Occurrence Frequencies of Acoustic Patterns of Vocal Fry in American English Speakers.

OBJECTIVE: The goal of this study was to analyze the occurrence frequencies of three individual acoustic patterns (A, B, C) and of vocal fry overall (A + B + C) as a function of gender, word position in the sentence (Not Last Word vs. Last Word), and sentence length (number of words in a sentence). STUDY DESIGN: This is an experimental design. METHODS: Twenty-five male and 29 female American English (AE) speakers read the Grandfather Passage. The recordings were processed by a Matlab toolbox designed for the analysis and detection of creaky segments, automatically identified using the Kane-Drugman algorithm. The experiment produced subsamples of outcomes, three that reflect a single, discrete acoustic pattern (A, B, or C) and the fourth that reflects the occurrence frequency counts of Vocal Fry Overall without regard to any specific pattern. Zero-truncated Poisson regression analyses were conducted with Gender and Word Position as predictors and Sentence Length as a covariate. RESULTS: The results of the present study showed that the occurrence frequencies of the three acoustic patterns and vocal fry overall (A + B + C) are greatest at the end of sentences but are unaffected by sentence length. The findings also reveal that AE female speakers exhibit Pattern C significantly more frequently than Pattern B, and the converse holds for AE male speakers. CONCLUSIONS: Future studies are needed to confirm such outcomes, assess the perceptual salience of these acoustic patterns, and determine the physiological correlates of these acoustic patterns. The findings have implications for the design of new excitation models of vocal fry.

Objective study of sensor relevance for automatic cough detection.

The development of a system for the automatic, objective, and reliable detection of cough events is a need underlined by the medical literature for years. The benefit of such a tool is clear as it would allow the assessment of pathology severity in chronic cough diseases. Even though some approaches have recently reported solutions achieving this task with a relative success, there is still no standardization about the method to adopt or the sensors to use. The goal of this paper is to study objectively the performance of several sensors for cough detection: ECG, thermistor, chest belt, accelerometer, contact, and audio microphones. Experiments are carried out on a database of 32 healthy subjects producing, in a confined room and in three situations, voluntary cough at various volumes as well as other event categories which can possibly lead to some detection errors: background noise, forced expiration, throat clearing, speech, and laugh. The relevance of each sensor is evaluated at three stages: mutual information conveyed by the features, ability to discriminate at the frame level cough from these latter other sources of ambiguity, and ability to detect cough events. In this latter experiment, with both an averaged sensitivity and specificity of about 94.5%, the proposed approach is shown to clearly outperform the commercial Karmelsonix system which achieved a specificity of 95.3% and a sensitivity of 64.9%.