Effect of boost articulation therapy (BArT) on intelligibility in adults with dysarthria

Quantifying Articulatory Working Space in Individuals Surgically Treated for Oral Cancer With Electromagnetic Articulography

PURPOSE

The purpose of this study was to quantify sentence-level articulatory kinematics in individuals treated for oral squamous cell carcinoma (ITOC) compared to control speakers while also assessing the effect of treatment site (jaw vs. tongue). Furthermore, this study aimed to assess the relation between articulatory-kinematic measures and self-reported speech problems.

METHOD

Articulatory-kinematic data from the tongue tip, tongue back, and jaw were collected using electromagnetic articulography in nine Dutch ITOC and eight control speakers. To quantify articulatory kinematics, the two-dimensional articulatory working space (AWS; in mm2), one-dimensional anteroposterior range of motion (AP-ROM; in mm), and superior-inferior range of motion (SI-ROM in mm) were calculated and examined. Self-reported speech problems were assessed with the Speech Handicap Index (SHI).

RESULTS

Compared to a sex-matched control group, ITOC showed significantly smaller AWS, AP-ROM, and SI-ROM for both the tongue tip and tongue back sensor, but no significant differences were observed for the jaw sensor. This pattern was found for both individuals treated for tongue and jaw tumors. Moderate nonsignificant correlations were found between the SHI and the AWS of the tongue back and jaw sensors.

CONCLUSIONS

Despite large individual variation, ITOC showed reduced one- and two-dimensional tongue, but not jaw, movements compared to control speakers and treatment for tongue and jaw tumors resulted in smaller tongue movements. A larger sample size is needed to establish a more generalizable connection between the AWS and the SHI. Further research should explore how these kinematic changes in ITOC are related to acoustic and perceptual measures of speech.

Perceptual Classification of Motor Speech Disorders: The Role of Severity, Speech Task, and Listener's Expertise

PURPOSE

The clinical diagnosis of motor speech disorders (MSDs) is mainly based on perceptual approaches. However, studies on perceptual classification of MSDs often indicate low classification accuracy. The aim of this study was to determine in a forced-choice dichotomous decision-making task (a) how accuracy of speech-language pathologists (SLPs) in perceptually classifying apraxia of speech (AoS) and dysarthria is impacted by speech task, severity of MSD, and listener's expertise and (b) which perceptual features they use to classify.

METHOD

Speech samples from 29 neurotypical speakers, 14 with hypokinetic dysarthria associated with Parkinson's disease (HD), 10 with poststroke AoS, and six with mixed dysarthria associated with amyotrophic lateral sclerosis (MD-FlSp [combining flaccid and spastic dysarthria]), were classified by 20 expert SLPs and 20 student SLPs. Speech samples were elicited in spontaneous speech, text reading, oral diadochokinetic (DDK) tasks, and a sample concatenating text reading and DDK. For each recorded speech sample, SLPs answered three dichotomic questions following a diagnostic approach, (a) neurotypical versus pathological speaker, (b) AoS versus dysarthria, and (c) MD-FlSp versus HD, and a multiple-choice question on the features their decision was based on.

RESULTS

Overall classification accuracy was 72% with good interrater reliability, varying with SLP expertise, speech task, and MSD severity. Correct classification of speech samples was higher for speakers with dysarthria than for AoS and higher for HD than for MD-FlSp. Samples elicited with continuous speech reached the best classification rates. An average number of three perceptual features were used for correct classifications, and their type and combination differed between the three MSDs.

CONCLUSIONS

The auditory-perceptual classification of MSDs in a diagnostic approach reaches substantial performance only in expert SLPs with continuous speech samples, albeit with lower accuracy for AoS. Specific training associated with objective classification tools seems necessary to improve recognition of neurotypical speech and distinction between AoS and dysarthria.

An Investigation to Identify Optimal Setup for Automated Assessment of Dysarthric Intelligibility using Deep Learning Technologies

Recent advances in deep learning have provided an opportunity to improve and automate dysarthria intelligibility assessment, offering a cost-effective, accessible, and less subjective way to assess dysarthric speakers. However, reviewing previous literature in the area determines that the generalization of results on new dysarthric patients was not measured properly or incomplete among the previous studies that yielded very high accuracies due to the gaps in the adopted evaluation methodologies. This is of particular importance as any practical and clinical application of intelligibility assessment approaches must reliably generalize on new patients; otherwise, the clinicians cannot accept the assessment results provided by the system deploying the approach. In this paper, after these gaps are explained, we report on our extensive investigation to propose a deep learning–based dysarthric intelligibility assessment optimal setup. Then, we explain different evaluation strategies that were applied to thoroughly verify how the optimal setup performs with new speakers and across different classes of speech intelligibility. Finally, a comparative study was conducted, benchmarking the performance of our proposed optimal setup against the state of the art by adopting similar strategies previous studies employed. Results indicate an average of 78.2% classification accuracy for unforeseen low intelligibility speakers, 40.6% for moderate intelligibility speakers, and 40.4% for high intelligibility speakers. Furthermore, we noticed a high variance of classification accuracies among individual speakers. Finally, our proposed optimal setup delivered an average of 97.19% classification accuracy when adopting a similar evaluation strategy used by the previous studies.

A serious game for speech training in dysarthric speakers with Parkinson's disease: Exploring therapeutic efficacy and patient satisfaction

BACKGROUND

The increasing need for speech therapy due to our ageing population raises the demand on therapeutical resources. To meet this demand, innovative delivery of speech training is required. eHealth applications may provide a solution, as intensified and prolonged training is only possible and affordable in patients' home environment.

AIMS

This study explores the effects on speech intelligibility of game-based speech training that provides automatic feedback on loudness, pitch and pronunciation. Additionally, we investigate how satisfied patients are with the game-based speech training and how they experience the automatic feedback. Furthermore, patients' preferences for game-based speech training compared with face-to-face training are explored.

METHODS AND PROCEDURES

Eight adult dysarthric speakers with Parkinson's disease (PD) completed a 4-week game-based speech training in their home environment. For each speaker, 24 speech utterances were audio recorded 4 weeks before (T1), immediately before (T2) and immediately after (T3) the training. All speech samples were rated on speech intelligibility by 10 untrained listeners, by comparing them with the corresponding utterances realized by a healthy speaker. Changes over time were analysed using a linear mixed-effects analysis. Patient satisfaction with the game and the automatic feedback was assessed using a questionnaire. The preferences of patients were collected using a paired comparisons procedure in which the patients were asked whether they would prefer game-based or face-to-face speech training in four hypothetical scenarios with different hypothesized levels of speech improvement.

OUTCOMES AND RESULTS

While there was no significant difference in speech intelligibility ratings between T1 and T2, we did find one between T2 and T3. At T3, speech intelligibility was rated higher than at T2, indicating positive effects of the game-based speech training. Patients generally seemed satisfied with the game as average ratings were above 7 on a 10-point rating scale. Generally, patients agreed with the automatic feedback and could use it to positively change the way they spoke. Patients prefer the training that provides the highest hypothetical improvement, and thus do not prefer face-to-face above game-based therapy.

CONCLUSIONS AND IMPLICATIONS

The results of this study suggest that dysarthric speakers due to PD see game-based speech therapy as a valid alternative for face-to-face therapy and that it leads to an average improvement in speech intelligibility. For an optimal effect and user satisfaction it should preferably not be used in isolation but in combination with face-to-face training. In this manner, the strengths of both therapeutic deliveries can be harnessed.

WHAT THIS PAPER ADDS

What is already known on this subject Dysarthric speech in patients with PD is known to benefit from intensified and long-term speech therapy. The increasing need for speech therapy due to our ageing population raises the demand on therapeutical resources making highly frequent and long-term therapy difficult. eHealth provides the opportunity to intensify and prolong speech training in patients' home environment. A drill-and-practice method was employed and investigated in a web-based speech application, indicating positive effects on speech intelligibility. However, participants indicated a lack of variation in exercises making the training less enjoyable. Other research showed that serious games can increase enjoyment during training. What this paper adds to existing knowledge The results of this study show that it is possible to develop a serious game that can be successfully used for speech training by patients with dysarthria due to PD. Comparing speech intelligibility ratings before and after training, we observed significant improvements in speech intelligibility ratings. Patients generally agree with the automatic feedback and can use it to positively change the way they speak. Average ratings were above 7 on a 10-point scale, indicating that patients are satisfied with the game. Patients prefer the type of training (game based or face to face) that provides the highest hypothetical improvement. What are the potential or actual clinical implications of this work? The results of this study suggest that game-based speech training can improve speech intelligibility in patients. This indicates that it can be considered a suitable approach in the treatment of patients with dysarthria due to PD. Patients do not prefer game-based training above face-to-face training in all scenarios. For that reason, for every patient one should carefully consider how to optimally combine game-based and face-to-face training.

Automatic boost articulation therapy in adults with dysarthria: Acceptability, usability and user interaction

BACKGROUND

Imprecise articulation has a negative impact on speech intelligibility. Therefore, treatment of articulation is clinically relevant in patients with dysarthria. In order to be effective and according to the principles of motor learning, articulation therapy needs to be intensive, well organized, with adequate feedback and requires frequent practice.

AIMS

The aims of this pilot study are (1) to evaluate the feasibility of a virtual articulation therapy (VAT) to guide patients with dysarthria through a boost articulation therapy (BArT) program; (2) to evaluate the acoustic models' performance used for automatic phonological error detection; and (3) to validate the system by end-users from their perspective.

METHODS & PROCEDURES

The VAT provides an extensive and well-structured package of exercises with visual and auditory modelling and adequate feedback on the utterances. The tool incorporates automated methods to detect phonological errors, which are specifically designed to analyse Dutch speech production. A total of 14 subjects with dysarthria evaluated the acceptability, usability and user interaction with the VAT based on two completed therapy sessions using a self-designed questionnaire.

OUTCOMES & RESULTS

In general, participants were positive about the new computer-based therapy approach. The algorithm performance for phonological error detection shows it to be accurate, which contributes to adequate feedback of utterance production. The results of the study indicate that the VAT has a user-friendly interface that can be used independently by patients with dysarthria who have sufficient cognitive, linguistic, motoric and sensory skills to benefit from speech therapy. Recommendations were given by the end-users to further optimize the program and to ensure user engagement.

CONCLUSIONS & IMPLICATIONS

The initial implementation of an automatic BArT shows it to be feasible and well accepted by end-users. The tool is an appropriate solution to increase the frequency and intensity of articulation training that supports traditional methods.

WHAT THIS PAPER ADDS

What is already known on the subject Behavioural interventions to improve articulation in patients with dysarthria demand intensive treatments, repetitive practice and feedback. However, the current treatments are mainly limited in time to the interactive sessions in the presence of speech-language pathology. Automatic systems addressing the needs of individuals with dysarthria are scarce. This study evaluates the feasibility of a VAT program and investigates its acceptability, usability and user interaction. What this paper adds to existing knowledge The computer-based speech therapy approach developed and applied in this study intends to support intensive articulation training of patients with dysarthria. The virtual speech therapy offers the possibility of an individualized and customized therapy programme, with an extensive database of exercises, visual and auditory models of the target utterances, and providing adequate feedback based on automatic acoustic analysis of speech. What are the potential or actual clinical implications of this work? The automatic BArT overcomes the limitation in time of face-to-face traditional speech therapy. It offers patients the opportunity to have access to speech therapy more intensively and frequently in their home environment.