Phonological scoring of speech
Development of a machine learning approach to score the phonological quality of speech recordings
While deep learning approaches have significantly pushed language applications like keyword spotting in audio recordings, natural language processing on text documents etc., these solutions for the masses can not applied directly to e.g. speech recordings from patients with language production deficits after stroke (aphasia).
Building upon an existing keyword spotting solution for such aphasic speech recordings, the student's task is to develop and evaluate a machine learning approach capable to deliver phonological scores of speech.
Keywords:
- recurrent neural networks
- deep learning
- embedding learning
- augmentation
- transfer learning
Filed under:
student project