Nowadays, the research on materials science is rapidly entering a phase of data‐driven
age. Machine learning, one of the most powerful data‐driven methods, have been being …

In response to uncovering brain mechanisms underlying vocal communication and
searching for biomarkers for mental illnesses, speech prosody has been increasingly …

Introduction Language disorders–disorganized and incoherent speech in particular-are
distinctive features of schizophrenia. Natural language processing (NLP) offers automated …

Abstract Language abnormalities are a core symptom of schizophrenia-spectrum disorders
and could serve as a potential diagnostic marker. Natural language processing enables …

Abstract Background and Hypothesis Speech markers are digitally acquired,
computationally derived, quantifiable set of measures that reflect the state of neurocognitive …

Background In recent years, automated analyses using novel NLP methods have been used
to investigate language abnormalities in schizophrenia. In contrast, only a few studies used …

Speech in psychosis has long been ascribed as involving 'loosening of associations'. We
pursued the aim to elucidate its underlying cognitive mechanisms by analysing picture …

Introduction Alterations of verbalized thought occur frequently in psychotic disorders. We
characterize linguistic findings in individuals with schizophrenia based on the current …

TextDescriptives is a Python package for calculating a large variety of statistics from text. It is
built on top of spaCy and can be easily integrated into existing workflows. The package has …

Natural language processing (NLP) tools are increasingly used to quantify semantic
anomalies in schizophrenia. Automatic speech recognition (ASR) technology, if robust …