3 accepted papers
Training machine learning algorithms for speech applications requires large, labeled training data sets. This is problematic for clinical applications where obtaining such data is prohibitively expensive because of privacy concerns or lack of access. As a result, clinical speech applications typical…
Instrumental analysis of speech sometimes complements subjective evaluations in speech and language therapy; however, apart from elemental speech features such as pitch and formant statistics, higher dimensional spectral features are rarely used in practice because they are clinically uninterpretabl…
A reliable online speaking rate estimation tool is useful in many domains, including speech recognition, speech therapy intervention, speaker identification, etc. This paper proposes an online speaking rate estimation model based on recurrent neural networks (RNNs). Speaking rate is a long-term feat…