with different articulatory phenotypes.
ACOUSTIC-BASED ARTICULATORY PHENOTYPES OF AMYOTROPHIC LATERAL SCLEROSIS AND PARKINSON'S DISEASE: TOWARDS AN INTERPRETABLE, HYPOTHESIS-DRIVEN FRAMEWORK OF MOTOR CONTROL
Rowe, H.P., Gutz, S.E., Maffei, M.F., & Green, J.R. (2020). Interspeech.
Taken together, the findings suggest that our framework has potential as a valid diagnostic tool with which we can discriminate speech motor disorders based on their underlying articulatory impairments. These phenotypes—derived from interpretable, hypothesis-driven features—can inform classification algorithms for differential diagnosis and guide impairment-based feature selection for ASR models, ultimately increasing clinical confidence in assessing and treating speech motor disorders. Further research is needed to validate our acoustic features against corresponding biomechanical features.
PROFILING SPEECH MOTOR IMPAIRMENTS IN PERSONS WITH AMYOTROPHIC LATERAL SCLEROSIS: AN ACOUSTIC-BASED APPROACH
Rowe, H.P. & Green, J.R. (2019). Interspeech.
In this paper, we proposed a novel framework composed of four key components of speech motor control (i.e., coordination, consistency, speed, and precision) to characterize speech impairments in persons with ALS. Our findings revealed impairments across all components except consistency. We also found that consistency, speed, and precision were correlated with speech severity in the ALS group as indexed by SMR. Additional research is required to determine whether these four components of speech motor control correlate with functional measures of speech such as intelligibility. Further research is also needed to test this framework with other types of dysarthria that are likely to be characterized by different patterns of impairments. The results of such studies will inform impairment-specific ASR models and determine the use of this framework as an effective assessment tool.
