Speech Assessment for the Classification of Hypokinetic Dysthria in Parkinson Disease

The aim of this thesis is to investigate computerized voice assessment methods to classify between the normal and Dysarthric speech signals. In this proposed system, computerized assessment methods equipped with signal processing and artificial intelligence techniques have been introduced. The sentences used for the measurement of inter-stress intervals (ISI) were read by each subject. These sentences were computed for comparisons between normal and impaired voice. Band pass filter has been used for the preprocessing of speech samples. Speech segmentation is performed using signal energy and spectral centroid to separate voiced and unvoiced areas in speech signal. Acoustic features are extracted from the LPC model and speech segments from each audio signal to find the anomalies. The speech features which have been assessed for classification are Energy Entropy, Zero crossing rate (ZCR), Spectral-Centroid, Mean Fundamental-Frequency (Meanf0), Jitter (RAP), Jitter (PPQ), and Shimmer (APQ). Naïve Bayes (NB) has been used for speech classification. For speech test-1 and test-2, 72% and 80% accuracies of classification between healthy and impaired speech samples have been achieved respectively using the NB. For speech test-3, 64% correct classification is achieved using the NB. The results direct the possibility of speech impairment classification in PD patients based on the clinical rating scale.

Assessment of PD Speech Anomalies @ Home

Background: Voice processing in real-time is challenging. A drawback of previous work for Hypokinetic Dysarthria (HKD) recognition is the requirement of controlled settings in a laboratory environment. A personal digital assistant (PDA) has been developed for home assessment of PD patients. The PDA offers sound processing capabilities, which allow for developing a module for recognition and quantification HKD. Objective: To compose an algorithm for assessment of PD speech severity in the home environment based on a review synthesis. Methods: A two-tier review methodology is utilized. The first tier focuses on real-time problems in speech detection. In the second tier, acoustics features that are robust to medication changes in Levodopa-responsive patients are investigated for HKD recognition. Keywords such as Hypokinetic Dysarthria , and Speech recognition in real time were used in the search engines. IEEE explorer produced the most useful search hits as compared to Google Scholar, ELIN, EBRARY, PubMed and LIBRIS. Results: Vowel and consonant formants are the most relevant acoustic parameters to reflect PD medication changes. Since relevant speech segments (consonants and vowels) contains minority of speech energy, intelligibility can be improved by amplifying the voice signal using amplitude compression. Pause detection and peak to average power rate calculations for voice segmentation produce rich voice features in real time. Enhancements in voice segmentation can be done by inducing Zero-Crossing rate (ZCR). Consonants have high ZCR whereas vowels have low ZCR. Wavelet transform is found promising for voice analysis since it quantizes non-stationary voice signals over time-series using scale and translation parameters. In this way voice intelligibility in the waveforms can be analyzed in each time frame. Conclusions: This review evaluated HKD recognition algorithms to develop a tool for PD speech home-assessment using modern mobile technology. An algorithm that tackles realtime constraints in HKD recognition based on the review synthesis is proposed. We suggest that speech features may be further processed using wavelet transforms and used with a neural network for detection and quantification of speech anomalies related to PD. Based on this model, patients' speech can be automatically categorized according to UPDRS speech ratings.

What aspects of rehabilitation provision contribute to self-reported met needs for rehabilitation one year after stroke - amount, place, operator or timing?

BACKGROUND AND OBJECTIVE: To a large extent, people who have suffered a stroke report unmet needs for rehabilitation. The purpose of this study was to explore aspects of rehabilitation provision that potentially contribute to self-reported met needs for rehabilitation 12 months after stroke with consideration also to severity of stroke. METHODS: The participants (n = 173) received care at the stroke units at the Karolinska University Hospital, Sweden. Using a questionnaire, the dependent variable, self-reported met needs for rehabilitation, was collected at 12 months after stroke. The independent variables were four aspects of rehabilitation provision based on data retrieved from registers and structured according to four aspects: amount of rehabilitation, service level (day care rehabilitation, primary care rehabilitation and home-based rehabilitation), operator level (physiotherapist, occupational therapist, speech therapist) and time after stroke onset. Multivariate logistic regression analyses regarding the aspects of rehabilitation were performed for the participants who were divided into three groups based on stroke severity at onset. RESULTS: Participants with moderate/severe stroke who had seen a physiotherapist at least once during each of the 1st, 2nd and 3rd-4th quarters of the first year (OR 8.36, CI 1.40-49.88 P = 0.020) were more likely to report met rehabilitation needs. CONCLUSION: For people with moderate/severe stroke, continuity in rehabilitation (preferably physiotherapy) during the first year after stroke seems to be associated with self-reported met needs for rehabilitation.

Dialectal Speech in Literature and Translation : Bachelor Degree Thesis in English Linguistics

This essay studies how dialectal speech is reflected in written literature and how this phenomenon functions in translation. With this purpose in mind, Styron's Sophie's Choice and Twain's The Adventures of Huckleberry Finn are analysed using samples of non-standard orthography which have been applied in order to reflect the dialect, or accent, of certain characters. In the same way, Lundgren's Swedish translation of Sophie's Choice and Ferres and Rolfe's Spanish version of The Adventures of Huckleberry Finn are analysed. The method consists of linguistically analysing a few text samples from each novel, establishing how dialect is represented through non-standard orthography, and thereafter, comparing the same samples with their translation into another language in order to establish whether dialectal features are visible also in the translated novels. It is concluded that non-standard orthography is applied in the novels in order to represent each possible linguistic level, including pronunciation, morphosyntax, and vocabulary. Furthermore, it is concluded that while Lundgren's translation intends to orthographically represent dialectal speech on most occasions where the original does so, Ferres and Rolfe's translation pays no attention to dialectology. The discussion following the data analysis establishes some possible reasons for the exclusion of dialectal features in the Spanish translation considered here. Finally, the reason for which this study contributes to the study of dialectology is declared.

Children's recall of words spoken in their first and second language : Effects of Signal-to-Noise Ratio and Reverberation Time

Speech perception runs smoothly and automatically when there is silence in the background, but when the speech signal is degraded by background noise or by reverberation, effortful cognitive processing is needed to compensate for the signal distortion. Previous research has typically investigated the effects of signal-to-noise ratio (SNR) and reverberation time in isolation, whilst few have looked at their interaction. In this study, we probed how reverberation time and SNR influence recall of words presented in participants' first- (L1) and second-language (L2). A total of 72 children (10 years old) participated in this study. The to-be-recalled wordlists were played back with two different reverberation times (0.3 and 1.2 s) crossed with two different SNRs (+3 dBA and +12 dBA). Children recalled fewer words when the spoken words were presented in L2 in comparison with recall of spoken words presented in L1. Words that were presented with a high SNR (+12 dBA) improved recall compared to a low SNR (+3 dBA). Reverberation time interacted with SNR to the effect that at +12 dB the shorter reverberation time improved recall, but at +3 dB it impaired recall. The effects of the physical sound variables (SNR and reverberation time) did not interact with language. © 2016 Hurtig, Keus van de Poll, Pekkola, Hygge, Ljung and Sörqvist.

Residual signal auto-correlation to evaluate speech in Parkinson's disease patients

Objective: To evaluate the maximum residual signal auto-correlation also known as pitch amplitude (PA) values in patients with Parkinson's disease (PD) patients. Method. The signals of 21 Parkinson's patients were compared with 15 healthy individuals, divided according age and gender. Results: Statistical difference was seen between groups for PA, 0.39 for controls and 0.25 for PD. Normal value threshold was set as 0.3; (p <= 0.001). In the Parkinson's group 80.77%, and in the control group only 12.28%, had a PA < 0.3 demonstrating an association between these variables. The dispersion diagram for age and PA for PD individuals showed p=0.01 and r=0.54. There was no significant difference in relation to gender and PA between groups: Conclusion: the significant differences in pitch's amplitude between PD patients and healthy individuals demonstrate the methods specificity.-The results showed the need of prospective controlled studies,to improve the use and indications of residual signal auto-correlation to evaluate speech in PD patients.

Discrepancies between abstracts presented at international association for dental research annual sessions from 2004 to 2005 and full-text publication

Purpose. The purpose of this study was to evaluate the discrepancies between abstracts presented at the IADR meeting (2004-2005) and their full-text publication. Material and Methods. Abstracts from the Prosthodontic Section of IADR meeting were obtained. The following information was collected: abstract title, number of authors, study design, statistical analysis, outcome, and funding source. PubMed was used to identify the full-text publication of the abstracts. The discrepancies between the abstract and the full-text publication were examined, categorized as major and minor discrepancies, and quantified. The data were collected and analyzed using descriptive analysis. Frequency and percentage of major and minor discrepancies were calculated. Results. A total of 109 (95.6%) articles showed changes from their abstracts. Seventy-four (65.0%) and 105 (92.0%) publications had at least one major and one minor discrepancies, respectively. Minor discrepancies were more prevalent (92.0%) than major discrepancies (65.0%). The most common minor discrepancy was observed in the title (80.7%), and most common major discrepancies were seen in results (48.2%). Conclusion. Minor discrepancies were more prevalent than major discrepancies. The data presented in this study may be useful to establish a more comprehensive structured abstract requirement for future meetings. © 2012 Soni Prasad et al.

Enmiendas al texto de las atribuciones y reglamento de la CEPAL = Amendments to the text of the terms of reference and rules of procedure of ECLAC = Amendements au texte du mandat et règlement intérieur de la CEPALC

Somete a consideracion de las delegaciones las enmiendas propuestas al texto de las atribuciones de CEPAL, documento E/CN.12/850/Rev.1.

A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition

In this letter, a speech recognition algorithm based on the least-squares method is presented. Particularly, the intention is to exemplify how such a traditional numerical technique can be applied to solve a signal processing problem that is usually treated by using more elaborated formulations.

Speech-language therapy for treatment of dysphagia and dysphonia in systemic granulomatous diseases: granulomatous diseases: dysphagia and dysphonia treatments

The granulomatous lesions are frequently founded in infectious diseases and can involve the larynx and pharynx and can cause varying degrees of dysphonia and dysphagia. There is still no systematic review that analyzes effectiveness of speech therapy in systemic granulomatous diseases. Research strategy: A systematic review was performed according to Cochrane guideline considering the inclusion of RCTs and quasi-RCTs about the effectiveness of speech-language therapy to treat dysphagia and dysphonia symptoms in systemic granulomatous diseases of the larynx and pharynx. Selection criteria: The outcome planned to be measured in this review were: swallowing impairment, frequency of chest infections and voice and swallowing symptoms. Data analysis: We identified 1,140 citations from all electronic databases. After an initial shift we only selected 9 titles to be retrieved in full-text. After full reading, there was no RCT found in this review and therefore, we only described the existing 2 case series studies. Results: There were no randomized controlled trials found in the literature. Therefore, two studies were selected to be included only for narratively analysis as they were case series. Conclusion: There is no evidence from high quality studies about the effectiveness of speech-language therapy in patients with granulomatous diseases of the larynx and pharynx. The investigators could rely in the outcomes suggested in this review to design their own clinical trials.