Computer Scientist II, Speech Technology and Research Laboratory
Jennifer Smith is a computer scientist in SRI’s Speech Technology and Research (STAR) Laboratory. She contributes to research in speech analytics in multiple ways, from statistical analysis to data collection and data visualization to machine learning.
Prior to joining SRI, Smith worked in non-profit administration at a think tank focused on international human rights law.
Smith earned an M.S. in statistics from California State University, East Bay. She holds a B.A. in women’s studies and a minor in mathematics from Mills College.
Recent publications
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Speech‐based markers for post traumatic stress disorder in US veterans
This study demonstrates that a speech-based algorithm can objectively differentiate PTSD cases from controls.
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Mapping Individual to Group Level Collaboration Indicators Using Speech Data
To address the challenge of mapping characteristics of individuals’ speech to information about the group, we coded behavioral and learning-related indicators of collaboration at the individual level.
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Crowdsourcing Emotional Speech
We describe the methodology for the collection and annotation of a large corpus of emotional speech data through crowdsourcing.
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Analysis and prediction of heart rate using speech features from natural speech
We predict HR from speech using the SRI BioFrustration Corpus.In contrast to previous studies we use continuous spontaneous speech as input.
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Privacy- preserving speech analytics for automatic assessment of student collaboration
This work investigates whether nonlexical information from speech can automatically predict the quality of small-group collaborations. Audio was collected from students as they collaborated in groups of three to solve math problems.
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Spoken Interaction Modeling for Automatic Assessment of Collaborative Learning
This study investigates whether automatic audio- based monitoring of interactions can predict collaboration quality.