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- Speech and voice response to a Levodopa challenge in late-stage Parkinson’s diseasePublication . Fabbri, Margherita; Guimarães, Isabel; Cardoso, Rita; Coelho, Miguel; Guedes, Leonor Correia; Rosa, Mário M; Godinho, Catarina; Abreu, Daisy; Gonçalves, Nilza; Antonini, Angelo; Ferreira, JoaquimBackground: Parkinson’s disease (PD) patients are affected by hypokinetic dysarthria, characterized by hypophonia and dysprosody, which worsens with disease progression. Levodopa’s (l-dopa) effect on quality of speech is inconclusive; no data are currently available for late-stage PD (LSPD). Objective: To assess the modifications of speech and voice in LSPD following an acute l-dopa challenge. Method: LSPD patients [Schwab and England score <50/Hoehn and Yahr stage >3 (MED ON)] performed several vocal tasks before and after an acute l-dopa challenge. The following was assessed: respiratory support for speech, voice quality, stability and variability, speech rate, and motor performance (MDS-UPDRS-III). All voice samples were recorded and analyzed by a speech and language therapist blinded to patients’ therapeutic condition using Praat 5.1 software. results: 24/27 (14 men) LSPD patients succeeded in performing voice tasks. Median age and disease duration of patients were 79 [IQR: 71.5–81.7] and 14.5 [IQR: 11–15.7] years, respectively. In MED OFF, respiratory breath support and pitch break time of LSPD patients were worse than the normative values of non-parkinsonian. A correlation was found between disease duration and voice quality (R = 0.51; p = 0.013) and speech rate (R = −0.55; p = 0.008). l-Dopa significantly improved MDS-UPDRS-III score (20%), with no effect on speech as assessed by clinical rating scales and automated analysis. conclusion: Speech is severely affected in LSPD. Although l-dopa had some effect on motor performance, including axial signs, speech and voice did not improve. The applicability and efficacy of non-pharmacological treatment for speech impairment should be considered for speech disorder management in PD.
- Hierarchical classification and system combination for automatically identifying physiological and neuromuscular laryngeal pathologiesPublication . Cordeiro, Hugo; Fonseca, José; Guimarães, Isabel; Meneses, CarlosObjectives. Speech signal processing techniques have provided several contributions to pathologic voice identification, in which healthy and unhealthy voice samples are evaluated. A less common approach is to identify laryngeal pathologies, for which the use of a noninvasive method for pathologic voice identification is an important step forward for preliminary diagnosis. In this study, a hierarchical classifier and a combination of systems are used to improve the accuracy of a three-class identification system (healthy, physiological larynx pathologies, and neuromuscular larynx pathologies). Method. Three main subject classes were considered: subjects with physiological larynx pathologies (vocal fold nodules and edemas: 59 samples), subjects with neuromuscular larynx pathologies (unilateral vocal fold paralysis: 59 samples), and healthy subjects (36 samples). The variables used in this study were a speech task (sustained vowel /a/ or continuous reading speech), features with or without perceptual information, and features with or without direct information about formants evaluated using single classifiers.Ahierarchical classification system was designed based on this information. Results. The resulting system combines an analysis of continuous speech by way of the commonly used sustained vowel /a/ to obtain spectral and perceptual speech features. It achieved an accuracy of 84.4%, which represents an improvement of approximately 9% compared with the stand-alone approach. For pathologic voice identification, the accuracy obtained was 98.7%, and the identification accuracy for the two pathology classes was 81.3%. Conclusions. Hierarchical classification and system combination create significant benefits and introduce a modular approach to the classification of larynx pathologies.
- Undernutrition in institutionalized elderly patients with neurological diseases: comparison between different diagnostic criteriaPublication . Miranda, Diana; Cardoso, Rita; Gomes, R; Guimarães, Isabel; Abreu, Daisy; Godinho, C; Pereira, P; Domingos, Josefa; Pona, N; Ferreira, JoaquimObjectives: To determine and compare the frequency of undernutrition in institutionalized elderly patients with neurological diseases at admission using different nutritional assessment tools. Design: Cross-sectional observational study. Setting: One long-term care institution specialized in neurodegenerative diseases. Participants: 92 Elderly people (aged ≥ 65 years) with at least one neurological condition. Measurements: Mini Nutritional Assessment (MNA), body mass index (BMI), mid-arm (MAC) and calf circumferences (CC) were used for nutritional status assessment. Presence and severity of dysphagia, polypharmacy and feeding difficulties were also assessed. Results: According to MNA, 77.1% of the participants were undernourished at admission. BMI identified 46.8%, MAC identified 44.6% and CC identified 22.8% of undernourished participants. Undernutrition was more frequent in Alzheimer’s disease, stroke and dementia syndromes. 63% had dysphagia for at least one food consistence and most of these patients were malnourished. MNA revealed best concordance with BMI and MAC than with CC. BMI and feeding difficulties were the major risk factors for undernutrition. Conclusion: Undernutrition prevalence in institutionalized elderly with neurological diseases at admission is high. Nutritional assessment tools revealed low concordance between them.
- Sibilant consonants classification with deep neural networksPublication . Anjos, Ivo; Marques, Nuno; Grilo, Ana Margarida; Guimarães, Isabel; Magalhães, João; Cavaco, SofiaAbstract. Many children su ering from speech sound disorders cannot pronounce the sibilant consonants correctly. We have developed a serious game that is controlled by the children's voices in real time and that allows children to practice the European Portuguese sibilant consonants. For this, the game uses a sibilant consonant classi er. Since the game does not require any type of adult supervision, children can practice the production of these sounds more often, which may lead to faster improvements of their speech. Recently, the use of deep neural networks has given considerable improvements in classi cation for a variety of use cases, from image classication to speech and language processing. Here we propose to use deep convolutional neural networks to classify sibilant phonemes of European Portuguese in our serious game for speech and language therapy. We compared the performance of several diferent arti cial neural networks that used Mel frequency cepstral coefcients or log Mel lterbanks. Our best deep learning model achieves classi cation scores of 95:48% using a 2D convolutional model with log Mel lterbanks as input features.
- Robust phoneme recognition for a speech therapy environmentPublication . Grossinho, André; Guimarães, Isabel; Magalhães, João; Cavaco, SofiaTraditional speech therapy approaches for speech sound disorders have a lot of advantages to gain from computerbased therapy systems. With speech recognition techniques the motivation elements of these systems can be automated in order to get an interactive environment that motivates the therapy attendee towards better performances. Here we propose a robust phoneme recognition solution for an interactive environment for speech therapy. We compare the results of hierarchical and flat classification, with naive Bayes, support vector machines andkernel density estimation on linear predictive coding coefficients and Mel-frequency cepstral coefficients.
- 3D facial video retrieval and management for decision support in speech and language therapyPublication . Carrapiço, Ricardo; Guimarães, Isabel; Grilo, Ana Margarida; Cavaco, Sofia; Magalhães, João3D video is introducing great changes in many health related areas. The realism of such information provides health professionals with strong evidence analysis tools to facilitate clinical decision processes. Speech and language therapy aims to help subjects in correcting several disorders. The assessment of the patient by the speech and language therapist (SLT), requires several visual and audio analysis procedures that can interfere with the patient's production of speech. In this context, the main contribution of this paper is a 3D video system to improve health information management processes in speech and language therapy. The 3D video retrieval and management system supports multimodal health records and provides the SLTs with tools to support their work in many ways: (i) it allows SLTs to easily maintain a database of patients' orofacial and speech exercises; (ii) supports three-dimensional orofacial measurement and analysis in a non-intrusive way; and (iii) search patient speech-exercises by similar facial characteristics, using facial image analysis techniques. The second contribution is a dataset with 3D videos of patients performing orofacial speech exercises. The whole system was evaluated successfully in a user study involving 22 SLTs. The user study illustrated the importance of the retrieval by similar orofacial speech exercise.
- Montreal children´s hospital feeding scale: tradução e contributo para a validação em português europeuPublication . Lopes, Ana Cláudia; Guimarães, Isabel; Afonso, CatarinaObjetivo: Adaptar e contribuir para a validação do Montreal Children´s Hospital Feeding Scale, em português europeu, que permite identificar a opinião dos cuidadores de crianças, entre os seis meses e os seis anos de idade com perturbações da alimentação. Métodos: O estudo consistiu nas seguintes fases: i) adaptação cultural e linguística através da técnica de tradução e retrotradução do instrumento para o português europeu seguido da análise através do processo de Delphi. Esta versão foi submetida a um pré-teste com cinco cuidadores de crianças e realizada a revisão final; ii) contributo para a validação. A escala foi aplicada a cuidadores de 30 crianças com desenvolvimento alimentar típico e a 10 crianças com perturbações da alimentação. A validação foi obtida utilizando a análise fatorial, o alfa de Cronbach como coeficiente de consistência interna e o Kaiser-Meyer-Olkin (KMO) para o construto. Resultados: A análise da escala, pelos peritos, resultou numa boa aceitabilidade do conteúdo dos seus itens (71%) e excelente aceitação em relação à pertinência dos mesmos (100%). Existem diferenças estatisticamente significativas (p <0.05) entre os grupos estudados para o valor total e para cinco das 14 perguntas. O instrumento apresenta uma forte consistência interna para a totalidade dos itens que a constituem (alfa=0.898). A análise fatorial explica 73% da variância total apenas com três componentes da escala. Conclusão: A versão portuguesa desta escala tem aceitabilidade linguística e cultural, mostrou precisão na distinção entre a opinião de cuidadores, contribuindo assim para a sua validação preliminar na população portuguesa mas a sua aplicabilidade deve resultar apenas após o aprimoramento da sua precisão.
- Automatic detection of Parkinson’s disease: an experimental analysis of common speech production tasks used for diagnosisPublication . Pompili, Anna; Abad, Alberto; Romano, Paolo; Martins, Isabel P; Cardoso, Rita; Santos, Helena; Carvalho, Joana; Guimarães, Isabel; Ferreira, JoaquimParkinson’s disease (PD) is the second most common neurodegenerative disorder of mid-to-late life after Alzheimer’s disease. During the progression of the disease, most individuals with PD report impairments in speech due to deficits in phonation, articulation, prosody, and fluency. In the literature, several studies perform the automatic classification of speech of people with PD considering various types of acoustic information extracted from different speech tasks. Nevertheless, it is unclear which tasks are more important for an automatic classification of the disease. In this work, we compare the discriminant capabilities of eight verbal tasks designed to capture the major symptoms affecting speech. To this end, we introduce a new database of Portuguese speakers consisting of 65 healthy control and 75 PD subjects. For each task, an automatic classifier is built using feature sets and modeling approaches in compliance with the current state of the art. Experimental results permit to identify reading aloud prosodic sentences and story-telling tasks as the most useful for the automatic detection of PD.
- A serious mobile game with visual feedback for training sibilant consonantsPublication . Anjos, Ivo; Grilo, Ana Margarida; Ascensão, Mariana; Guimarães, Isabel; Magalhães, João; Cavaco, SofiaAbstract. The distortion of sibilant sounds is a common type of speech sound disorder (SSD) in Portuguese speaking children. Speech and language pathologists (SLP) frequently use the isolated sibilants exercise to assess and treat this type of speech errors. While technological solutions like serious games can help SLPs to motivate the children on doing the exercises repeatedly, there is a lack of such games for this specic exercise. Another important aspect is that given the usual small number of therapy sessions per week, children are not improving at their maximum rate, which is only achieved by more intensive therapy. We propose a serious game for mobile platforms that allows children to practice their isolated sibilants exercises at home to correct sibilant distortions. This will allow children to practice their exercises more frequently, which can lead to faster improvements. The game, which uses an automatic speech recognition (ASR) system to classify the child sibilant productions, is controlled by the child's voice in real time and gives immediate visual feedback to the child about her sibilant productions. In order to keep the computation on the mobile platform as simple as possible, the game has a client-server architecture, in which the external server runs the ASR system. We trained it using raw Mel frequency cepstral coe cients, and we achieved very good results with an accuracy test score of above 91% using support vector machines.
- Psychosocial impact of Parkinson’s disease-associated dysarthria: cross-cultural adaptation and validation of the Dysarthria Impact Profile into european portuguesePublication . Cardoso, Rita; Guimarães, Isabel; Santos, Helena; Loureiro, Rita; Domingos, Josefa; Abreu, Daisy; Gonçalves, Nilza; Pinto, Serge; Ferreira, JoaquimAim: The present study sought to make a cross-cultural adaptation of the Dysarthria Impact Profile (DIP) for European Portuguese (EP) and validate it for use in Parkinson’s disease (PD) patients. Methods: The cross-cultural adaptation was carried out in accordance with the guidelines. The EP version of the DIP was administered to 80 people with PD, and 30 sex- and age-matched control participants. Psychometric properties, acceptability, feasibility reliability (internal consistency and intrarater agreement) and validity (construct, convergent and known-groups validity) were assessed using other assessment tools (motor disability and impairment, and voice impact). Results: Overall, the EP-DIP final version has the same conceptual meaning, semantics, idiomatic and score equivalences as the original version. Statistical analyses showed adequate feasibility (missing data <5%), good acceptability (ceiling or floor effects <15%; high requests of assistance to complete the questionnaire), satisfactory internal consistency (Cronbach’s α = 0.9), weak-to-moderate intrarater reliability, good construct validity, strong convergent validity (with the Voice Handicap Index; Spearman’s P = −0.8) and good known-groups validity (between those with PD and control participants). Conclusions: The EP-DIP version displays the salient features of a valid patient-based assessment tool used to measure the psychosocial impact of slight-to-mild dysarthria in people with PD.