Abstract
Background: This paper presents a first study on the assessment of Cancer-Related Cognitive Impairment (CRCI) with speech analysis. CRCI is a reported change in cognitive performance by cancer patients, which is too subtle to be detected by the current tests in use. Speech analysis might provide a solution to this issue. Speech analysis can be instrumental in the detection of subtle cognitive impairment, as speech contains fine-grained segmental and suprasegmental parameters that are sensitive to changes in cognition. Pauses have particularly been highlighted as potential behavioral markers of neurocognitive disorders. However, the absence of simple, detailed methods compromises the feasibility of speech analyses in clinical practice.Objectives: This study aims (i) to identify breast cancer survivors with CRCI using a new practical method centered on speech pauses, and (ii) to provide the detailed protocol that supports this study, which is intended to be applicable in clinical contexts. Methods: Thirty-three breast cancer survivors with a cognitive complaint, eleven breast cancer survivors without a cognitive complaint and thirteen controls were included in the study. Participants were instructed to tell a picture-based story. Their narratives were recorded, automatically transcribed with Whisper, and analyzed using the SPPAS and Praat software. Silent pauses, filled pauses, and sustained vowels were annotated, then processed in RStudio for statistical analysis.Results: Only silent pause duration was significantly longer for breast cancer survivors with a cognitive complaint than for controls. Conclusions: The results suggest that silent pause duration is a good marker for detecting CRCI. Automatizing the transcription and annotation of speech data improves the feasibility of speech analysis in clinical contexts, although a manual check is required.