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Found 8 papers, 2 papers with code
A Speech Production Model for Radar: Connecting Speech Acoustics with Radar-Measured Vibrations
Millimeter Wave (mmWave) radar has emerged as a promising modality for speech sensing, offering advantages over traditional microphones.
Automated Extraction of Spatio-Semantic Graphs for Identifying Cognitive Impairment
These results highlight the potential of the automated approach for extracting spatio-semantic features in developing clinical speech models for cognitive impairment assessment.
Applications of Artificial Intelligence for Cross-language Intelligibility Assessment of Dysarthric Speech
Purpose: Speech intelligibility is a critical outcome in the assessment and management of dysarthria, yet most research and clinical practices have focused on English, limiting their applicability across languages.
A Tutorial on Clinical Speech AI Development: From Data Collection to Model Validation
Specifically, this paper will cover the design of speech elicitation tasks and protocols most appropriate for different clinical conditions, collection of data and verification of hardware, development and validation of speech representations designed to measure clinical constructs of interest, development of reliable and robust clinical prediction models, and ethical and participant considerations for clinical speech AI.
Requirements for Mass Adoption of Assistive Listening Technology by the General Public
Assistive listening systems (ALSs) dramatically increase speech intelligibility and reduce listening effort.
Robust Vocal Quality Feature Embeddings for Dysphonic Voice Detection
In this paper, we propose a deep learning framework for generating acoustic feature embeddings sensitive to vocal quality and robust across different corpora.
TorchDIVA: An Extensible Computational Model of Speech Production built on an Open-Source Machine Learning Library
The DIVA model is a computational model of speech motor control that combines a simulation of the brain regions responsible for speech production with a model of the human vocal tract.
Robust Estimation of Hypernasality in Dysarthria with Acoustic Model Likelihood Features
To demonstrate that the features derived from these acoustic models are specific to hypernasal speech, we evaluate them across different dysarthria corpora.
