Acoustic Parameters Of Speech Research Articles

Acoustic Speech Analysis in Alzheimer’s Disease: A Systematic Review and Meta-Analysis

BackgroundThe potential of biomarkers in the detection of Alzheimer’s disease (AD) is prominent. Acoustics may be useful in this context but the evaluation and weighting for specific acoustic parameters on continuous speech is missing. This meta-analysis aimed to explore the significance of acoustic parameters from acoustic speech analysis on continuous speech, as a diagnostic tool for clinical AD.MethodsApplying PRISMA protocol, a comprehensive search was done in MEDLINE, Scopus, Web of Science, and CENTRAL, from 1960 to January 2024. Cross-sectional studies comparing the acoustic speech analysis between AD patients and healthy controls (HC), were taken into account. The bias risk of the included studies were examined via JBI checklist. Using Review Manager v.5.4.1, the mean differences of acoustic speech parameters among AD and HC were weighted, and the pooled analysis and the heterogeneity statistics were conducted.ResultsIn total, 1112 records (without duplicates) were obtained, and 11 papers with 7 acoustic parameters were included for this study, and 8 from 11 studies were identified with a low level of bias. Five from 7 acoustic parameters revealed significant differences among the two groups (p-values ≤ 0.01), in which for all rate-related and interruption-related acoustic parameters were the most prominent and less in temporal-related acoustic parameters.ConclusionsAlthough a small number of acoustic parameters on continuous speech could be evaluated in the detection of clinical AD, the greatest potential of acoustic biomarkers for AD appeared to exist in two of three categories. Further contributions of high-quality studies are needed to support evidence for acoustics as biomarkers for AD.

Comparison of Acoustic Parameters of Voice and Speech According to Vowel Type and Suicidal Risk in Adolescents

Globally, suicide prevention and understanding suicidal behavior represent significant health challenges. The predictive potential of voice, speech, and language appears as a promising solution to the difficulty in assessment. ObjectiveTo analyze variations in acoustic parameters in voice and speech based on vowel types according to different levels of suicidal risk among adolescents in a text reading task. MethodologyCross-sectional analytical design using non-probabilistic sampling. Our sample comprised 98 adolescents aged 14 to 19, undergoing voice acoustic assessment, along with suicidal ideation determination through the Okasha Suicidality Scale and Beck Depression Inventory. Acoustic analysis of recordings was conducted using Praat for phonetic research, Python program, Focusrite interface, and microphone to register voice and speech acoustic parameters such as Fundamental Frequency, Jitter, and Formants. Subsequently, data from adolescents with and without suicidal risk were compared. ResultsSignificant differences were observed between suicidal and non-suicidal adolescents in several acoustic aspects, especially in females in fundamental frequency (F0), signal-to-noise ratio (HNRdB) and temporal variability measured by jitter and standard deviation. In mens, differences were found in F0 and HNRdB (p < 0.05). ConclusionThis study demonstrated statistically significant variations in various voice acoustic parameters among adolescents with and without suicidal risk. These findings underscore the potential relevance of voice and speech as markers for suicidal risk.

Speech Acoustic Parameters for Predicting Presbyphagia: A Preliminary Study in the Elderly Shanghainese Population

PurposeAge is a high-risk factor for dysphagia. Speech and swallowing share the same anatomical and neurophysiological basis. Their functions are closely related; hence, speech assessment can predict the risk of dysphagia. This study aimed to investigate the factors influencing presbyphagia in a normal elderly Shanghainese population by analyzing speech acoustic parameters. MethodsRelevant speech acoustic parameters were compared between 15 people with dysphagia and 15 without dysphagia. After extracting sensitive speech acoustic parameters related to swallowing, changes in sensitive parameters were compared at different ages to analyze the relevant factors influencing presbyphagia in the normal elderly population. ResultsEight speech acoustic parameters related to swallowing, including maximum phonation time (MPT), max F0, /ʔʌ/Jitter, /ʔʌ/L-DDK, /hʌ/L-DDK, /pataka/DDK, F1/a/, and vowel space area, were extracted after comparing the relevant data between the two groups. Analyzing the changes in each of these parameters between different age groups (age 18–39, 40–64, and 65 and above), we discovered that three speech acoustic parameters, including MPT, /hʌ/L-DDK, and /pataka/DDK, had statistical differences, with a decreasing trend in their mean values with increasing age. ConclusionsThe elderly group had significantly lower MPT, /hʌ/L-DDK, and /pataka/DDK than the young and middle-aged groups. We hypothesized that reduced respiratory support and control, decreased range of mouth movements and coordination, closed control of the vocal cords, and inadequate airflow control in vocal cord abduction are risk factors for presbyphagia in the elderly Shanghainese population.

Levodopa may modulate specific speech impairment in Parkinson's disease: an fMRI study.

Hypokinetic dysarthria (HD) is a difficult-to-treat symptom affecting quality of life in patients with Parkinson's disease (PD). Levodopa may partially alleviate some symptoms of HD in PD, but the neural correlates of these effects are not fully understood. The aim of our study was to identify neural mechanisms by which levodopa affects articulation and prosody in patients with PD. Altogether 20 PD patients participated in a task fMRI study (overt sentence reading). Using a single dose of levodopa after an overnight withdrawal of dopaminergic medication, levodopa-induced BOLD signal changes within the articulatory pathway (in regions of interest; ROIs) were studied. We also correlated levodopa-induced BOLD signal changes with the changes in acoustic parameters of speech. We observed no significant changes in acoustic parameters due to acute levodopa administration. After levodopa administration as compared to the OFF dopaminergic condition, patients showed task-induced BOLD signal decreases in the left ventral thalamus (p = 0.0033). The changes in thalamic activation were associated with changes in pitch variation (R = 0.67, p = 0.006), while the changes in caudate nucleus activation were related to changes in the second formant variability which evaluates precise articulation (R = 0.70, p = 0.003). The results are in line with the notion that levodopa does not have a major impact on HD in PD, but it may induce neural changes within the basal ganglia circuitries that are related to changes in speech prosody and articulation.

Harnessing acoustic speech parameters to decipher amyloid status in individuals with mild cognitive impairment.

Alzheimer's disease (AD) is a neurodegenerative condition characterized by a gradual decline in cognitive functions. Currently, there are no effective treatments for AD, underscoring the importance of identifying individuals in the preclinical stages of mild cognitive impairment (MCI) to enable early interventions. Among the neuropathological events associated with the onset of the disease is the accumulation of amyloid protein in the brain, which correlates with decreased levels of Aβ42 peptide in the cerebrospinal fluid (CSF). Consequently, the development of non-invasive, low-cost, and easy-to-administer proxies for detecting Aβ42 positivity in CSF becomes particularly valuable. A promising approach to achieve this is spontaneous speech analysis, which combined with machine learning (ML) techniques, has proven highly useful in AD. In this study, we examined the relationship between amyloid status in CSF and acoustic features derived from the description of the Cookie Theft picture in MCI patients from a memory clinic. The cohort consisted of fifty-two patients with MCI (mean age 73 years, 65% female, and 57% positive amyloid status). Eighty-eight acoustic parameters were extracted from voice recordings using the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS), and several ML models were used to classify the amyloid status. Furthermore, interpretability techniques were employed to examine the influence of input variables on the determination of amyloid-positive status. The best model, based on acoustic variables, achieved an accuracy of 75% with an area under the curve (AUC) of 0.79 in the prediction of amyloid status evaluated by bootstrapping and Leave-One-Out Cross Validation (LOOCV), outperforming conventional neuropsychological tests (AUC = 0.66). Our results showed that the automated analysis of voice recordings derived from spontaneous speech tests offers valuable insights into AD biomarkers during the preclinical stages. These findings introduce novel possibilities for the use of digital biomarkers to identify subjects at high risk of developing AD.

Body Perception From Connected Speech: Speaker Height Discrimination from Natural Sentences and Sine-Wave Replicas with and without Pitch.

In addition to language, the human voice carries information about the physical characteristics of speakers, including their body size (height and weight). The fundamental speaking frequency, perceived as voice pitch, and the formant frequencies, or resonators of the vocal tract, are the acoustic speech parameters that have been most intensely studied for perceiving a speaker's body size. In this study, we created sine-wave (SW) replicas of connected speech (sentences) uttered by 20 male and 20 female speakers, consisting of three time-varying sinusoidal waves matching the frequency pattern of the first three formants of each sentence. These stimuli only provide information about the formant frequencies of a speech signal. We also created a new experimental condition by adding a sinusoidal replica of the voice pitch of each sentence. Results obtained from a binary discrimination task revealed that (a) our SW replicas provided sufficient useful information to accurately judge the speakers' body height at an above chance level; (b) adding the sinusoidal replica about the voice pitch did not significantly increase accuracy; and (c) stimuli from female speakers were more informative for body height detection and allowed higher perceptual accuracy, due to a stronger correlation between formant frequencies and actual body height than stimuli from male speakers.

Acoustic speech parameter relationships with voice disorders and phrase differences

While acoustic speech analysis is non-invasive, the utility has been mixed due to the range of voice types. For vocal health practitioners to efficiently and quickly assess and document voice changes, knowing which voice parameter would be sensitive to vocal change is crucial. Using a database of 296 individual voices including 8 voice pathology types and typical voice samples, the sensitivity of a range of acoustic speech parameters to differentiate common voice pathology types was investigated. Both traditional and contemporary acoustic speech metrics were estimated for the samples using a custom MATLAB script and PRAAT (e.g., jitter, shimmer HNR, CPPS, Alpha ratio, PPE). Analysis then evaluate the predictability value of the metrics to discriminate pathology type. From the pool of parameters, 11 were able to identify pathological voices from normal controls and several of the parameters were more sensitive to some pathology. For example, CPPs and jitter values could discriminate neuropathological voices whereas HNR and Shimmer cold discriminate muscle-based pathologies. These results indicate how the sensitivity of acoustic speech metrics to the voice pathology types can allow for the identification of individual metrics (or combinations of metrics) which could be used to track changes in vocal health.

Speech and Nonspeech Parameters in the Clinical Assessment of Dysarthria: A Dimensional Analysis.

Nonspeech (or paraspeech) parameters are widely used in clinical assessment of speech impairment in persons with dysarthria (PWD). Virtually every standard clinical instrument used in dysarthria diagnostics includes nonspeech parameters, often in considerable numbers. While theoretical considerations have challenged the validity of these measures as markers of speech impairment, only a few studies have directly examined their relationship to speech parameters on a broader scale. This study was designed to investigate how nonspeech parameters commonly used in clinical dysarthria assessment relate to speech characteristics of dysarthria in individuals with movement disorders. Maximum syllable repetition rates, accuracies, and rates of isolated and repetitive nonspeech oral-facial movements and maximum phonation times were compared with auditory-perceptual and acoustic speech parameters. Overall, 23 diagnostic parameters were assessed in a sample of 130 patients with movement disorders of six etiologies. Each variable was standardized for its distribution and for age and sex effects in 130 neurotypical speakers. Exploratory Graph Analysis (EGA) and Confirmatory Factor Analysis (CFA) were used to examine the factor structure underlying the diagnostic parameters. In the first analysis, we tested the hypothesis that nonspeech parameters combine with speech parameters within diagnostic dimensions representing domain-general motor control principles. In a second analysis, we tested the more specific hypotheses that diagnostic parameters split along effector (lip vs. tongue) or functional (speed vs. accuracy) rather than task boundaries. Our findings contradict the view that nonspeech parameters currently used in dysarthria diagnostics are congruent with diagnostic measures of speech characteristics in PWD.

How’s my kitty? Acoustic parameters of cat-directed speech in human-cat interactions

In Western cultures, humans tend to use a specific kind of speech when talking to their pets, characterised, from an acoustical point of view, by elevated pitch and greater pitch modulation. Pet-directed speech (PDS), which has been mainly studied in dogs, shares some acoustic features with infant-directed speech (IDS), used when talking to young children. The purpose of this study was to test the hypothesis that adult humans also modify characteristics of their voice when talking to a cat. We compared acoustic parameters of speech directed to cats (CDS) and speech directed to adult humans (ADS). In a first experiment, we compared ADS and CDS utterances of male and female participants, addressing cats through video recordings, under controlled laboratory conditions. Both men and women used a higher pitch (mean fundamental frequency, or mean F0) in CDS vs. ADS. The second experiment was conducted under conditions allowing direct cat-human interactions, in a cohort of women. Once again, mean F0 was significantly higher in CDS vs. ADS. Overall, these data confirm our hypothesis that humans change the way they speak when addressing a cat, mainly by increasing the pitch of their voice. Further research is needed to fully investigate specificities of this speech.

Оптимизация логопедической работы по диагностике гипокинетической дизартрии у лиц с болезнью Паркинсона

The aim of the study was to objectify speech and voice disorders in persons with Parkinson’s disease depending on gender, age, form of the disease and degree of speech disorders severity. The article experimentally confirmed the objective indices of acoustic parameters of speech influencing rehabilitation potential of persons with Parkinson’s disease. The scientific novelty of the study lies in the fact that for the first time a pedagogical model for diagnosing hypokinetic dysarthria in patients of the Russian population depending on the stage of the disease, available in outpatient and inpatient settings, was presented. As a result, it has been proved that the speech deficit testifies to the complex organization of the pathological process in which not only acoustic characteristics of the voice, but also the energy base of speech in neurodegeneration inevitably suffer.

Cerebellar Continuous Theta Burst Stimulation for Aphasia Rehabilitation: Study Protocol for a Randomized Controlled Trial.

BackgroundLanguage recovery is limited in moderate to severe post-stroke aphasia patients. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising tool in improving language dysfunctions caused by post-stroke aphasia, but the treatment outcome is as yet mixed. Considerable evidence has demonstrated the essential involvement of the cerebellum in a variety of language functions, suggesting that it may be a potential stimulation target of TMS for the treatment of post-stroke aphasia. Theta burst stimulation (TBS) is a specific pattern of rTMS with shorter stimulation times and better therapeutic effects. The effect of continuous TBS (cTBS) on the cerebellum in patients with aphasia with chronic stroke needs further exploration.MethodsIn this randomized, sham-controlled clinical trial, patients (n = 40) with chronic post-stroke aphasia received 10 sessions of real cTBS (n = 20) or sham cTBS (n = 20) over the right cerebellar Crus I+ a 30-min speech-language therapy. The Western Aphasia Battery (WAB) serves as the primary measure of the treatment outcome. The secondary outcome measures include the Boston Diagnostic Aphasia Examination, Boston Naming Test and speech acoustic parameters. Resting-state fMRI data were also obtained to examine treatment-induced changes in functional connectivity of the cerebro-cerebellar network. These outcome measures are assessed before, immediately after, and 12 weeks after cerebellar cTBS intervention.DiscussionThis protocol holds promise that cerebellar cTBS is a potential strategy to improve language functions in chronic post-stroke aphasia. The resting-state fMRI may explore the neural mechanism underlying the aphasia rehabilitation with cerebellar cTBS.

Acoustic characteristics of voice and speech in Arabic-speaking stuttering children

BackgroundUsing different methodologies, several researchers have reported certain acoustical and physiological differences between fluent utterances of stutterers and normally fluent speakers. The aim of this study was to determine acoustic characteristics of voice and speech in Arabic-speaking stuttering children in comparison to normal children and correlate these characteristics with stuttering severity. A sample of 80 Arabic-speaking Egyptian children (including 40 typically developing children and 40 stuttering children) in the age range 5–8 years were subjected to acoustic analysis of voice and speech using the Praat software.ResultsThe stuttering children showed significantly higher values of jitter and shimmer in prolonged /a/ vowel sample, as compared to the normal group. This may reflect the subtle differences in laryngeal functioning or in the complex interaction among the laryngeal, respiratory, and the vocal tract systems in stuttering children. Both jitter and shimmer of prolonged /a/ vowel demonstrated significant positive moderate correlation with stuttering severity as assessed by SSI3. F0 was significantly higher in females than in males, both in normal and stuttering children.ConclusionsThe present study revealed significant differences in the acoustic parameters of voice and speech between Arabic-speaking stuttering children and normal children. Some of these acoustic parameters were significantly correlated with stuttering severity. Acoustic analysis can be used as simple, quick, and cheap tool for assessment of stuttering in children and might be a valuable addition to the diagnostic set for assessment of stuttering severity.

On the relation between the similarity of the acoustic distribution patterns of vowels and the language closeness

Based on the “Unified Platform for Speech Acoustic Parameters of Chinese Minority Languages”, this paper calculates and compares the acoustic distribution of vowels in Mongolian, Uyghur, and Ewenki and proposes a hypothesis that the relevance between the similarity of the acoustic distribution patterns of vowels and language closeness does exist. It indicates that the acoustic pattern implies clues of closeness and relevance among the three languages. The results demonstrate that, in terms of vowels, Mongolian and Ewenki are closely related. Both those languages and the Uyghur language are distant relatives, with only typological similarity. This paper provides a new perspective for the research methodology of language kindred. It proves that the comparison of acoustic pattern is of significance in studies in linguistics, linguistic typology, historical comparative linguistics, and anthropology.

An Investigational Approach for Vowels of the Salar Language Based on a Database of Speech Acoustic Parameters

According to relevant specifications, this article divides, marks, and extracts the acquired speech signals of the Salar language, and establishes the speech acoustic parameter database of the Salar language. Then, the vowels of the Salar language are analyzed and studied by using the parameter database. The vowel bitmap (average value at the beginning of words), the vowel bitmap (average value at the abdomen of words), the vowel bitmap (average value at the ending of words), and the vowel bitmap (average value) are obtained. Through the vowel bitmaps, we can observe the vowel in different positions of the word, the overall appearance of an obtuse triangle. The high vowel [i], [o], and low vowel [a] occupy three vertices, respectively. Among the three lines, [i] to [o] are the longest, [i] to [a] are the second longest, and [a] to [o] are the shortest. The lines between [a] to [o] and [a] and [i] are asymmetric. Combining with the vowel bitmap, the vowels were discretized, and the second formant (F2) frequency parameter was used as the coordinate of the X axis, and the first formant (F1) frequency was used as the coordinate of the Y axis to draw the region where the vowel was located, and then the vowel pattern was formed. These studies provide basic data and parameters for the future development of modern phonetics such as the database of Sarah language speech, speech recognition, and speech synthesis. It also provides the basic parameters of speech acoustics for the rare minority acoustic research work of the national language project.

Acoustic speech markers for schizophrenia-spectrum disorders: a diagnostic and symptom-recognition tool.

Clinicians routinely use impressions of speech as an element of mental status examination. In schizophrenia-spectrum disorders, descriptions of speech are used to assess the severity of psychotic symptoms. In the current study, we assessed the diagnostic value of acoustic speech parameters in schizophrenia-spectrum disorders, as well as its value in recognizing positive and negative symptoms. Speech was obtained from 142 patients with a schizophrenia-spectrum disorder and 142 matched controls during a semi-structured interview on neutral topics. Patients were categorized as having predominantly positive or negative symptoms using the Positive and Negative Syndrome Scale (PANSS). Acoustic parameters were extracted with OpenSMILE, employing the extended Geneva Acoustic Minimalistic Parameter Set, which includes standardized analyses of pitch (F0), speech quality and pauses. Speech parameters were fed into a random forest algorithm with leave-ten-out cross-validation to assess their value for a schizophrenia-spectrum diagnosis, and PANSS subtype recognition. The machine-learning speech classifier attained an accuracy of 86.2% in classifying patients with a schizophrenia-spectrum disorder and controls on speech parameters alone. Patients with predominantly positive v. negative symptoms could be classified with an accuracy of 74.2%. Our results show that automatically extracted speech parameters can be used to accurately classify patients with a schizophrenia-spectrum disorder and healthy controls, as well as differentiate between patients with predominantly positive v. negatives symptoms. Thus, the field of speech technology has provided a standardized, powerful tool that has high potential for clinical applications in diagnosis and differentiation, given its ease of comparison and replication across samples.

Pronunciation correction of students in music classroom based on computer voice simulation

In order to improve the pronunciation effect of students in music classroom, based on computer speech simulation technology, this paper combines speech recognition technology and speech feature extraction technology to summarize the various acoustic parameters of speech and the perception of the information by the human ear, and establishes the physical model and digital model of the speech signal. Through the analysis of voice signals, this paper selects several acoustic parameters that can reflect individual characteristics, and studies the methods of their extraction and adjustment to construct a pronunciation correction system for music students based on computer voice simulation. Finally, this paper designs experiments to verify the performance of the system constructed in this paper. The research results show that the system constructed in this paper has certain practical effects and enriches the expressive power of machine speech. The process of synthesizing speech is simple, and the practical effect is good, which meets the current music teaching needs.

Dopaminergic Treatment Effects on Dysarthric Speech: Acoustic Analysis in a Cohort of Patients With Advanced Parkinson's Disease.

Importance: The effects of dopaminergic treatment on speech in patients with Parkinson's disease (PD) are often mixed and unclear. The aim of this study was to better elucidate those discrepancies.Methods: Full retrospective data from advanced PD patients before and after an acute levodopa challenge were collected. Acoustic analysis of spontaneous monologue and sustained phonation including several quantitative parameters [i.e., maximum phonation time (MPT); shimmer local dB] as well as the Unified Parkinson's Disease Rating Scale (UPDRS) (total scores, subscores, and items) and the Clinical Dyskinesia Rating Scale (CDRS) were performed in both the defined-OFF and -ON conditions. The primary outcome was the changes of speech parameters after levodopa intake. Secondary outcomes included the analysis of possible correlations of motor features and levodopa-induced dyskinesia (LID) with acoustic speech parameters. Statistical analysis included paired t-test between the ON and OFF data (calculated separately for male and female subgroups) and Pearson correlation between speech and motor data.Results: In 50 PD patients (male: 32; female: 18), levodopa significantly increased the MPT of sustained phonation in female patients (p < 0.01). In the OFF-state, the UPDRS part-III speech item negatively correlated with MPT (p = 0.02), whereas in the ON-state, it correlated positively with the shimmer local dB (p = 0.01), an expression of poorer voice quality. The total CDRS score and axial subscores strongly correlated with the ON-state shimmer local dB (p = 0.01 and p < 0.01, respectively).Conclusions: Our findings emphasize that levodopa has a poor effect on speech acoustic parameters. The intensity and location of LID negatively influenced speech quality.

Highlighting interlanguage phoneme differences based on similarity matrices and convolutional neural network.

The goal of this research is to find a way of highlighting the acoustic differences between consonant phonemes of the Polish and Lithuanian languages. For this purpose, similarity matrices are employed based on speech acoustic parameters combined with a convolutional neural network (CNN). In the first experiment, we compare the effectiveness of the similarity matrices applied to discerning acoustic differences between consonant phonemes of the Polish and Lithuanian languages. The similarity matrices built on both an extensive set of parameters and a reduced set after removing high-correlated parameters are used. The results show that higher accuracy is obtained by the similarity matrices without discarding high-correlated parameters. In the second experiment, the averaged accuracies of the similarity matrices obtained are compared with the results provided by spectrograms combined with CNN, as well as the results of the vectors containing acoustic parameters and two baseline classifiers, namely k-nearest neighbors and support vector machine. The performance of the similarity matrix approach demonstrates its superiority over the methods used for comparison.

Association between suicidal ideation and acoustic parameters of university students’ voice and speech: a pilot study

Purpose At a worldwide level, suicide is a public health problem that, despite displaying downward trends in several areas of the world, in many countries these rates have increased. One of the elements that contributes to its prevention is an early and dynamic evaluation. Due to this, the objective is to determine the association between acoustic parameters of voice and speech (F0, F1, F2, F3, dB, and Jitter) and suicidal ideation arousal amongst some university students from the city of Temuco, Chile. Methods Attending to this issue, a cross-sectional design study was conducted through a non-probabilistic sampling of sixty 18- and 19-year-old adolescents from the city of Temuco, that went through an acoustic evaluation of their voice and speech after taking a test to determine suicidal ideation. Afterwards, data were analyzed through IBM SPSS version 23.0 software (IBM SPSS Statistics, Armonk, NY), by means of exploratory, descriptive, and inferential statistics taking the variable’s levels of measurements and the types of distributions into account. Results The results point out that 30% of the adolescents, from both genders, displayed suicidal ideation. Taking into account the acoustic results of their voice, it is possible to recognize that the fundamental frequency (F0), the formants (F1, F2), and Jitter, are the ones that majorly link to the presence of suicidal ideation, both in women and men (p < .05). The characteristics that describe F3 were only linked to the presence of suicidal ideation in men (p < .05). Conclusions It is concluded that the acoustic parameters of voice and speech differ in adolescents with suicidal behavior, opening the possibility of representing a useful tool in the diagnosis of suicide.

Diagnosis of Obstructive Sleep Apnea Using Speech Signals From Awake Subjects

Obstructive sleep apnea (OSA) is a sleep disorder in which pharyngeal collapse during sleep causes complete (apnea) or partial (hypopnea) airway obstruction. OSA is common and can have severe implications, but often remains undiagnosed. The most widely used objective measure of OSA severity is the number of obstructive events per hour of sleep, known as the apnea-hypopnea index (AHI). This study reports an innovative system to identify OSA subjects while they are awake, not asleep, using speech signal processing techniques. The assumption is that OSA affects the acoustic parameters of speech because it is associated with anatomical and functional abnormalities of the upper airway. The system associates three different sub-systems based on features extracted from breathing segments within continuous speech signals, information acquired from sustained vowels using a convolutional neural network, and inherent information in continuous speech signals using a recurrent neural network. Each of these sub-systems provided an AHI estimation and were combined with age and body mass index (BMI) to produce a composite system that estimates AHI using a linear regression. The sample was composed of 398 subjects (men and women). The performance of each sub-system was examined separately, in addition to the composite system. As expected, the composite AHI estimation yielded the superior results, with a Pearson correlation coefficient of 0.61 between the estimated and diagnosed AHI. To distinguish between OSA and non-OSA subjects, a classification decision was made using an AHI threshold of 15 events per hour. The system achieved an average accuracy of 77.14%, a sensitivity of 75%, and a specificity of 79%.