A Review of Automated Speech and Language Features for Assessment of Cognitive and Thought Disorders

no code implementations • 4 Jun 2019 • Rohit Voleti, Julie M. Liss, Visar Berisha

Broadly speaking, the review is split into two categories: language features based on natural language processing and speech features based on speech signal processing.

Objective Assessment of Social Skills Using Automated Language Analysis for Identification of Schizophrenia and Bipolar Disorder

no code implementations • 24 Apr 2019 • Rohit Voleti, Stephanie Woolridge, Julie M. Liss, Melissa Milanovic, Christopher R. Bowie, Visar Berisha

Furthermore, the same feature set can be used to build a strong binary classifier to distinguish between healthy controls and a clinical group (AUC = 0. 96) and also between patients within the clinical group with schizophrenia and bipolar I disorder (AUC = 0. 83).

Investigating the Effects of Word Substitution Errors on Sentence Embeddings

1 code implementation • 16 Nov 2018 • Rohit Voleti, Julie M. Liss, Visar Berisha

In this paper we investigate the effects of word substitution errors, such as those coming from automatic speech recognition errors (ASR), on several state-of-the-art sentence embedding methods.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +6