The Etymology and Semantics of the Ethnic Name Csángó

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In order to improve the ability of English special sentence pattern conversion in machine translation software, an English special sentence pattern conversion method based on semantic feature analysis is proposed. The semantic feature analysis model of feature vocabulary translation is constructed, the semantic correlation feature analysis method is used to detect the features in the process of English special sentence pattern transformation in machine translation software, the semantic decomposition model of English special sentence pattern transformation in machine translation software is established, and the online feature quantity of characteristic vocabulary translation is extracted. The fusion clustering analysis method is used to control the adaptive optimization in the process of English special sentence pattern conversion of machine translation software, and the machine learning algorithm is used to judge the fuzzy control and convergence in the process of English special sentence pattern conversion of machine translation software, and the optimization of English special sentence pattern conversion process of machine translation software is realized. The simulation results show that the control of English special sentence pattern conversion by machine translation software is stable and the translation results are accurate and reliable.

Background: Up to 60% of people with aphasia experience persistent word-finding difficulties into the chronic stage, starting six months after the stroke. Semantic Feature Analysis (SFA) and Phonological Components Analysis (PCA) are two common word-finding interventions that use the generation of semantic features for SFA (e.g. category) and phonological features for PCA (e.g. first sound) to improve naming. Despite inconsistent support for the generalization to untreated items, studies have shown improvements on probe word naming for treated items. However, research concerning within-intervention effects and generalization to alternative contexts has been limited. Aim: This study investigated the effect of treatment for SFA and PCA probe word naming as well as their within-intervention effects in four individuals with chronic post-stroke aphasia. Methods & Procedures: Baseline and follow-up measures included standardized assessments and image naming tasks. The image naming task was used to generate three lists: an SFA treated list, a PCA treated list, and an untreated list. One SFA session and one PCA session per week were then provided concurrently to each participant for a period of six weeks. Outcomes & Results: While only one participant experienced significant gains on treated probe word naming, these gains were maintained four weeks after the intervention. Exploratory results suggested that effects could transfer to two types of generalization items: different pictures of the same items and pictures of items shown in a natural context. Furthermore, while generalization to untreated items did not reach significance for any participant, some generalization of gains to standardized assessments was observed. Although rarely equivalent for SFA and PCA interventions, all participants also experienced some degree of within-intervention improvement over the progression of sessions. These improvements included a reduction in the number of forced choices required for feature generation and/or a reduction in the number of words never named during intervention sessions. Conclusion: The results support additional avenues of investigation for SFA and PCA therapies for individuals with post-stroke aphasia, namely within intervention effects and the potential for generalization to different contexts.

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Background: Semantic feature analysis (SFA) is a prominent treatment for the word retrieval deficits of aphasia. Generalisation of improved word retrieval on picture naming to discourse production has been an important factor for evaluating the effectiveness of SFA treatment. Unfortunately, generalisation of word retrieval improvements to discourse production following SFA has been modest. Aims: Because of the previous, albeit limited, success of SFA in producing improved word retrieval for discourse we further examined the utility of SFA for reducing noun and verb retrieval failures in aphasic discourse. Rather than use SFA as a means for improving generalisation of picture naming or as a compensatory strategy for lexical failures during discourse, we applied SFA as an a priori means to reduce the frequency of word retrieval failures in discourse. Methods & Procedures: Semantic feature analysis was applied to object and action word retrieval failures appearing during picture descriptions and procedural questions by two participants with anomic aphasia. A single case time-series design across behaviours with replication was used to assess changes in discourse production as well as generalisation of treatment effects to untrained pictures resulting from SFA. Outcomes & Results: Increases were observed in verbal productivity for both participants, while the informativeness of the participant's discourse, as measured by correct information unit analyses, also improved. Minimal changes were observed in the frequency and type of word-finding behaviours evinced by the participants; this finding was attributed to a masking effect arising from the participants' increased quantity of verbal output. Evidence was also found that targeting word finding behaviours in connected speech generalised to naming of untrained object and action pictures. Conclusions: The changes effected by this discourse-based approach to SFA were as robust and as consistent as has been achieved previously with SFA treatment. The choice to use a discourse-based versus a picture-based approach to SFA treatment might be based on the ecological validity of the discourse-based approach.

Case Presentation: We reported the case of a 61-year-old male patient with a university degree, diagnosed with the semantic variant of primary progressive aphasia (svPPA). For five years, he had experienced progressive anomia, initially affecting proper names and low-frequency nouns, gradually extending to more frequent items. The patient underwent an assessment involving 50 visual stimuli across five semantic categories. He was asked to name and describe each item. The stimuli were randomly assigned to trained (n=25) and untrained (n=25) items. The intervention lasted two months, with five weekly sessions (one in-person and four remote via Google Forms), totaling 40 hours. A formal-semantic treatment based on Semantic Feature Analysis was implemented, incorporating spaced retrieval and errorless learning strategies. At baseline, naming accuracy was similar across groups. However, trained items showed a significant improvement (from 40 to 88%), whereas untrained items improved modestly (from 44 to 52%). In the definition task, both groups showed gains in semantic feature retrieval (30% for trained, 40% for untrained items). Discussion: Although naming gains did not generalize to untrained items, the overall improvement in semantic feature access in definition task suggests an improvement in the semantic network as a whole. This may support communication in daily life by enabling the patient to describe target concepts more effectively when word retrieval fails. Final Considerations: Intensive therapy based on Semantic Feature Analysis proved effective in improving naming performance and strengthening semantic network in a patient with svPPA.

Recent developments in “lexical semantics” have prompted the development of the “semantic field theory,” or “semantic features analysis” approaches, which organize words in terms of interrelated lexical meanings. Research has shown that semantic feature analysis is a powerful strategy that mimics the way the brain organizes information. SFA suggests that the lexical content of a language is best treated not as an unstructured list of words but as a collection of interrelating networks of relations between words. Hence, it is plausible to assume that a method of teaching that takes account of the psychological processes underlying semantic relatedness must be more effective pedagogically than one that does not. The present entry discusses the pedagogic implications of “semantic feature analysis” to second language vocabulary teaching and learning.

The current Internet data explosion is expecting an ever-higher demand for text emotion analysis that greatly facilitates public opinion analysis and trend prediction, among others. Therefore, this paper proposes to use a dual-channel convolutional neural network (DCNN) algorithm to analyze the semantic features of English text big data. Following the analysis of the effect of CNN, artificial neural network (ANN), and recurrent neural network (RNN) on English text data analysis, the more effective long short-term memory (LSTM) and the gated recurrent unit (GRU) neural network (NN) are introduced, and each network is combined with the dual-channel CNN, respectively, and comprehensively analyzed under comparative experiments. Second, the semantic features of English text big data are analyzed through the improved SO-pointwise mutual information (SO-PMI) algorithm. Finally, the ensemble dual-channel CNN model is established. Under the comparative experiment, GRU NN has a better feature detection effect than LSTM NN, but the performance increase from dual-channel CNN to GRU NN + dual-channel CNN is not obvious. Under the comparative analysis of GRU NN + dual-channel CNN model and LSTM NN + dual-channel CNN model, GRU NN + dual-channel CNN model ensures the high accuracy of semantic feature analysis and improves the analysis speed of the model. Further, after the attention mechanism is added to the GRU NN + dual-channel CNN model, the accuracy of semantic feature analysis of the model is improved by nearly 1.3%. Therefore, the ensemble model of GRU NN + dual-channel CNN + attention mechanism is more suitable for semantic feature analysis of English text big data. The results will help the e-commerce platform to analyze the evaluation language and semantic features for the current network English short texts.

<b>PB-PG-0609-18074 – NIHR Research for Patient Benefit Programme – Final report</b><br /> <br /> <b>Project title: </b>SemaFoRe: Semantic Feature and Repetition therapy in aphasia: A pilot RCT<br /> <br /> <b>Authors: </b>Dr Julie Morris - Newcastle University<br /> Professor David Howard - Newcastle University&nbsp;<br /> Mrs Frauke Buerk - Newcastle upon Tyne Hospitals Trust<br /> <br /> <b>Plain language summary</b><br /> This project focused on therapy for word finding difficulties in aphasia, an acquired communication problem, often following stroke . The project was designed as a pilot study to inform future research, looking at whether the research was feasible and acceptable. It examined two treatments to improve word finding: ‘Semantic Feature Analysis’ (SFA) and ‘Repetition in the Presence of a Picture’ (RIPP). In SFA, you generate ideas around a particular word. RIPP involves repeating words. Participants’ communication was assessed before and after therapy, including the ability to retrieve words via naming and describing pictures. Participants’ views of their communication and therapy were collected.<br /> <br /> In terms of findings about feasibility and acceptability of the research, we considered recruitment to the study, retention and acceptability (whether people stayed in the study and what they thought about it). We had 41 people referred to the study with 25 suitable. We aimed to recruit 30 in total. Recruitment was slightly slower than we had anticipated at the start. Of the 25 who took part, 23 completed every aspect of the study; this is a major achievement given the commitment (8-9 month period). The 2 people who did not complete were unable to because of ill health. Participants reported favourably about therapy; they liked both therapies with little they would change. It therefore appears that the research is feasible and acceptable to participants.<br /> <br /> In terms of more specific results, though this is a pilot study, our results do not completely replicate previous findings. Importantly, both treatments appear only to have an effect on the words treated; previous evidence suggested that SFA would improve word finding generally but this study did not find that, certainly in correct retrieval of words. Additionally, participants appear to benefit from either both or neither treatment.<br /> The implications of our research is that the methods used are acceptable to participants and it was possible to recruit and retain participants. The findings, whilst a pilot study, are based on results from 23 people; this is a larger sample than typical when such well defined therapies are investigated. Results suggest effects of these therapies are restricted to treated items; if this is the case, this has important implications for selection of treatment words. Further research in this area is warranted and we are currently developing a proposal to take to funders.<br /> <br /> <b>Keywords</b><br /> Aphasia, Anomia, Word-finding, Semantic feature analysis, Therapy, Treatment, Rehabilitation<br /> <br /> <b>Summary of research findings</b><br /> BACKGROUND<br /> This study aims to contribute to the development of research and the evidence base about treatment for word retrieval in aphasia. Aphasia is an acquired communication problem, usually after stroke or head injury. One of the most frequent difficulties experienced is a problem with word retrieval; this is therefore a frequent goal of intervention. One of the treatments in clinical use is Semantic Feature Analysis (SFA). In SFA the person is shown a picture and asked to retrieve semantic information about it (e.g. what it is used for). This treatment is of interest as some evidence suggests that treatment effects generalise to words not worked on in therapy. This is in contrast to other word retrieval therapies where effects have been shown to be restricted to treated words. If working on one word can effect change in another (untreated) word, this is an attractive treatment option; the impact of treatment is maximised. However, although widely used, there is a limited evidence base for SFA (limited by number of participants and items as well as other aspects of methodology). The evidence base also describes a set of word retrieval interventions which are more phonological in nature, involving pairing of phonology with meaning, often involving repeating the word. We have called this Repetition in the Presence of a Picture (RIPP). In RIPP, treatment effects are restricted to words seen in treatment. This study involved both treatment approaches, within a pilot cross over randomised control trial.&nbsp;<br /> <br /> AIMS AND OBJECTIVES<br /> This study is a pilot RCT which aimed:<br /> 1. To determine the approximate effect size for the primary outcome measure to inform the power calculation for a trial.<br /> 2. To assess whether the randomised crossover design is an appropriate trial design in this context.<br /> 3. To establish patterns of recruitment, consent and retention, including whether the burden of data collection required by multiple assessments in a cross-over design is acceptable.<br /> 4. To evaluate whether all planned assessment points are necessary to inform the study.<br /> 5. To evaluate overall satisfaction for the people with aphasia with the delivery of therapy.<br /> <br /> METHODS<br /> Participants were recruited by speech and language therapists (SLTs) across several hospital trusts. Participants were at least 3 months post stroke and had word retrieval difficulties, scoring 10%-60% on a naming test. They had no other significant cognitive difficulties. Participants stopped SLT for the study period, though could attend support groups. Following consent, a brief screen of speech production, comprehension and cognitive skills took place. Eligible participants were randomly assigned to one of two treatment orders; SFA followed by RIPP or RIPP followed by SFA. The random allocation was generated via an external randomisation service (Newcastle Clinical Trials Unit).&nbsp;<br /> Each therapy took place twice weekly over a 6 week period with sessions of 1 hour, either in University rooms or the participant’s home. Treatment protocols were established based on literature and discussion with the primary authors in each field. The person administering therapy worked with another SLT to refine the protocols and then to ensure adherence to the protocols.<br /> The items used in therapy were subsets of a 150 item word/picture set. In each phase of therapy, one sub-set of 50 items was treated. The sub-sets were specific to participants; the division into sets A (used in therapy A), B (used in therapy B) and C (control; never treated) was on pre-therapy performance and matched for word frequency and length. Within these constraints, items were randomly allocated to the three sets.&nbsp;<br /> An SLT administered therapy, with assessments carried out by a different SLT who was both blind to treatment condition (SFA vs. RIPP) and item set (set A, B, C). It was not possible for participants to be blind to condition since this was obvious during therapy. For analysis of connected speech, the person transcribing and analysing the samples was completely blinded using anonymised, time referent free samples. Participants’ performance was assessed after each treatment phase, with a gap between the two phases of therapy (of equivalent duration to a therapy period). This led to seven assessment points (Ax.1 &amp; Ax.2 prior to any therapy, Ax.3 following therapy A, Ax.4 prior to therapy B, Ax.5 following therapy B, Ax.6 six weeks and then Ax.7 ten weeks after all treatment ended), with approximately equal gaps between assessments 1-6.&nbsp;<br /> The primary outcome measure was the percentage of the 150 words named correctly. Secondary outcome measures were a comprehension task involving the 150 words, measures of connected speech and a measure of the participant’s perception of change in their communication.&nbsp;<br /> <br /> KEY FINDINGS<br /> There are two aspects to the findings from this study. The first relates to the pilot nature of the study and concerns the feasibility of the methods and design. The second concerns the findings in relation to the treatment effects. Taking the pilot aspects first and considering recruitment: of the 41 people recruited to the study, 25 people were appropriate. Reasons for not being included in the study were typically that word retrieval abilities were above or below the 10-60% criteria. Rates of recruitment were therefore reasonable, with a relatively high referral to consent to participation ratio (i.e. appropriate people were referred). Recruitment was slightly slow in the initial phases and improved. In terms of retention, of the 25 people recruited to the study, there was excellent retention. Only 2 participants were lost to the study due to ill health. 23 participants completed therapy and took part in assessment at all 7 points (spanning approx. 8-9 months), representing a significant commitment. Participants completed an aphasia friendly post-therapy questionnaire (at assessment time points 3 and 5). Participants were overwhelmingly positive about therapy, with very little that they would change. Within the questionnaire, 13 participants stated they had no preference for one therapy, 9 preferred SFA and 1 preferred RIPP.<br /> <br /> In terms of participants’ response to treatment, we found an average effect size (primary outcome measure) for treatment of 11.0 extra items with RIPP (95% CI 16.5-5.4, d=0.49), and 3.3 with SFA (7.7-1.0, d=0.15). The difference was highly significant (CI: 12.5-2.8, d=0.34). Across all 23 participants there was a significant overall improvement: a linear trend (z=8.79, p&lt;&lt;.0001). We also saw differences between people: homogeneity test χ2 (22) = 197.4, p&lt;&lt;0.0001 (which is unsurprising given the variation within aphasia). When the treatment effect was examined by therapy period and considering whether items had been within the treated set or not, the results demonstrated that both treatments were effective; however there was significantly larger effect of treatment for RIPP than for SFA. For both treatments the effect was seen for those items seen within treatment (contrary to predictions for SFA). Analysis of this pilot data also suggests that participants benefited from both or neither therapy. The predictor variables available to us in this study (background language, wider cognitive and demographic variables) did not allow us to predict the benefit.<br /> In considering the secondary outcome measures, there was small but significant change for the semantic verification task and also for the participant rating measure (COAST) over time. We are continuing to analyse the data from the connected speech measures, with a focus on the picture description task from the Comprehensive Aphasia Test, which was completed across each assessment point and for which there is data on the reliability and validity of scoring.<br /> <br /> All seven assessment points appear important and feasible to deliver on. The two pre therapy assessments facilitated item selection to treatment sets, it is essential to have pre and post therapy assessment to allow comparison of performance and the final post-therapy measurements are clearly important both to the clinical community and to participants (with questions at dissemination events about the longer term benefits of treatment).&nbsp;<br /> <br /> EXPECTED IMPACT AND CONCLUSION<br /> This study demonstrates the feasibility of a crossover RCT of specific aphasia therapies. Referral to a study of this type is feasible; our experience suggests that in future, the recruitment drive needs to start before the study is ready to recruit to facilitate consultation with potential participants. This study only used SLT recruiters; it was not possible to utilise the resources of the (then) Stroke Research Network. Strong support was given to the study, but referrers needed to know in detail about potential participants’ aphasia and about other therapy needs. Retention within the study and acceptability to participants were both excellent, suggesting the design and methods are appropriate. However, it is important to remember that one therapist delivered all intervention, with one research site and so participants had a great deal of consistency and this may have contributed to this success.&nbsp;<br /> The study, whilst a pilot, also generated interesting results regarding the two treatments. Both were effective, but RIPP more so; neither treatment showed generalisation to untreated items on the primary outcome measure (contrary to predictions). This has a potential impact on treatment choices for word retrieval; if the more complex SFA treatment cannot be demonstrated to have an advantage, then RIPP may be the treatment of choice for this specific aspect of aphasia rehabilitation. Results from this pilot study suggest we need to better understand the impact of treatment on everyday communication and confidence in communication, whether we can get generalisation of treatment effects, what might predict benefit and also explore whether there is a more efficient way to deliver the repetition therapy.&nbsp;<br /> <br /> <b>Patient and public involvement</b><br /> Involvement of patients has grown with this project and spread beyond this project to influence subsequent projects (from PhD studies to project grants). In developing the original project proposal, a small Aphasia Research User Group (ARUG) was set up, and has discussed (in varying depth) this project on 6 occasions. Aphasia adds a challenge to involvement of patients; people have communication difficulties which can affect their understanding of spoken and written communication and their ability to convey their ideas. This has meant meetings need to be facilitated; both in terms of understanding (of spoken and written material) and expression of ideas. Meetings have been small (typically 4-5 members with 2 facilitators who are qualified SLTs). Over time, we have developed our skills in ensuring members are able to truly contribute their views, but importantly members have gained experience and the confidence to put forward their ideas. We have also recently invited a family member to join the group, to widen consultation. We have also worked with one member, a gentleman with aphasia and with a scientific background, who has been able to comment on specific queries via e-mail (this project, and others) and this has been useful. He has commented on the lay summary of this report and has been sent the full report. We remain mindful of ensuring people with aphasia themselves are able to fully contribute. The importance of considering what to consult about, and what amount has been important as has building on information over time. The group appears to have a sense of ownership of this particular project.<br /> <br /> ARUG has gone on to be involved with other projects (e.g. Reading Comprehension in Aphasia) and to shape ideas within that project. We also encourage students (PhD, UG) who are completing projects involving people with aphasia, to present to and consult with ARUG as part of their research training (e.g. Fiona Menger, Stroke Association Fellow).&nbsp;<br /> We are now looking at ways to ensure ARUG is sustainable over time. This is both in terms of members but also in terms of the researchers' time involved. Ideally there needs to be some consistency of faciltitator and/or overall coordinator. We are looking to a model where in future these costs might be met by funded grants (by having a costing model for any future grants). The aim would be to enable ARUG to continue consultation in the very early stages (when there is no identified funding stream) into a funded role in funded projects. ARUG members have not wanted remibursement for their time to date, but this, along with other principles, would need revisiting over time. ARUG would like to develop a web presence and a set of guidelines for researchers, drawing on its experience.<br /> <br /> The project also held a wider PPI event in November 2014, inviting participants, family members and referring speech and language therapists to a dissemination and future plans event. Results of the project were discussed and then small groups discussed their views on possible future directions for the research (summary available on request). These are being taken forward as we consider the next stages.&nbsp;<br /> As seen in the ResearchFish submission, there has been on-going engagement of the SLT profession, particularly regionally, who have been engaged in discussion about this project since the outset.<br /> &nbsp;<br /> <b>Data sharing statement</b><br /> See link <a href="https://www.nihr.ac.uk/documents/nihr-position-on-the-sharing-of-research-data/12253">[https://www.nihr.ac.uk/documents/nihr-position-on-the-sharing-of-research-data/12253</a>] for the NIHR position of the sharing of research data.&nbsp; The NIHR strongly supports the sharing of data in the most appropriate way, to help deliver research that maximises benefits to patients and the wider public, the health and care system and which contributes to economic growth in the UK.&nbsp; All requests for data should be directed to the award holder and managed by the award holder.<br /> <br /> <b>Disclaimer</b><br /> This project is funded by the National Institute for Health Research (NIHR) under its Research for Patient Benefit (RfPB) Programme (Grant Reference Number PB-PG-0609-18074). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.<br /> <br /> This project was carried out between March 2011 and November 2014. This final report has not been peer-reviewed. The report was examined by the Programme Director at the time of submission to assess completeness against the stated aims.

Vocabulary becomes the main problem that encountered by the students in SMP Negeri 14 Kendari. Less motivation and interest are factors that affect students in learning vocabulary. The research question of this study was “Is there any significant effect of semantic feature analysis on students’ vocabulary achievement at the second grade students of SMP Negeri 14 Kendari?” The objective of this study was to find out whether semantic feature analysis has an effect on students’ vocabulary achievement at the second grade students of SMP Negeri 14 Kendari. The population of this study was all students at second grade of SMP Negeri 14 Kendari who registered on second semester in academic year 2017/2018 with the total number of students’ were 205 students. The samples of this study were all students at class VIII.2 with total number of students are 30 and it taken by using simple random sampling. The instrument of this study was vocabulary test which consisted of 25 items (5 items matching with the synonym, 10 items matching with the meaning, 5 items complete the sentences and 5 items fill in the blank test). They were administered into two groups as the pre test and post test. The researcher used Paired Sample T-test in SPSS 16 to analyze the result of the research whether there is a significant effect of semantic feature analysis on students’ vocabulary achievement after analyzed the normality of the data in experiment class. Based on the analysis result of pre-test and post-test through SPSS in form of test, it found that the probability (Sig. 1-tailed) was 0.000 (ρ &lt; 0.05) and the calculation of tcount (10.070) was higher than ttable (1.699) in the level of significance 0.05, df = 29. It indicated that null hypothesis (H0) was totally rejected and the alternative hypothesis (H1) was completely accepted. Therefore, it can be concluded that there is enough evidence to claim that semantic feature analysis strategy has significant effect on students’ vocabulary achievement at the second grade students of SMP Negeri 14 Kendari.Keyword: Vocabulary, Semantic Feature Analysis

Background Semantic therapy tasks are popular in aphasia rehabilitation, with many different treatments reported that claim to target semantic processing and to effect improvement. While most tasks involve some semantic processing, the term “semantic therapy task” generally refers to tasks with an explicit focus on meaning (e.g. semantic feature analysis, odd-one out), rather than tasks that only require implicit semantic processing (e.g. repetition in the presence of the picture). Despite the focus on meaning, the active ingredients underpinning explicit semantic tasks remain unclear. Aim This research aimed to examine the prevalence and change over time in the use of different explicit semantic therapy tasks, identifying the steps within each task and the variability of these tasks and steps across studies. Method and procedures Scoping review methodology was used to systematically search for studies published before November 3, 2022. Studies were included if they reported primary data that included participants with stroke aphasia and described semantic therapy tasks. We documented explicit semantic tasks and their component steps, and examined variability across semantic therapy studies. Outcomes and results 8,571 records were screened, 631 full-text articles assessed for eligibility, and 244 articles were included. We identified 67 distinct semantic tasks. Over time, there was a significant increase in the studies using semantic feature analysis (i.e. semantic feature generation protocol ± semantic feature review), and a corresponding decrease in the studies using other tasks. There was considerable variability in the implementation of semantic tasks, with different combinations of steps. We examined two tasks in detail (semantic feature generation, cueing hierarchy). Variability in the implementation of semantic feature generation included differences in the features used, whether or not feature choice was provided, whether feature repetition was required, and the inclusion of additional tasks (e.g. response elaboration training). Cueing hierarchies varied in the type, number, and order of cues provided. Conclusion This scoping review demonstrates the continued and increasing use of explicit semantic tasks in aphasia rehabilitation. By detailing the steps used in explicit semantic tasks, we highlight variability in their implementation. Semantic tasks are often multicomponent, multimodal and/or combined with additional tasks, and the vast majority include a word-form component (e.g. picture naming, repetition in the presence of a picture). The active ingredients of semantic tasks are obscured by this variability. Future research is required to further our understanding of the active and essential ingredients of semantic therapy provided to people with aphasia.

Introduction: Semantic Feature Analysis (SFA) therapy is a widely used approach for single-word naming treatment in monolingual and bilingual persons with aphasia (BiPWAs). There is evidence that SFA leads to naming improvements in both treated and untreated languages of BiPWAs. However, research on the generalization effects of SFA on narrative production is scarce. This study investigated the within- and cross-language generalization effects of SFA on narrative production and its relationship to naming gains in a group of L1-Russian-L2-Hebrew chronic-stage BiPWAs. Methods: The study included two groups of BiPWAs. In the experimental group, ten individuals received one or two blocks of SFA, while ten participants who did not receive therapy served as a control group. We compared the changes in narrative production between the experimental and control groups and examined whether the narrative changes in the experimental group were related to naming gains. Results: The results indicated that SFA generalized to narrative production in the experimental group. Within-language generalization was observed following SFA in L1, while cross-language generalization was found following SFA in both L1 and L2. Conclusion: Although SFA has the potential to generalize to narrative production in BiPWAs, this effect did not consistently align with the therapy gains in naming. To achieve greater within- and cross-language generalization effects, we recommend providing SFA in the L1 of BiPWAs.

Background: Semantic feature analysis (SFA) is a treatment approach aimed at enhancing lexical retrieval by improving access to the semantic network in speakers with aphasia. Although there are promising results on trained items, previous studies exploring the impact of SFA on verb production in monolingual speakers have shown mixed results for generalisation to untrained items and discourse. There are few published studies investigating SFA and action naming in multilingual speakers.Aims: The study explores the impact of SFA on trained and untrained verbs, semantics and syntax, and narrative production in the trained and untrained languages of a multilingual speaker (Japanese–English–German–Norwegian) with moderate non-fluent aphasia. Treatment was conducted in a late-acquired language (Norwegian).Methods & Procedures: SFA was provided during an intensive schedule of about 22 hr of therapy, with approximately 10 hr per week over two and a half weeks. The treatment focused on the production of verbs in sentence contexts.Outcomes & Results: Outcome measures include the Bilingual Aphasia Test, an action-naming test, and production of semi-spontaneous narratives.Outcomes in the treated language: Overall, the participant responded positively to the SFA treatment. The trained verbs improved significantly, but no transfer was observed to untrained verbs. There were no changes in the formal testing of semantics or syntax, but improvements were noted in narrative production.Cross-linguistic outcomes: Transfer to verbs in untreated German was evident. There were significant increases in the semantics and syntax in both English and German. The participant showed an improvement in discourse in English and German, although not in Japanese.Conclusions: SFA treatment in a late-acquired language can lead to gains in the treated language and transfer to both stronger and weaker languages, with different patterns for the various languages. This indicates that SFA may be a promising method for treating multilingual speakers with aphasia. The authors further advocate the use of narratives as an assessment tool. In addition to enhancing the ecological validity of the findings, the narratives provided information not obtainable from the other assessment tools for within- and cross-linguistic therapy gains for the participant.

Background Semantic Feature Analysis (SFA) treatment has been proven to be effective in alleviating word finding difficulties in individuals with aphasia. However, there is no consensus on the impact of SFA on naming abilities and general language skills in bilingual persons with aphasia (BiPWAs), nor on factors that determine the success of the SFA treatment. Aims This study aimed to investigate the efficacy of SFA treatment in a group of L1-Russian – L2-Hebrew chronic stage BiPWAs and to evaluate the contribution of background factors, language and cognitive measures on the treatment success. Methods & Procedures The current study included two groups of BiPWAs. In the experimental group (n=10), six individuals received SFA therapy in both languages and four individuals in L2. The delayed-treatment group (n=10) did not receive therapy and served as a control group. All BiPWAs completed the Bilingual Aphasia Test (BAT) in both languages, as well as a battery of 10 cognitive tests and linguistic background questionnaires. Outcome & Results The results indicated a direct effect of SFA treatment on naming as well as within-language generalization and cross-language transfer. Importantly, we found significant improvements of general language skills in the treated and untreated languages in BiPWAs who received SFA treatment, while no such improvement was observed in the control group. Non-verbal inhibition and verbal working memory in L1-Russian predicted success of SFA treatment in BiPWAs. Conclusions SFA therapy has positive effects on naming ability of BiPWAs. In addition, SFA therapy affects general language skills in BiPWAs. Yet, within-language generalization, cross-linguistic transfer, and maintenance of the treatment results vary across individuals. The success of SFA treatment in BiPWAs is predicted by cognitive functions rather than background factors of bilingualism.

Gestures and their concurrent words are often said to be meaningfully related and co-expressive. Research has shown that gestures and words are each particularly suited to conveying different kinds of information. In this paper, we describe and compare three methods for investigating the relationship between gestures and words: (1) an analysis of deictic expressions referring to gestures, (2) an analysis of the redundancy between information presented in words vs. in gestures, and (3) an analysis of the semantic features represented in words and gestures. We also apply each of these three methods to one set of data, in which 22 pairs of participants used words and gestures to design the layout of an apartment. Each of the three analyses revealed a different picture of the complementary relationship between gesture and speech. According to the deictic analysis, participant speakers marked only a quarter of their gestures as providing essential information that was missing from the speech, but the redundancy analysis indicated that almost all gestures contributed information that was not in the words. The semantic feature analysis showed that participants conveyed spatial information in their gestures more often than in their words. A follow-up analysis showed that participants contributed categorical information (i.e., the name of each room) in their words. Of the three methods, the semantic feature analysis yielded the most complex picture of the data, and it served to generate additional analyses. We conclude that although analyses of deictic expressions and redundancy are useful for characterizing gesture use in differing conditions, the semantic feature method is best for exploring the complementary, semantic relationship between gesture and speech.