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Speech articulation is produced by the movements of muscles in the larynx, pharynx, mouth and face. Therefore speech shows acoustic features as formants which are directly related with neuromotor actions of these muscles. The first two formants are strongly related with jaw and tongue muscular activity. Speech can be used as a simple and ubiquitous signal, easy to record and process, either locally or on e-Health platforms. This fact may open a wide set of applications in the study of functional grading and monitoring neurodegenerative diseases. A relevant question, in this sense, is how far speech correlates and neuromotor actions are related. This preliminary study is intended to find answers to this question by using surface electromyographic recordings on the masseter and the acoustic kinematics related with the first formant. It is shown in the study that relevant correlations can be found among the surface electromyographic activity (dynamic muscle behavior) and the positions and first derivatives of the first formant (kinematic variables related to vertical velocity and acceleration of the joint jaw and tongue biomechanical system). As an application example, it is shown that the probability density function associated to these kinematic variables is more sensitive than classical features as Vowel Space Area (VSA) or Formant Centralization Ratio (FCR) in characterizing neuromotor degeneration in Parkinson's Disease. [ABSTRACT FROM AUTHOR]

Neurodegenerative pathologies as Parkinson's Disease (PD) show important distortions in speech, affecting fluency, prosody, articulation and phonation. Classically, measurements based on articulation gestures altering formant positions, as the Vocal Space Area (VSA) or the Formant Centralization Ratio (FCR) have been proposed to measure speech distortion, but these markers are based mainly on static positions of sustained vowels. The present study introduces a measurement based on the mutual information distance among probability density functions of kinematic correlates derived from formant dynamics. An absolute kinematic velocity associated to the position of the jaw and tongue articulation gestures is estimated and modeled statistically. The distribution of this feature may differentiate PD patients from normative speakers during sustained vowel emission. The study is based on a limited database of 53 male PD patients, contrasted to a very selected and stable set of eight normative speakers. In this sense, distances based on Kullback–Leibler divergence seem to be sensitive to PD articulation instability. Correlation studies show statistically relevant relationship between information contents based on articulation instability to certain motor and nonmotor clinical scores, such as freezing of gait, or sleep disorders. Remarkably, one of the statistically relevant correlations point out to the time interval passed since the first diagnostic. These results stress the need of defining scoring scales specifically designed for speech disability estimation and monitoring methodologies in degenerative diseases of neuromotor origin. [ABSTRACT FROM AUTHOR]

Patients suffering from Parkinson's disease (PD) may be successfully treated pharmacologically and surgically to preserve and even improve their life quality and health conditions. Although the progress of the disease cannot be stopped, at least mitigation of the most handicapping symptoms can be achieved. But both pharmacological and surgical treatments require the adequate monitoring of the disease stage of progress and the effects of treatment. Several techniques have been proposed for PD evolution monitoring, ranging from subjective auto-evaluation by questionnaires, or from gait and handwriting examination by specialists. Nevertheless, these techniques present certain difficulties, which make frequent evaluation impractical. On the other hand, it is known that speech acoustic analysis may estimate indicators of patient's conditions, and can be implemented for a frequent evaluation protocol; and under minimal help, it can be carried out at distance using communication technologies. The acoustic analysis, may be based on mel-cepstral coefficients, distortion features as jitter, shimmer , harmonic-to-noise contents, or pitch-perturbation estimates, among others. Phonation biomechanical parameter and tremor estimates are also good markers of PD. The present work proposes a combination of biomechanical features to predict PD progress using Bayesian likelihood estimation. This methodology proves to be very sensitive and allows a three-band based comparison: pre-treatment versus post-treatment in reference to a control subject or a normative population. Results from a study are presented, including eight patients recorded on a 4-week separation interval, meanwhile they were treated with medication, physical exercising and speech therapy. The conclusions show that certain distortion, biomechanical and tremor features are of special relevance to monitor PD phonation, and that they can be used as evolution markers. [ABSTRACT FROM AUTHOR]

Speech production in patients suffering of dementias of Alzheimer׳s type is known to experience noticeable changes with respect to normative speakers. Classically this kind of speech has been described as presenting altered prosody, rhythmic pace, anomy, or impaired semantics. Phonation, conceived as the production of voice in voiced speech fragments remains as an unexplored field. The aim of the present paper is to open a preliminary study presenting biomechanical estimates from phonation produced by two patients (male and female) suffering Alzheimer׳s Disease (AD), contrasted on two controls of both genders (CS: control speakers). A vocal fold biomechanical model is inverted to facilitate estimates of the vocal fold stiffness to analyze significant segments of phonated speech as long vowels and fillers. The estimates of both the AD patients and CS subjects are contrasted on a database of phonation features from a normative speaker population of both genders, as well as in paired tests contrasting AD and CS subjects. Results show the possibility of establishing significant discrimination between AD and CS when using f 0, as well as vocal fold body stiffness, although this last feature seems to be more relevant and shows larger statistical significance. [ABSTRACT FROM AUTHOR]

Neuromotor Degenerative Diseases (NDD) affecting mainly sub-thalamic and extra-pyramidal neuromotor structures leave significant marks in speech and phonation correlates. These may be used in the characterization, detection, grading and monitoring diseases and their progress in a non-invasive way. Considering that speech and phonation recording can be carried out using handy and low-cost instrumentation, speech and phonation correlates may be quite adequate candidates to define specific NDD biomarkers for disease progress monitoring protocols. The purpose of the paper is to present the fundamentals of speech articulation biomechanical modeling from the level of signal processing to neuromotor activity inference. This backward pathway involves several inverse problems, which are addressed separately. Results from study cases relevant in Amyotrophic Lateral Sclerosis are presented and discussed. The conclusions of the research show that several correlates may be reliably established, and that monitoring disease state and progress may rely on some biomechanical correlates informing on jaw and tongue neuromotor residual activity. Possible applications of the methodology to other neurodegenerative diseases are also discussed. [ABSTRACT FROM AUTHOR]

Parkinson's disease (PD) is a neurodegenerative condition with constantly increasing prevalence rates, affecting strongly life quality in terms of neuromotor and cognitive performance. PD symptoms include voice and speech alterations, known as hypokinetic dysarthria (HD). Unstable phonation is one of the manifestations of HD. Repetitive transcranial magnetic stimulation (rTMS) is a rehabilitative treatment thathas been shown to improve some motor and non-motor symptoms of persons with PD (PwP). This study analyzed the phonation functional behavior of 18 participants (13 males, 5 females) with PD diagnosis before (one pre-stimulus) and after (four post-stimulus) evaluation sessions of rTMS treatment, to assess the extent of changes in their phonation stability. Participants were randomized 1:1 to receive either rTMS or sham stimulation. Voice recordings of a sustained vowel [a:] taken immediately before and after the treatment, and at follow-up evaluation sessions (immediately after, at six, ten, and fourteen weeks after the baseline assessment) were processed by inverse filtering to estimate a biomechanical correlate of vocal fold tension. This estimate was further band-pass filtered into EEG-related frequency bands. Log-likelihood ratios (LLRs) between pre- and post-stimulus amplitude distributions of each frequency band showed significant differences in five cases actively stimulated. Seven cases submitted to the sham protocol did not show relevant improvements in phonation instability. Conversely, four active cases did not show phonation improvements, whereas two sham cases did. The study provides early preliminary insights into the capability of phonation quality assessment by monitoring neuromechanical activity from acoustic signals in frequency bands aligned with EEG ones. [ABSTRACT FROM AUTHOR]

Abstract: Vowels are important clues supporting speech perception. Nevertheless in Computational Perception the definition of vowels is a very complex and elusive issue. The purpose of the present paper is to give a possible definition under the perceptual point of view. A vowel could be defined as an assignment of an acoustic–phonetic pattern to a specific categorical representation space. This assignment would be competitively instantiated in the cortical structures, depending on the specific phonological framework of the listener's language. An experimental framework is designed to test this definition on a Neuromorphic Speech Processing Architecture. Results from experiments to test reference patterns in Spanish, and possible extension to other languages with a larger repertoire of categories are presented and discussed. [Copyright &y& Elsevier]

Abstract: Speech and voice technologies are experiencing a profound review as new paradigms are sought to overcome some specific problems which cannot be completely solved by classical approaches. Neuromorphic Speech Processing is an emerging area in which research is turning the face to understand the natural neural processing of speech by the Human Auditory System in order to capture the basic mechanisms solving difficult tasks in an efficient way. In the present paper a further step ahead is presented in the approach to mimic basic neural speech processing by simple neuromorphic units standing on previous work to show how formant dynamics – and henceforth consonantal features – can be detected by using a general neuromorphic unit which can mimic the functionality of certain neurons found in the upper auditory pathways. Using these simple building blocks a General Speech Processing Architecture can be synthesized as a layered structure. Results from different simulation stages are provided as well as a discussion on implementation details. Conclusions and future work are oriented to describe the functionality to be covered in the next research steps. [Copyright &y& Elsevier]

Abstract: The Glottal Source is an important component of voice as it can be considered as the excitation signal to the voice apparatus. The use of the Glottal Source for pathology detection or the biometric characterization of the speaker are important objectives in the acoustic study of the voice nowadays. Through the present work a biometric signature based on the speaker’s power spectral density of the Glottal Source is presented. It may be shown that this spectral density is related to the vocal fold cover biomechanics, and from literature it is well-known that certain speaker’s features as gender, age or pathologic condition leave changes in it. The paper describes the methodology to estimate the biometric signature from the power spectral density of the mucosal wave correlate, which after normalization can be used in pathology detection experiments. Linear Discriminant Analysis is used to confront the detection capability of the parameters defined on this glottal signature among themselves and compared to classical perturbation parameters. A database of 100 normal and 100 pathologic subjects equally balanced in gender and age is used to derive the best parameter cocktails for pathology detection and quantification purposes to validate this methodology in voice evaluation tests. In a study case presented to illustrate the detection capability of the methodology exposed a control subset of 24+24 subjects is used to determine a subject’s voice condition in a pre- and post-surgical evaluation. Possible applications of the study can be found in pathology detection and grading and in rehabilitation assessment after treatment. [Copyright &y& Elsevier]

Abstract: Nowadays applications demand a comprehensive view of voice and speech perception to build more complex and competitive procedures amenable of extracting as much knowledge from sound-based human communication as possible. Many knowledge-extraction tasks from speech and voice may share signal treatment procedures which can be devised under the point of view of bio-inspiration. The present paper examines a hierarchy of sound processing functionalities at the auditory and perceptual levels on the Auditory Neural pathways which can be translated into bio-inspired speech-processing techniques, their fundamental characteristics being analyzed in relation with current tendencies in cognitive audio processing. The pathways linking the peripheral auditory system (cochlear complex) with the brain cortex are briefly examined, with special attention to the study of neuronal structures showing specific capabilities under the point of view of formant analysis and the build-up of a semantic hierarchy from the time-frequency structure of speech to explore their capability of conveying semantics to speech processing and understanding from the minimal acoustic clues with elementary meaning or “sematoms”. The replication of known biological functionality by algorithmic methods through bio-inspiration is a secondary aim of the research. Examples extracted from speech processing tasks in the domain of acoustic-phonetics are presented. These may find applicability in speech recognition, speaker''s characterization and biometry, emotion detection, and others related. [Copyright &y& Elsevier]

Voice diseases have been increasing dramatically in recent times due mainly to unhealthy social habits and voice abuse. These diseases must be diagnosed and treated at an early stage, especially in the case of larynx cancer. It is widely recognized that vocal and voice diseases do not necessarily cause changes in voice quality as perceived by a listener. Acoustic analysis could be a useful tool to diagnose this type of disease. Preliminary research has shown that the detection of voice alterations can be carried out by means of Gaussian mixture models and short-term mel cepstral parameters complemented by frame energy together with first and second derivatives. This paper, using the F-Ratio and Fisher's discriminant ratio, will demonstrate that the detection of voice impairments can be performed using both mel cesptral vectors and their first derivative, ignoring the second derivative. [ABSTRACT FROM AUTHOR]

There is a growing consensus that hybrid approaches are necessary for successful speaker characterization in Forensic Speaker Comparison (FSC); hence this study explores the forensic potential of voice features combining source and filter characteristics. The former relate to the action of the vocal folds while the latter reflect the geometry of the speaker's vocal tract. This set of features have been extracted from pause fillers, which are long enough for robust feature estimation while spontaneous enough to be extracted from voice samples in real forensic casework. Speaker similarity was measured using standardized Euclidean Distances (ED) between pairs of speakers: 54 different-speaker (DS) comparisons, 54 same-speaker (SS) comparisons and 12 comparisons between monozygotic twins (MZ). Results revealed that the differences between DS and SS comparisons were significant in both high quality and telephone-filtered recordings, with no false rejections and limited false acceptances; this finding suggests that this set of voice features is highly speaker-dependent and therefore forensically useful. Mean ED for MZ pairs lies between the average ED for SS comparisons and DS comparisons, as expected according to the literature on twin voices. Specific cases of MZ speakers with very high ED (i.e. strong dissimilarity) are discussed in the context of sociophonetic and twin studies. A preliminary simplification of the Vocal Profile Analysis (VPA) Scheme is proposed, which enables the quantification of voice quality features in the perceptual assessment of speaker similarity, and allows for the calculation of perceptual-acoustic correlations. The adequacy of z-score normalization for this study is also discussed, as well as the relevance of heat maps for detecting the so-called phantoms in recent approaches to the biometric menagerie. [ABSTRACT FROM AUTHOR]

This paper presents an acoustic-to-articulatory (AtoA) mapping method for tracking the movement of the critical articulators on fricative utterances. The proposed approach applies a vocal tract length normalization process. Subsequently, those acoustic time-frequency features better related to movement of articulators from the statistical perspective are used for AtoA mapping. We test this method on the MOCHA-TIMIT database, which contains signals from an electromagnetic articulograph system. The proposed features were tested on an AtoA mapping system based on Gaussian mixture models, where Pearson correlation coefficient is used to measure the goodness of estimates. Correlation value between the estimates and reference signals shows that subject-independent AtoA mapping with proposed approach yields comparable results to subject-dependent AtoA mapping. [ABSTRACT FROM AUTHOR]

This paper presents an acoustic-to-articulatory (AtoA) mapping method for tracking the movement of the critical articulators on fricative utterances. The proposed approach applies a vocal tract length normalization process. Subsequently, those acoustic time-frequency features better related to movement of articulators from the statistical perspective are used for AtoA mapping. We test this method on the MOCHA-TIMIT database, which contains signals from an electromagnetic articulograph system. The proposed features were tested on an AtoA mapping system based on Gaussian mixture models, where Pearson correlation coefficient is used to measure the goodness of estimates. Correlation value between the estimates and reference signals shows that subject-independent AtoA mapping with proposed approach yields comparable results to subject-dependent AtoA mapping. [ABSTRACT FROM AUTHOR]

Artificial intelligence and all its supporting tools, e.g. machine and deep learning in computational intelligence-based systems, are rebuilding our society (economy, education, life-style, etc.) and promising a new era for the social welfare state. In this paper we summarize recent advances in data science and artificial intelligence within the interplay between natural and artificial computation. A review of recent works published in the latter field and the state the art are summarized in a comprehensive and self-contained way to provide a baseline framework for the international community in artificial intelligence. Moreover, this paper aims to provide a complete analysis and some relevant discussions of the current trends and insights within several theoretical and application fields covered in the essay, from theoretical models in artificial intelligence and machine learning to the most prospective applications in robotics, neuroscience, brain computer interfaces, medicine and society, in general. [ABSTRACT FROM AUTHOR]

Speech is controlled by axial neuromotor systems, therefore, it is highly sensitive to the effects of neurodegenerative illnesses such as Parkinson's Disease (PD). Patients suffering from PD present important alterations in speech, which are manifested in phonation, articulation, prosody, and fluency. These alterations may be evaluated using statistical methods on features obtained from glottal, spectral, cepstral, or fractal descriptions of speech. This work introduces an evaluation paradigm based on Information Theory (IT) to differentiate the effects of PD and aging on glottal amplitude distributions. The study is conducted on a database including 48 PD patients (24 males, 24 females), 48 age-matched healthy controls (HC, 24 males, 24 females), and 48 mid-age normative subjects (NS, 24 males, 24 females). It may be concluded from the study that Hierarchical Clustering (HiCl) methods produce a clear separation between the phonation of PD patients from NS subjects (accuracy of 89.6% for both male and female subsets), but the separation between PD patients and HC subjects is less efficient (accuracy of 75.0% for the male subset and 70.8% for the female subset). Conversely, using feature selection and Support Vector Machine (SVM) classification, the differentiation between PD and HC is substantially improved (accuracy of 94.8% for the male subset and 92.8% for the female subset). This improvement was mainly boosted by feature selection, at a cost of information and generalization losses. The results point to the possibility that speech deterioration may affect HC phonation with aging, reducing its difference to PD phonation. [ABSTRACT FROM AUTHOR]

Background. Paralysis of one vocal fold leads to glottal gap and vocal fold insufficiency that has significant impact upon a patient’s quality of life. Fillers have been tested to perform intracordal injections, but they do not provide perdurable results. Early data suggest that enriching fat grafts with adipose-derived regenerative cells (ADRCs) promote angiogenesis and modulate the immune response, improving graft survival. The aim of this study is to propose ADRC-enriched adipose tissue grafts as effective filler for the paralyzed vocal fold to use it for functional reconstruction of the glottal gap. Method. This is the first phase I-IIA clinical trial (phase I/IIA clinical trial, unicentric, randomized, controlled, and two parallel groups), to evaluate the safety of a new therapy with ADRC-enriched fat grafting (ADRC: group I) for laryngoplasty after unilateral vocal fold paralysis. Control group patients received centrifuged autologous fat (CAF: group II) grafts. Overall mean age is 52.49 ± 16.60 years. Group I (ADRC): 7 patients (3 males and 4 females), 52.28 ± 20.95 year. Group II (CAF): 7 patients (3 males and 4 females), 52.71 ± 12.59 year. Results. VHI-10 test showed that preoperative mean score was 24.21 ± 8.28. Postoperative mean score was 6.71 ± 6.75. Preoperative result in group I was 21.14 ± 3.58 and postoperative result was 3.14 ± 3.53. Preoperative result for group II was 27.29 ± 10.66. Postoperative score in group II was 10.29 ± 7.52. Wilcoxon and the Student t-tests showed that the patient’s self-perception of posttreatment improvement is larger when ADRCs are used. Comparing pre- and posttreatment voice quality analysis, group I showed a p=0.053. Group II showed a p=0.007. There would be no significant differentiation between pre- and posttreatment results. This is true for group II and limited for group I. Conclusions. This prospective trial demonstrates the safety and efficacy of the treatment of glottal gap defects utilizing ADRC-enriched fat grafts. This trial is registered with NCT02904824. [ABSTRACT FROM AUTHOR]

Most of the parameters proposed for the characterization of the emotion in speech concentrate their attention on phonetic and prosodic features. Our approach goes beyond trying to relate the biometrical signature of voice with a possible neural activity that might generate alterations in voice production. A total of 68, acoustical, glottal and biomechanical parameters were extracted from neutral and stressed speeches. The importance of the parameters was evaluated using t-test, entropy, Receiver Operator Characteristic (ROC) and Wilcoxon methods and support vector machines algorithms for classification. The emotion under study is the stress produced when a speaker has to defend an idea opposite to his/her thoughts or feelings, and this stress is compared to self-consistent speech. The results show tremor in the vocal folds to be the most relevant feature. [ABSTRACT FROM AUTHOR]

Abstract: The present paper describes a new algorithm to calculate the watershed transform through rain simulation of greyscale digital images by means of pixel arrowing. The efficiency of this method is based on limiting the necessary neighbouring operations to compute the transform to the outmost, and in the total number of scannings performed over the whole image. The experiments demonstrate that the proposed algorithm is able to significantly reduce the running time of the fastest known algorithm without involving any loss of efficiency. [Copyright &y& Elsevier]

Abstract: A PC-based integrated aid tool has been developed for the analysis and screening of pathological voices. With it the user can simultaneously record speech, electroglottographic (EGG), and videoendoscopic signals, and synchronously edit them to select the most significant segments. These multimedia data are stored on a relational database, together with a patient''s personal information, anamnesis, diagnosis, visits, explorations and any other comment the specialist may wish to include. The speech and EGG waveforms are analysed by means of temporal representations and the quantitative measurements of parameters such as spectrograms, frequency and amplitude perturbation measurements, harmonic energy, noise, etc. are calculated using digital signal processing techniques, giving an idea of the degree of hoarseness and quality of the voice register. Within this framework, the system uses a standard protocol to evaluate and build complete databases of voice disorders. The target users of this system are speech and language therapists and ear nose and throat (ENT) clinicians. The application can be easily configured to cover the needs of both groups of professionals. The software has a user-friendly Windows style interface. The PC should be equipped with standard sound and video capture cards. Signals are captured using common transducers: a microphone, an electroglottograph and a fiberscope or telelaryngoscope. The clinical usefulness of the system is addressed in a comprehensive evaluation section. [Copyright &y& Elsevier]