The feasibility of using acoustic measures for predicting the Total Opacity Scores of chest computed tomography scans in patients with COVID-19.

To study the possibility of using acoustic parameters, i.e., Acoustic Voice Quality Index (AVQI) and Maximum Phonation Time (MPT) for predicting the degree of lung involvement in COVID-19 patients. This cross-sectional case-control study was conducted on the voice samples collected from 163 healthy individuals and 181 patients with COVID-19. Each participant produced a sustained vowel/a/, and a phonetically balanced Persian text containing 36 syllables. AVQI and MPT were measured using Praat scripts. Each patient underwent a non-enhanced chest computed tomographic scan and the Total Opacity score was rated to assess the degree of lung involvement. The results revealed significant differences between patients with COVID-19 and healthy individuals in terms of AVQI and MPT. A significant difference was also observed between male and female participants in AVQI and MPT. The results from the receiver operating characteristic curve analysis and area under the curve indicated that MPT (0.909) had higher diagnostic accuracy than AVQI (0.771). A significant relationship was observed between AVQI and TO scores. In the case of MPT, however, no such relationship was observed. The findings indicated that MPT was a better classifier in differentiating patients from healthy individuals, in comparison with AVQI. The results also showed that AVQI can be used as a predictor of the degree of patients' and recovered individuals' lung involvement. A formula is suggested for calculating the degree of lung involvement using AVQI.

WordPars: A tool for orthographic and phonological neighborhood and other psycholinguistic statistics in Persian.

This paper presents a Windows program providing statistics on word and non-word stimuli in Persian, including word frequency, orthographic and phonological length, orthographic and phonological neighbors, and transposed-letter neighbors. It also generates possible non-words that are orthographic neighbors of the target word. Persian is an under-represented Indo-European language that has historically been influenced by Arabic and adopted certain characteristics in its writing, e.g., the omission of short vowels. This tool aims to help researchers in psycholinguistics, specifically with regard to isolated word recognition in Persian. This downloadable program computes the aforementioned indices free of charge. This tool uses two corpora, i.e., Zaya corpus and WorldLex, for reporting and computing statistics and is a user-friendly program provided in English that is also easy to work with for non-Persian researchers. It can be accessed from https://github.com/ssaneei/Wordpars .

Do you have COVID-19? An artificial intelligence-based screening tool for COVID-19 using acoustic parameters.

This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19 patients based on the acoustic parameters of their voices. Twenty-five acoustic parameters were extracted from voice samples of 203 COVID-19 patients and 171 healthy individuals who produced a sustained vowel, i.e., /a/, as long as they could after a deep breath. The selected acoustic parameters were from different categories including fundamental frequency and its perturbation, harmonicity, vocal tract function, airflow sufficiency, and periodicity. After the feature extraction, different machine learning methods were tested. A leave-one-subject-out validation scheme was used to tune the hyper-parameters and record the test set results. Then the models were compared based on their accuracy, precision, recall, and F1-score. Based on accuracy (89.71%), recall (91.63%), and F1-score (90.62%), the best model was the feedforward neural network (FFNN). Its precision function (89.63%) was a bit lower than the logistic regression (90.17%). Based on these results and confusion matrices, the FFNN model was employed in the software. This screening tool could be practically used at home and public places to ensure the health of each individual's respiratory system. If there are any related abnormalities in the test taker's voice, the tool recommends that they seek a medical consultant.

A Case Study of Negative Affixes in Sadegh Hedayat's Letters: The Effect of Bipolar Mood Disorder.

This research studies the morphological features found in Sadegh Hedayat's letters, who, based on linguistic and psychological studies, may have had bipolar disorder. It aims to assess the impact of various types of moods on the frequency of negative affixes through qualitative analysis of the letters' text. The letters are written in Persian, and include six negative derivational affixes. As bipolar disorder includes four episodes, all letters are analyzed on the basis of six negative affixes concerning the episodes using SPSS. The results indicate that each episode shows totally different characteristics in using negative affixes. In fact, Hedayat mostly used negative affixes in depression, confirming psychological studies, and it is revealed that he mostly used negative affixes in hypomania when he experienced an irritated mood. Moreover, the frequency of negative affixes in mixed episode shows a combination of hypomania and depression, which is in agreement with previous studies. Additionally, euthymia shows few negative affixes.

Cepstral Analysis of Voice in Patients With Temporomandibular Disorders.

OBJECTIVES: This study aimed to assess the voice quality of patients with temporomandibular disorders (TMDs) compared with healthy subjects using cepstral analysis and investigate the relationship between the TMD severity and the values of cepstral analysis. METHODS: Subjects who met the inclusion criteria completed a general health questionnaire and the Fonseca Anamnestic Index. Patients who had TMDs with FAI were subjected to an examination based on the Diagnostic Criteria for Temporomandibular Disorders. The final sample included 65 subjects, 31 TMDs patients (with a mean age ± standard deviation of 36.64 ± 13.67 years), and 34 healthy individuals in the control group (with a mean age ± standard deviation of 30.35 ± 7.78 years). Cepstral Peak Prominence (CPP) and Smoothened Cepstral Peak Prominence (CPPS) of a sustained vowel and connected speech were computed using Praat software. RESULTS: TMD patients indicated lower cepstral values and lower voice quality compared to the control group. Significant differences were found between TMD and control groups for all cepstral parameters (P < .001) and cepstral measurements showed a moderate to strong negative correlation with TMD severity (P < .001, rho = -0.57 to -0.88). CONCLUSION: The outcomes of the present study indicate that cepstral analysis can accurately distinguish the reduced voice quality of TMD patients from normal voice.

Voice Quality Evaluation in Patients With COVID-19: An Acoustic Analysis.

OBJECTIVES: With the COVID-19 outbreak around the globe and its potential effect on infected patients' voice, this study set out to evaluate and compare the acoustic parameters of voice between healthy and infected people in an objective manner. METHODS: Voice samples of 64 COVID-19 patients and 70 healthy Persian speakers who produced a sustained vowel /a/ were evaluated. Between-group comparisons of the data were performed using the two-way ANOVA and Wilcoxon's rank-sum test. RESULTS: The results revealed significant differences in CPP, HNR, H1H2, F0SD, jitter, shimmer, and MPT values between COVID-19 patients and the healthy participants. There were also significant differences between the male and female participants in all the acoustic parameters, except jitter, shimmer and MPT. No interaction was observed between gender and health status in any of the acoustic parameters. CONCLUSION: The statistical analysis of the data revealed significant differences between the experimental and control groups in this study. Changes in the acoustic parameters of voice are caused by the insufficient airflow, and increased aperiodicity, irregularity, signal perturbation and level of noise, which are the consequences of pulmonary and laryngological involvements in patients with COVID-19.

A Comparison of Persian Vowel Production in Hearing-Impaired Children Using a Cochlear Implant and Normal-Hearing Children.

OBJECTIVE: Normal-hearing (NH) acuity and auditory feedback control are crucial for human voice production and articulation. The lack of auditory feedback in individuals with profound hearing impairment changes their vowel production. The purpose of this study was to compare Persian vowel production in deaf children with cochlear implants (CIs) and that in NH children. METHODS: The participants were 20 children (12 girls and 8 boys) with age range of 5 years; 1 month to 9 years. All patients had congenital hearing loss and received a multichannel CI at an average age of 3 years. They had at least 6 months experience of their current device (CI). The control group consisted of 20 NH children (12 girls and 8 boys) with age range of 5 to 9 years old. The two groups were matched by age. Participants were native Persian speakers who were asked to produce the vowels /i/, /e/, /ӕ/, /u/, /o/, and /a/. The averages for first formant frequency (F1) and second formant frequency (F2) of six vowels were measured using Praat software (Version 5.1.44, Boersma & Weenink, 2012). The independent samples t test was conducted to assess the differences in F1 and F2 values and the area of the vowel space between the two groups. RESULTS: Mean values of F1 were increased in CI children; the mean values of F1 for vowel /i/ and /a/, F2 for vowel /a/ and /o/ were significantly different (P < 0.05). The changes in F1 and F2 showed a centralized vowel space for CI children. CONCLUSIONS: F1 is increased in CI children, probably because CI children tend to overarticulate. We hypothesis this is due to a lack of auditory feedback; there is an attempt by hearing-impaired children to compensate via proprioceptive feedback during articulatory process.