Cepstral Analysis of Hypokinetic and Ataxic Voices: Correlations With Perceptual and Other Acoustic Measures

Long-term voice outcomes of medialization thyroplasty with adjustable implant for unilateral vocal fold paralysis

OBJECTIVES

Medialization thyroplasty (MT) using various implants has been employed as a corrective procedure for unilateral vocal fold paralysis (UVFP). A newly developed APrevent® vocal implant system (VOIS) offers an innovative solution with a finely adjustable design. This study aimed to investigate the long-term functional voice outcomes and benefits of postoperative adjustments in patients receiving MT using the VOIS-implant.

METHODS

This is a prospective case series study at single tertiary medical center. Fourteen adult patients diagnosed with UVFP received MT with the VOIS implant and were followed up for more than 1 year. Implant adjustment procedure by injecting 0.9% physiological saline solution was performed both during and after the surgery to optimize glottal closure and voice quality. Objective voice outcomes and acoustic parameters were assessed preoperatively and postoperatively at various timepoints.

RESULTS

Thirteen patients (93%) received intraoperative balloon adjustment, ranging from 0.05to 0.12 ml. Four patients underwent adjustments postoperatively and exhibited a positive trend towards immediately improving acoustic voice quality. Our long-term results demonstrated a notable improvement after the surgery in voice quality, with significant decreases in VHI-30 and improvements in perceptual parameters of GRBAS scale, acoustic measures such as jitter and signal-to-noise ratio (p < 0.001) and cepstral peak prominence smoothed in sustained vowel and short sentences. The voice outcomes remained stable more than 1 year follow-up.

CONCLUSIONS

Overall, MT with VOIS implantation provides a favorable long-term outcomes and stability in voice quality for patients with UVFP and also an effective tool for postoperative adjustment without major revision surgeries.

Effects of a Concurrent Working Memory Task on Speech Acoustics in Parkinson's Disease

PURPOSE

The purpose of this study was to determine the effect of a concurrent working memory task on acoustic measures of speech in individuals with Parkinson's disease (PD).

METHOD

Individuals with PD and age- and sex-matched controls performed a speaking task with and without a Stroop-like concurrent working memory task. Cepstral peak prominence, low-to-high spectral energy ratio, fundamental frequency (fo) standard deviation, articulation rate, pause duration, articulatory-acoustic vowel space, relative fo, mean voice onset time (VOT), and VOT variability were calculated for each condition. Mixed-model analyses of variance were performed to determine the effects of group, condition (presence of the concurrent working memory task), and their interaction on the acoustic measures.

RESULTS

All measures except for VOT variability, mean pause duration, and relative fo offset differed between people with and without PD. Cepstral peak prominence, articulation rate, and relative fo offset differed as a function of condition. However, no measures indicated disparate effects of condition as a function of group.

CONCLUSION

Although differentially impactful on limb motor function in PD, here a concurrent working memory task was not found to be differentially disruptive to speech acoustics in PD.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.24759648.

Acoustic Measures of Dysphonia in Amyotrophic Lateral Sclerosis

PURPOSE

Identifying efficacious measures to characterize dysphonia in complex neurodegenerative diseases is key to optimal assessment and intervention. This study evaluates the validity and sensitivity of acoustic features of phonatory disruption in amyotrophic lateral sclerosis (ALS).

METHOD

Forty-nine individuals with ALS (40-79 years old) were audio-recorded while producing a sustained vowel and continuous speech. Perturbation/noise-based (jitter, shimmer, and harmonics-to-noise ratio) and cepstral/spectral (cepstral peak prominence, low-high spectral ratio, and related features) acoustic measures were extracted. The criterion validity of each measure was assessed using correlations with perceptual voice ratings provided by three speech-language pathologists. Diagnostic accuracy of the acoustic features was evaluated using area-under-the-curve analysis.

RESULTS

Perturbation/noise-based and cepstral/spectral features extracted from /a/ were significantly correlated with listener ratings of roughness, breathiness, strain, and overall dysphonia. Fewer and smaller correlations between cepstral/spectral measures and perceptual ratings were observed for the continuous speech task, although post hoc analyses revealed stronger correlations in speakers with less perceptually impaired speech. Area-under-the-curve analyses revealed that multiple acoustic features, particularly from the sustained vowel task, adequately differentiated between individuals with ALS with and without perceptually dysphonic voices.

CONCLUSIONS

Our findings support using both perturbation/noise-based and cepstral/spectral measures of sustained /a/ to assess phonatory quality in ALS. Results from the continuous speech task suggest that multisubsystem involvement impacts cepstral/spectral analyses in complex motor speech disorders such as ALS. Further investigation of the validity and sensitivity of cepstral/spectral measures during continuous speech in ALS is warranted.

Singing and Speaking Ability in Parkinson's Disease and Spinocerebellar Ataxia

PURPOSE

This study examined spontaneous, spoken-to-a-model, and two sung modes in speakers with Parkinson's disease (PD), speakers with cerebellar disease (CD), and healthy controls. Vocal performance was measured by intelligibility scores and listeners' perceptual ratings.

METHOD

Participants included speakers with hypokinetic dysarthria secondary to PD, those with ataxic dysarthria secondary to CD, and healthy speakers. Participants produced utterances in four vocal modes: spontaneous speech, spoken-to-a-model, sung-to-a-model, and spontaneous singing. For spoken-to-a-model and sung-to-a-model modes, written material was provided the model. For spontaneous singing, participants sang songs that they endorsed as familiar.

DEPENDENT VARIABLES

In Experiment I, listeners orthographically transcribed the audio samples of the first three vocal modes. In Experiment IIa, raters evaluated the accuracy of the pitch and rhythm of the spontaneous singing of familiar songs. Finally, familiar songs and sung-to-a-model utterances were rated on a competency scale by a second group of raters (Experiment IIb).

RESULTS

Results showed increases in intelligibility during the spoken-to-a-model mode compared with the spontaneous mode in both PD and CD groups. Singing enhanced the vocal output of speakers with PD more than in speakers with CD, as measured by percent intelligibility. PD participants' pitch and rhythm accuracy and competency in singing familiar songs was rated more favorably than those produced by CD participants.

CONCLUSIONS

The findings reveal a vocal task effect for spoken utterances in both groups. Sung exemplars, more impaired in CD, suggest a significant involvement of the cerebellum in singing.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21809544.

A Cepstral Analysis of Pathological Voice Quality in the Korean Population using Praat

OBJECTIVES

This study aimed to investigate the reference values for cepstral peak prominence (CPP) and smoothed CPP (CPPS) measured using Praat in Korean speakers with the normal, healthy and pathological voice.

METHODS

A total of 4,524 Korean participants with vocally healthy (n = 410) and dysphonic voices (n = 4,114) participated in this study. The speech task consisted of a sustained vowel /a/ and a sentence reading the Korean passage "Walk". CPP and CPPS values were quickly and automatically measured in sustained vowel and continuous speech tasks using Praat script. Furthermore, three veteran speech language pathologists (SLPs) scored the severity of dysphonia using the GRBAS scale (grade, roughness, breathiness, asthenia, strain) and Consensus Auditory Perceptual Evaluation of Voice (CAPE-V).

RESULTS

Three SLPs showed high inter- and intra-rater reliabilities (IRR) in auditory-perceptual (A-P) evaluation. Significant differences were confirmed in CPP and CPPS between the normally healthy and pathological voice groups for both voice tasks (P < 0.01). The measured values of CPP and CPPS varied depending on the laryngeal pathology. In the receiver operating characteristic (ROC) curve analysis, the CPP_Vowel (CPP_V), CPPS_V, CPP_Sentence (CPP_S), and CPPS_S cut-off values were <21.5, <12.0, <19.7, and <10.1, respectively. Through ROC curve analysis, it was confirmed that CPP and CPPS had excellent diagnostic accuracy in distinguishing disordered voice (area under the ROC: 0.951-0.966).

CONCLUSION

We investigated the reference values for CPP and CPPS measured with Praat for Korean speakers and confirmed that cepstral analysis is a promising tool for differentiating pathological voice.

Use of Laughter for the Detection of Parkinson's Disease: Feasibility Study for Clinical Decision Support Systems, Based on Speech Recognition and Automatic Classification Techniques

Parkinson's disease (PD) is an incurable neurodegenerative disorder which affects over 10 million people worldwide. Early detection and correct evaluation of the disease is critical for appropriate medication and to slow the advance of the symptoms. In this scenario, it is critical to develop clinical decision support systems contributing to an early, efficient, and reliable diagnosis of this illness. In this paper we present a feasibility study for a clinical decision support system for the diagnosis of PD based on the acoustic characteristics of laughter. Our decision support system is based on laugh analysis with speech recognition methods and automatic classification techniques. We evaluated different cepstral coefficients to identify laugh characteristics of healthy and ill subjects combined with machine learning classification models. The decision support system reached 83% accuracy rate with an AUC value of 0.86 for PD-healthy laughs classification in a database of 20,000 samples randomly generated from a pool of 120 laughs from healthy and PD subjects. Laughter could be employed for the efficient and reliable detection of PD; such a detection system can be achieved using speech recognition and automatic classification techniques; a clinical decision support system can be built using the above techniques. Significance: PD clinical decision support systems for the early detection of the disease will help to improve the efficiency of available and upcoming therapeutic treatments which, in turn, would improve life conditions of the affected people and would decrease costs and efforts in public and private healthcare systems.

Individual Voice Dimensions' Prediction of Overall Dysphonia Severity on Two Auditory-Perceptual Scales

BACKGROUND

Auditory-perceptual evaluation of dysphonic voice is an essential clinical activity that characterizes the nature of dysphonia and aids in planning its clinical management. Although there are multidimensional acoustic measures that correlate well with overall severity ratings, they tend to include measures that have only small or moderate correlations with individual voice characteristics frequently perceptually measured (e.g., breathiness or roughness). Given this difference between perceptual and acoustic measures, it is unclear how much individual voice characteristics contribute to a listener's perception of overall severity of dysphonia.

PURPOSE

The purpose of this study was to explore individual voice characteristics' relative contribution to the rating of overall dysphonia severity and to explore sex-related differences.

METHOD

Two hundred ninety-six voice samples were accessed from the Perceptual Voice Qualities Database. Roughness, breathiness, asthenia, strain, pitch, and loudness ratings from the Grade, Roughness, Breathiness, Asthenia, Strain and Consensus Auditory-Perceptual Evaluation of Voice scales were used to predict overall voice quality severity in linear regression with bootstrapped coefficients.

RESULTS

Roughness, breathiness, and strain were the strongest predictors of overall severity. Asthenia and, to a lesser extent, pitch were also significant predictors of overall severity. Loudness was not a significant predictor. There were several sex-related differences noted, as well as differences related to the scale used.

CONCLUSIONS

Breathiness, roughness, and strain were all important predictors of overall severity for all regressions. Clinicians should be aware of scale-related differences if they are using auditory-perceptual measures to choose voice therapy targets. Analyses accounting for perceptual strategy differences were recommended for future studies.

Study protocol for using a smartphone application to investigate speech biomarkers of Parkinson's disease and other synucleinopathies: SMARTSPEECH

INTRODUCTION

Early identification of Parkinson's disease (PD) in its prodromal stage has fundamental implications for the future development of neuroprotective therapies. However, no sufficiently accurate biomarkers of prodromal PD are currently available to facilitate early identification. The vocal assessment of patients with isolated rapid eye movement sleep behaviour disorder (iRBD) and PD appears to have intriguing potential as a diagnostic and progressive biomarker of PD and related synucleinopathies.

METHODS AND ANALYSIS

Speech patterns in the spontaneous speech of iRBD, early PD and control participants' voice calls will be collected from data acquired via a developed smartphone application over a period of 2 years. A significant increase in several aspects of PD-related speech disorders is expected, and is anticipated to reflect the underlying neurodegeneration processes.

ETHICS AND DISSEMINATION

The study has been approved by the Ethics Committee of the General University Hospital in Prague, Czech Republic and all the participants will provide written, informed consent prior to their inclusion in the research. The application satisfies the General Data Protection Regulation law requirements of the European Union. The study findings will be published in peer-reviewed journals and presented at international scientific conferences.

An Update on the Measurement of Motor Cerebellar Dysfunction in Multiple Sclerosis

Multiple sclerosis (MS) is a progressive disease that often affects the cerebellum. It is characterised by demyelination, inflammation, and neurodegeneration within the central nervous system. Damage to the cerebellum in MS is associated with increased disability and decreased quality of life. Symptoms include gait and balance problems, motor speech disorder, upper limb dysfunction, and oculomotor difficulties. Monitoring symptoms is crucial for effective management of MS. A combination of clinical, neuroimaging, and task-based measures is generally used to diagnose and monitor MS. This paper reviews the present and new tools used by clinicians and researchers to assess cerebellar impairment in people with MS (pwMS). It also describes recent advances in digital and home-based monitoring for people with MS.

Immediate and long-term effects of speech treatment targets and intensive dosage on Parkinson's disease dysphonia and the speech motor network: Randomized controlled trial

This study compared acoustic and neural changes accompanying two treatments matched for intensive dosage but having two different treatment targets (voice or articulation) to dissociate the effects of treatment target and intensive dosage in speech therapies. Nineteen participants with Parkinsonian dysphonia (11 F) were randomized to three groups: intensive treatment targeting voice (voice group, n = 6), targeting articulation (articulation group, n = 7), or an untreated group (no treatment, n = 6). The severity of dysphonia was assessed by the smoothed cepstral peak prominence (CPPS) and neuronal changes were evaluated by cerebral blood flow (CBF) recorded at baseline, posttreatment, and 7-month follow-up. Only the voice treatment resulted in significant posttreatment improvement in CPPS, which was maintained at 7 months. Following voice treatment, increased activity in left premotor and bilateral auditory cortices was observed at posttreatment, and in the left motor and auditory cortices at 7-month follow-up. Articulation treatment resulted in increased activity in bilateral premotor and left insular cortices that were sustained at a 7-month follow-up. Activation in the auditory cortices and a significant correlation between the CPPS and CBF in motor and auditory cortices was observed only in the voice group. The intensive dosage resulted in long-lasting behavioral and neural effects as the no-treatment group showed a progressive decrease in activity in areas of the speech motor network out to a 7-month follow-up. These results indicate that dysphonia and the speech motor network can be differentially modified by treatment targets, while intensive dosage contributes to long-lasting effects of speech treatments.

Co-Occurrence of Hypernasality and Voice Impairment in Amyotrophic Lateral Sclerosis: Acoustic Quantification

PURPOSE

Hypernasality and atypical voice characteristics are common features of dysarthric speech due to amyotrophic lateral sclerosis (ALS). Existing acoustic measures have been developed to primarily target either hypernasality or voice impairment, and the effects of co-occurring hypernasality-voice problems on these measures are unknown. This report explores (a) the extent to which acoustic measures are affected by concurrent perceptually identified hypernasality and voice impairment due to ALS and (b) candidate acoustic measures of early indicators of hypernasality and voice impairment in the presence of multisystem involvement in individuals with ALS.

METHOD

Two expert listeners rated severity of hypernasality and voice impairment in sentences produced by individuals with ALS (n = 27). The samples were stratified based on perceptual ratings: voice/hypernasality asymptomatic, predominantly hypernasal, predominantly voice impairment, and mixed (co-occurring hypernasality and voice impairment). Groups were compared using established acoustic measures of hypernasality (one-third octave analysis) and voice (cepstral/spectral analysis) impairment.

RESULTS

The one-third octave analysis differentiated all groups; the cepstral peak prominence differentiated all groups except asymptomatic versus mixed, whereas the low-to-high spectral ratio did not differ among groups. Additionally, one-third octave analyses demonstrated promising speech diagnostic potential.

CONCLUSIONS

The results highlight the need to consider the validity of measures in the context of multisubsystem involvement. Our preliminary findings further suggest that the one-third octave analysis may be an optimal approach to quantify hypernasality and voice abnormalities in the presence of multisystem speech impairment. Future evaluation of the diagnostic accuracy of the one-third octave analysis is warranted.

Validation of cepstral peak prominence in assessing early voice changes of Parkinson's disease: Effect of speaking task and ambient noise

Although the cepstral peak prominence (CPP) and its variant, the cepstral peak prominence smooth (CPPS), are considered to be robust acoustic measures for the evaluation of dysphonia, whether they are sensitive to capture early voice changes in Parkinson's disease (PD) has not yet been explored. This study aimed to investigate the voice changes via the CPP measures in the idiopathic rapid eye movement sleep behavior disorder (iRBD), a special case of prodromal neurodegeneration, and recently diagnosed and advanced-stage Parkinson's disease (AS-PD) patients using different speaking tasks across noise-free and noisy environments. The sustained vowel phonation, reading of passages, and monologues of 60 early stage untreated PD, 30 advanced-stage Parkinson's disease, 60 iRBD, and 60 healthy control (HC) participants were evaluated. Significant differences were found between the PD groups and controls in sustained phonation via the CPP (p < 0.05) and CPPS (p < 0.01) and the monologue via the CPP (p < 0.01), although neither the CPP nor CPPS measures were sufficiently sensitive to capture the possible prodromal dysphonia in the iRBD. The quality of the CPP and CPPS measures was influenced substantially by the addition of ambient noise. It was anticipated that the CPP measures might serve as a promising digital biomarker in assessing the dysphonia from the early stages of PD.

Improved Estimation of Parkinsonian Vowel Quality through Acoustic Feature Assimilation

This paper investigated the performance of a number of acoustic measures, both individually and in combination, in predicting the perceived quality of sustained vowels produced by people impaired with Parkinson's disease (PD). Sustained vowel recordings were collected from 51 PD patients before and after the administration of the Levodopa medication. Subjective ratings of the overall vowel quality were garnered using a visual analog scale. These ratings served to benchmark the effectiveness of the acoustic measures. Acoustic predictors of the perceived vowel quality included the harmonics-to-noise ratio (HNR), smoothed cepstral peak prominence (CPP), recurrence period density entropy (RPDE), Gammatone frequency cepstral coefficients (GFCCs), linear prediction (LP) coefficients and their variants, and modulation spectrogram features. Linear regression (LR) and support vector regression (SVR) models were employed to assimilate multiple features. Different feature dimensionality reduction methods were investigated to avoid model overfitting and enhance the prediction capabilities for the test dataset. Results showed that the RPDE measure performed the best among all individual features, while a regression model incorporating a subset of features produced the best overall correlation of 0.80 between the predicted and actual vowel quality ratings. This model may therefore serve as a surrogate for auditory-perceptual assessment of Parkinsonian vowel quality. Furthermore, the model may offer the clinician a tool to predict who may benefit from Levodopa medication in terms of enhanced voice quality.

Dysarthria treatment for Parkinson's disease: one-year follow-up of SPEAK OUT!® with the LOUD Crowd®

INTRODUCTION

SPEAK OUT! with The LOUD Crowd is a standardized speech therapy program typically consisting of 12 one-on-one treatments and ongoing weekly group maintenance sessions for patients with dysarthria due to Parkinson's disease (PD). It is based upon the hypothesis that increased attention to speech, which is a goal-directed motor activity, may compensate for the impairment in automatic sequential motor behaviors often demonstrated in patients with PD. We present results on the 1-year response to treatment.

METHODS

Forty individuals with idiopathic PD received SPEAK OUT! delivered in 12 one-on-one 40-min treatment sessions 3 times per week for four consecutive weeks in addition to ongoing group maintenance sessions called The LOUD Crowd. Evaluations occurred 3 times at baseline, within one and six weeks after completion of the SPEAK OUT! sessions (N = 40) and 1-year later (N = 35). Assessments included mean speech intensity and intonation from reading and monolog, the voice quality acoustic measure called cepstral peak prominence (CPP), and scores on the voice-related quality of life questionnaire.

RESULTS

The significant improvements achieved in all outcome measures from baseline to completion of SPEAK OUT! were maintained 1-year later. Participation throughout the year in regular group maintenance sessions (The LOUD Crowd) was positively correlated with level of improvement at 1 year for all measures except patient perception of voice.

CONCLUSIONS

These long-term data contribute evidence of the effectiveness of this speech therapy program for improving communication for individuals with PD and emphasize the importance of regular and ongoing group sessions to sustain therapeutic gains.

Acoustic Analysis of Phonation in Children With Smith-Magenis Syndrome

Complex simultaneous neuropsychophysiological mechanisms are responsible for the processing of the information to be transmitted and for the neuromotor planning of the articulatory organs involved in speech. The nature of this set of mechanisms is closely linked to the clinical state of the subject. Thus, for example, in populations with neurodevelopmental deficits, these underlying neuropsychophysiological procedures are deficient and determine their phonation. Most of these cases with neurodevelopmental deficits are due to a genetic abnormality, as is the case in the population with Smith–Magenis syndrome (SMS). SMS is associated with neurodevelopmental deficits, intellectual disability, and a cohort of characteristic phenotypic features, including voice quality, which does not seem to be in line with the gender, age, and complexion of the diagnosed subject. The phonatory profile and speech features in this syndrome are dysphonia, high f0, excess vocal muscle stiffness, fluency alterations, numerous syllabic simplifications, phoneme omissions, and unintelligibility of speech. This exploratory study investigates whether the neuromotor deficits in children with SMS adversely affect phonation as compared to typically developing children without neuromotor deficits, which has not been previously determined. The authors compare the phonatory performance of a group of children with SMS (N = 12) with a healthy control group of children (N = 12) matched in age, gender, and grouped into two age ranges. The first group ranges from 5 to 7 years old, and the second group goes from 8 to 12 years old. Group differences were determined for two forms of acoustic analysis performed on repeated recordings of the sustained vowel /a/ F1 and F2 extraction and cepstral peak prominence (CPP). It is expected that the results will enlighten the question of the underlying neuromotor aspects of phonation in SMS population. These findings could provide evidence of the susceptibility of phonation of speech to neuromotor disturbances, regardless of their origin.

Monitoring Parkinson's disease progression based on recorded speech with missing ordinal responses and replicated covariates

Monitoring Parkinson's Disease (PD) progression is an important task to improve the life quality of the affected people. This task can be performed by extracting features from voice recordings and applying specifically designed statistical models, leading to systems that improve the ability of monitoring the progression of PD in an objective, remote, non-invasive, fast, and economically sustainable way. An experiment has been conducted with 36 subjects to study the progression of the PD over 4 years by using the Hoehn and Yahr (HY) scale and features extracted from the phonation of the vowel/a/. The collected dataset had many missing data, which should be addressed jointly with the non-decreasing nature of the disease and the within-subject variability due to the use of replicated features. In order to handle these issues, a Hidden Markov model for longitudinal data was designed and implemented by using a data augmentation scheme based on different latent variables. Markov chain Monte Carlo methods were used to generate from the posterior distribution. The proposed approach has been tested on simulated data, providing good accuracy rates in the context of a multiclass problem. It also has been applied to the real data obtained from the conducted experiment, providing imputed and predicted HY stages compatible with the progression of PD. The conducted experiment and the proposed approach contribute to fill a gap in the scientific literature on experiments and methodologies for tracking PD progression based on acoustic features and the HY scale. This would help to derive an expert system that can be integrated into the protocols of neurology units in hospital centers.

Exploring the Acoustic Perceptual Relationship of Speech in Parkinson's Disease

Purpose Auditory perceptual judgments are commonly used to diagnose dysarthria and assess treatment progress. The purpose of the study was to examine the acoustic underpinnings of perceptual speech abnormalities in individuals with Parkinson's disease (PD). Method Auditory perceptual judgments were obtained from sentences produced by 13 speakers with PD and five healthy older adults. Twenty young listeners rated overall ease of understanding, articulatory precision, voice quality, and prosodic adequacy on a visual analog scale. Acoustic measures associated with the speech subsystems of articulation, phonation, and prosody were obtained, including second formant transitions, articulation rate, cepstral and spectral measures of voice, and pitch variations. Regression analyses were performed to assess the relationships between perceptual judgments and acoustic variables. Results Perceptual impressions of Parkinsonian speech were related to combinations of several acoustic variables. Approximately 36%-49% of the variance in the perceptual ratings were explained by the acoustic measures indicating a modest acoustic perceptual relationship. Conclusions The relationships between perceptual ratings and acoustic signals in Parkinsonian speech are multifactorial and involve a variety of acoustic features simultaneously. The modest acoustic perceptual relationships, however, suggest that future work is needed to further examine the acoustic bases of perceptual judgments in dysarthria.

The Effect of SPEAK OUT! and The LOUD Crowd on Dysarthria Due to Parkinson's Disease

Purpose SPEAK OUT! and The LOUD Crowd is a standardized speech therapy program of 12 individual treatments combined with ongoing weekly group sessions for individuals with dysarthria due to Parkinson's disease (PD). The premise of this program is that individuals with PD must rely on goal-directed basal ganglia-cortical circuits to compensate for deficits in habitual, automatic control. The purpose of this study was to assess the outcome of this therapy program. Method Forty individuals with idiopathic PD received SPEAK OUT! in 12 individual 40-min sessions 3 times per week for 4 consecutive weeks and also participated in The LOUD Crowd. Assessments were conducted 3 times at baseline and then within 1 and 6 weeks after completion of the individual SPEAK OUT! sessions. Twenty-five adults without communication disorders were assessed on the same schedule. Acoustic outcome measures were mean intensity from reading and monologue, the prosody measures of standard deviation of intensity and frequency from reading and monologue, and the voice quality measure of cepstral peak prominence from reading. Patient perception of voice was also assessed with the Voice-Related Quality of Life. Results Posttherapy, mean intensity was greater and variation of frequency was larger in reading and monologue, while variation in intensity was larger in monologue but unchanged in reading. Cepstral peak prominence and Voice-Related Quality of Life scores were significantly higher (improved) after therapy. Conclusion These data contribute to evidence of the effectiveness of this program for hypokinetic dysarthria secondary to idiopathic PD and thus inform clinical practice in the selection among treatment options.

Multiparameter Voice Assessment in Dysphonics: Correlation Between Objective and Perceptual Parameters

BACKGROUND

Perceptual assessment and objective measures of voice provide a quantifiable tool for determining the degree of glottal closure, thus helping to distinguish dysphonic voices from normal voices. The correlation between the perceptual and objective parameters of voice in dysphonic can enable the voice pathologist to be more effective in differentiating the normal voices from dysphonic voices. However, only a few studies have investigated the correlation between these measures.

OBJECTIVE

To document the differences in the perceptual and objective parameters of voice in participants with dysphonia and normal controls and to investigate the correlation between the perceptual and objective parameters of voice among participants with dysphonia.

STUDY DESIGN

This investigation deployed standard group comparison and a retrospective study.

METHODS

Two groups of participants were included in the study. Participants in group 1 were diagnosed as having a voice disorder secondary to organic pathologies and group 2 participants had a clinically normal voice. Phonation samples of all the participants were collected and perceptual analysis was carried out using the GRBAS rating scale. As part of the objective measures, acoustic and cepstral measures were extracted from the phonation samples.

RESULTS

The analysis of the results revealed significant differences in perceptual ratings between the normal (control) and dysphonic groups. The mean values of all the objective measures of voice presented significant differences between participants of both groups. The perceptual ratings of grade, breathiness, and roughness showed better correlations with the cepstral measures than with the time-based acoustic measures.

CONCLUSIONS

Further foraging research on the correlation between perceptual and objective measures of voice in various degrees of dysphonia will improve reliability while discriminating and quantifying hoarse, harsh and breathy voices from modal voices.

Quantitative Assessment of Speech in Cerebellar Ataxia Using Magnitude and Phase Based Cepstrum

The clinical assessment of speech abnormalities in Cerebellar Ataxia (CA) is time-consuming and inconsistent. We have developed an automated objective system to quantify CA severity and thereby facilitate remote monitoring and optimisation of therapeutic interventions. A quantitative acoustic assessment could prove to be a viable biomarker for this purpose. Our study explores the use of phase-based cepstral features extracted from the modified group delay function as a complement to the features obtained from the magnitude cepstrum. We selected a combination of 15 acoustic measurements using RELIEF feature selection algorithm during the feature optimisation process. These features were used to segregate ataxic speakers from normal speakers (controls) and objectively assess them based on their severity. The effectiveness of our study has been experimentally evaluated through a clinical study involving 42 patients diagnosed with CA and 23 age-matched controls. A radial basis function kernel based support vector machine (SVM) classifier achieved a classification accuracy of 84.6% in CA-Control discrimination [area under the ROC curve (AUC) of 0.97] and 74% in the modified 3-level CA severity estimation (AUC of 0.90) deduced from the clinical ratings. The strong classification ability of selected features and the SVM model supports this scheme's suitability for monitoring CA related speech motor abnormalities.

Towards the identification of Idiopathic Parkinson's Disease from the speech. New articulatory kinetic biomarkers

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson's Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson's Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting.

Modal and non-modal voice quality classification using acoustic and electroglottographic features

The goal of this study was to investigate the performance of different feature types for voice quality classification using multiple classifiers. The study compared the COVAREP feature set; which included glottal source features, frequency warped cepstrum and harmonic model features; against the mel-frequency cepstral coefficients (MFCCs) computed from the acoustic voice signal, acoustic-based glottal inverse filtered (GIF) waveform, and electroglottographic (EGG) waveform. Our hypothesis was that MFCCs can capture the perceived voice quality from either of these three voice signals. Experiments were carried out on recordings from 28 participants with normal vocal status who were prompted to sustain vowels with modal and non-modal voice qualities. Recordings were rated by an expert listener using the Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V), and the ratings were transformed into a dichotomous label (presence or absence) for the prompted voice qualities of modal voice, breathiness, strain, and roughness. The classification was done using support vector machines, random forests, deep neural networks and Gaussian mixture model classifiers, which were built as speaker independent using a leave-one-speaker-out strategy. The best classification accuracy of 79.97% was achieved for the full COVAREP set. The harmonic model features were the best performing subset, with 78.47% accuracy, and the static+dynamic MFCCs scored at 74.52%. A closer analysis showed that MFCC and dynamic MFCC features were able to classify modal, breathy, and strained voice quality dimensions from the acoustic and GIF waveforms. Reduced classification performance was exhibited by the EGG waveform.

Modulation Spectra Morphological Parameters: A New Method to Assess Voice Pathologies according to the GRBAS Scale

Disordered voices are frequently assessed by speech pathologists using perceptual evaluations. This might lead to problems caused by the subjective nature of the process and due to the influence of external factors which compromise the quality of the assessment. In order to increase the reliability of the evaluations, the design of automatic evaluation systems is desirable. With that in mind, this paper presents an automatic system which assesses the Grade and Roughness level of the speech according to the GRBAS perceptual scale. Two parameterization methods are used: one based on the classic Mel-Frequency Cepstral Coefficients, which has already been used successfully in previous works, and other derived from modulation spectra. For the latter, a new group of parameters has been proposed, named Modulation Spectra Morphological Parameters: MSC, DRB, LMR, MSH, MSW, CIL, PALA, and RALA. In methodology, PCA and LDA are employed to reduce the dimensionality of feature space, and GMM classifiers to evaluate the ability of the proposed features on distinguishing the different levels. Efficiencies of 81.6% and 84.7% are obtained for Grade and Roughness, respectively, using modulation spectra parameters, while MFCCs performed 80.5% and 77.7%. The obtained results suggest the usefulness of the proposed Modulation Spectra Morphological Parameters for automatic evaluation of Grade and Roughness in the speech.