Why Can't Individuals with Nonfluent Aphasia Produce Sentences? Exploring the Role of Lexical Availability

<p>Nonfluent aphasia is a language disorder characterised by sparse, fragmented speech. Individuals with this disorder often produce single words accurately (for example, they can name pictured objects), but have great difficulty producing sentences. An important research goal is to understand why sentences are so difficult for these individuals. To produce a sentence, a speaker must not only retrieve its lexical elements, but also integrate them into a grammatically well-formed sentence. Indeed, most research to date has focused on this grammatical integration process. However, recent studies suggest that the noun and/or verb content of the sentence can also be an important determinant of success (e.g., Raymer & Kohen, 2006; Speer & Wilshire, 2014). In this thesis, I explore the role of noun availability on sentence production accuracy using an identity priming paradigm. Participants are asked to describe a pictured event using a single sentence (e.g., “The fish is kissing the turtle”). In the critical condition, an auditory prime word is presented just prior to the picture, which is identical to one of the nouns in the target sentence (e.g., fish). The rationale is that the prime will enhance the availability of its counterpart when the person comes to produce the target sentence. Participants were four individuals with mild nonfluent aphasia, two individuals with fluent aphasia, and six older, healthy controls. Consistent with our hypotheses, the nonfluent participants as a group were more accurate at producing sentences when one of its nouns – either the subject or object - was primed in this way. Importantly, in the primed subject noun condition, these results held even when accuracy on the primed element itself was excluded, suggesting it had a broad effect on sentence production accuracy. The primed nouns had no effect on sentence production accuracy for the fluent individuals or the controls. We interpret these findings within models of sentence production that allow for considerable interplay between the processes of lexical content retrieval and sentence structure generation.</p>

Why Can't Individuals with Nonfluent Aphasia Produce Sentences? Exploring the Role of Lexical Availability

<p>Nonfluent aphasia is a language disorder characterised by sparse, fragmented speech. Individuals with this disorder often produce single words accurately (for example, they can name pictured objects), but have great difficulty producing sentences. An important research goal is to understand why sentences are so difficult for these individuals. To produce a sentence, a speaker must not only retrieve its lexical elements, but also integrate them into a grammatically well-formed sentence. Indeed, most research to date has focused on this grammatical integration process. However, recent studies suggest that the noun and/or verb content of the sentence can also be an important determinant of success (e.g., Raymer & Kohen, 2006; Speer & Wilshire, 2014). In this thesis, I explore the role of noun availability on sentence production accuracy using an identity priming paradigm. Participants are asked to describe a pictured event using a single sentence (e.g., “The fish is kissing the turtle”). In the critical condition, an auditory prime word is presented just prior to the picture, which is identical to one of the nouns in the target sentence (e.g., fish). The rationale is that the prime will enhance the availability of its counterpart when the person comes to produce the target sentence. Participants were four individuals with mild nonfluent aphasia, two individuals with fluent aphasia, and six older, healthy controls. Consistent with our hypotheses, the nonfluent participants as a group were more accurate at producing sentences when one of its nouns – either the subject or object - was primed in this way. Importantly, in the primed subject noun condition, these results held even when accuracy on the primed element itself was excluded, suggesting it had a broad effect on sentence production accuracy. The primed nouns had no effect on sentence production accuracy for the fluent individuals or the controls. We interpret these findings within models of sentence production that allow for considerable interplay between the processes of lexical content retrieval and sentence structure generation.</p>

La constitución de una memoria terminológica: elaboración de terminologías bilingües en programas de memoria de traducción

Computer-aided translation systems (CAT) based on Translation Memories (TM) are a widely diffused technology that uses database and code-protection features to improve the quality, efficiency and consistency of the human translation process. These systems basically consist of a textual database in which each source sentence of a translation is stored together with the target sentence (this is called a translation memory “unit”). New and changed translation proposals will then be stored in the database for future use. This textual database – the kernel of the system – is combined with a terminological database (TDB), which is used by translators to store independently, terminological equivalences or translation units of particular value.In this paper the authors outline a first draft of a methodology that describes the preparation of a bilingual terminology from – and within – TM applications. The bilingual corpus produced is called the ‘terminological memory’ of the translator.

Do we rely on good-enough processing in reading under auditory and visual noise?

Noise, as part of real-life communication flow, degrades the quality of linguistic input and affects language processing. According to predictions of the noisy-channel model, noisemakes comprehenders rely more on word-level semantics and good-enough processing instead of actual syntactic relations. However, empirical evidence of such qualitative effect of noise on sentence processing is still lacking. For the first time, we investigated the qualitative effect of both auditory (three-talker babble) and visual (short idioms appearing next to target sentence on the screen) noise on sentence reading within one study in two eye-trackingexperiments. In both of them, we used the same stimuli — unambiguous grammatical Russian sentences — and manipulated their semantic plausibility. Our findings suggest that although readers relied on good-enough processing in Russian, neither auditory nor visualnoise qualitatively increased reliance on semantics in sentence comprehension. The only effect of noise was found in reading speed: only without noise, semantically implausible sentences were read slower than semantically plausible ones, as measured by both early and late eye-movement measures. These results do not support the predictions of the noisy-channel model. With regard to quantitative effects, we found a detrimental effect ofauditory noise on overall comprehension accuracy, and an accelerating effect of visual noise on sentence processing without accuracy decrease.

Lexical and syntactic influences on syntactic encoding in written language production by deaf speakers

It remains unclear whether deaf and hearing speakers differ in the processes and representations underlying written language production. Using the structural priming paradigm, this study investigated syntactic and lexical influences on syntactic encoding in writing by deaf speakers of Chinese in comparison with hearing controls. Experiment 1 showed that deaf speakers tended to re-use a prior syntactic structure in written sentence production (i.e., structural priming) to the same extent as hearing speakers did; in addition, such a tendency was enhanced when the target sentence repeated the verb from the prime sentence (i.e., lexical boost) in both deaf and hearing speakers to the same extent. These results suggest that deaf and hearing speakers are similarly affected by syntactic and lexical factors in syntactic encoding in writing. Experiment 2 revealed comparable boosts in structural priming between prime-target pairs with homographic homophone verbs and prime-target pairs with heterographic homophone verbs in hearing speakers, but a boost for prime-target pairs with homographic homophone verbs but not those with heterographic homophone verbs in deaf speakers. These results suggest that while syntactic encoding in writing is influenced by lemma associations developed for homophones as a result of phonological identity in hearing speakers, it is influenced by lemma associations developed for homographs as a result of orthographic identity in deaf speakers. In all, syntactic encoding in writing seems to employ the same syntactic and lexical representations in hearing and deaf speakers, though lexical representations are shaped more by orthography than phonology in deaf speakers.

An Oblivious Approach to Machine Translation Quality Estimation

Machine translation (MT) is being used by millions of people daily, and therefore evaluating the quality of such systems is an important task. While human expert evaluation of MT output remains the most accurate method, it is not scalable by any means. Automatic procedures that perform the task of Machine Translation Quality Estimation (MT-QE) are typically trained on a large corpus of source–target sentence pairs, which are labeled with human judgment scores. Furthermore, the test set is typically drawn from the same distribution as the train. However, recently, interest in low-resource and unsupervised MT-QE has gained momentum. In this paper, we define and study a further restriction of the unsupervised MT-QE setting that we call oblivious MT-QE. Besides having no access no human judgment scores, the algorithm has no access to the test text’s distribution. We propose an oblivious MT-QE system based on a new notion of sentence cohesiveness that we introduce. We tested our system on standard competition datasets for various language pairs. In all cases, the performance of our system was comparable to the performance of the non-oblivious baseline system provided by the competition organizers. Our results suggest that reasonable MT-QE can be carried out even in the restrictive oblivious setting.

Neural correlates of contributions of interpreting training to second language semantic integration

How interpreting training may enhance semantic integration in general language processing (instead of language processing during interpreting) was not clear, and its neural correlates remained unexplored. Two groups of university students with different amounts of interpreting training experience (more-IE and less-IE) performed a second language (L2) reading task, in which the target sentence ended with three types of lateralized words: expected words, words of related semantic violation (related violation), and words of unrelated semantic violation (unrelated violation). N400 responses elicited by the final words were used to index semantic integration. Two major findings suggested potential contributions of interpreting training to L2 semantic integration. First, the more-IE group exhibited smaller N400 amplitudes than the less-IE group for expected words, and no group differences were obtained for the two violations. Second, N400 amplitudes for related violations were generally smaller than those for unrelated violations in the right visual field, and this difference was more fully captured (more broadly distributed over the scalp) in the more-IE group than in the less-IE group. Therefore, smaller N400 amplitudes for expected words but not for violations, and broader scalp distribution of the differences between related and unrelated violations constitute the neural correlates for the potential contributions of interpreting training to general L2 semantic integration. The results also suggest possible connections between different types of language experience.

STRATEGI KESANTUNAN TINDAK TUTUR DIREKTIF WERKUDARA DALAM WAYANG PURWA: ANALISIS POLA PROSODI

Tokoh Werkudara (WR) memiliki kekhasan yang menjadikan tokoh tersebut unik dan berbeda dibanding tokoh lainya dalam pementasan wayang purwa. Secara kebahasaan tokoh WR memiliki gaya berbicara kasar dan tidak pernah berbicara halus, dan cenderung tidak santun terhadap mitra tuturnya. Tujuan penelitian ini adalah mendeskripsikan pola prosodi strategi kesantunan tindak tutur direktif yang dilakukan tokoh Werkudara dalam wayang purwa. Penelitian ini menggunakan data tindak tutur direktif yang dilakukan tokoh Werkudara dalam lakon Dewa Ruci dengan pemilihan kalimat target tindak tutur direktif requestives sub fungsi meminta dengan struktur S-P-Pel aku jaluk pamit dan tindak tutur direktif questions sub fungsi bertanya dengan strutur apa-S?. Sumber penelitian yang digunakan dalam penelitian ini adalah rekaman video pementasan wayang lakon Dewa Ruci oleh Ki Nartosabdo. Data tuturan tersebut diproses dengan menggunakan aplikasi Praat dengan berpedoman pada aturan IPO (Instituut voor Perceptie Onderzoek) guna menggambarkan dan mempersepsikan aspek prosodi dari tuturan Werkudara kepada masing-masing mitratuturnya. Penelitian ini menggunakan teori pragmatik sebagai pisau bedah guna menjelaskan hubungan pola prosodi dalam membangun kesatunan dengan mitra tutur. Hasil penelitian ini dapat dijelaskan tiga pola prosodi dalam tindak tutur direktif Werkudara, yaitu pertama, konteks mitra tutur (+D, +P ‘met’) dalam tuturanya Werkudara menggunakan pola prosodi kontur nada turun atau deklinasi, julat nada tinggi (melodis), dan durasi panjang. Kedua konteks mitra tutur (-D, +P ‘met’) menggunakan pola prosodi kontur nada turun atau deklinasi, julat nada kecil (monoton), dan durasi panjang. Ketiga, konteks mitra tutur (+D, +P ‘mat’) menggunakan pola prosodi kontur nada naik atau inklinasi, julat nada kecil (monoton), dan durasi pendek.Kata kunci: wayang purwa, werkudara, tindak tutur direktif, pola prosodi POLITENESS STRATEGY OF DIRECTIVE SPEECH ACT OF WERKUDARA IN THE WAYANG PURWA: A PROSODIC ANALYSISAbstract The Werkudara (WR) character has a peculiarity that makes this character unique and different from other characters in the shadow-puppet performances. Linguistically, the WR character has a harsh speaking style, never speaks softly, and tends to be disrespectful to his speech partners. The purpose of this study is to describe the prosody pattern of the directive speech acts of the politeness strategy performed by the Werkudara character in the puppet performance. This study uses the directive speech-act data performed by the character Werkudara in Dewa Ruci's play by selecting the target sentence directive speech-act requestives requesting sub-function with the structured target sentences S-P-Pel ‘aku jaluk pamit’ and the directive speech acts question sub-function of asking with the structure what-S?. The research source used in this study was the video recording of the Dewa Ruci puppet performance by Ki Nartosabdo. Furthermore, the speech data is processed using the Praat application guided by the IPO rules (Instituut voor Perceptie Onderzoek) to describe and perceive the prosody aspects of Werkudara's speech to each of his partners. This study uses the pragmatic theory as a tool to explain prosody patterns in building politeness with speech partners. The results of the study indicate the three prosody patterns in the speech acts of the Werkudara as follows. First, the context of the speech partners (+ D, + P 'met') in Werkudara's speech uses the prosody pattern of downward pitch or declination contours, high pitch range (melodic), and long duration. Second, the two contexts of speech partners (-D, + P 'met') use a downward or declination prosody pattern, a small pitch range (monotone), and a long duration. Third, the context of speech partners (+ D, + P 'mat') uses a prosody pattern of rising or inclination contours, small pitch ranges (monotone), and short duration.Keys word: shadow puppet, Werkudara, directive speech acts, prosody patterns.

Using fuzzy string matching for automated assessment of listener transcripts in speech intelligibility studies

Many studies of speech perception assess the intelligibility of spoken sentence stimuli by means of transcription tasks (‘type out what you hear’). The intelligibility of a given stimulus is then often expressed in terms of percentage of words correctly reported from the target sentence. Yet scoring the participants’ raw responses for words correctly identified from the target sentence is a time-consuming task, and hence resource-intensive. Moreover, there is no consensus among speech scientists about what specific protocol to use for the human scoring, limiting the reliability of human scores. The present paper evaluates various forms of fuzzy string matching between participants’ responses and target sentences, as automated metrics of listener transcript accuracy. We demonstrate that one particular metric, the token sort ratio, is a consistent, highly efficient, and accurate metric for automated assessment of listener transcripts, as evidenced by high correlations with human-generated scores (best correlation: r = 0.940) and a strong relationship to acoustic markers of speech intelligibility. Thus, fuzzy string matching provides a practical tool for assessment of listener transcript accuracy in large-scale speech intelligibility studies. See https://tokensortratio.netlify.app for an online implementation.

AUTOMATED SYSTEM FOR DETECTION OF NON-STANDARD ACTIONS USING SCRIPTURAL ANALYSIS OF THE TEXT

The scenario (narrative schemas) is some established (in society) sequence of steps to achieve the set goal and contains the most complete information about all possible ways of development of the described situation (with selection points and branches). The creation of the XML platform gave rise to a new high-tech and technologically more advanced stage in the development of the Web. As a result, the XML platform becomes a significant component in the technology of information systems development, and the tendency of their integration at the level of corporations, agencies, ministries only strengthens the position of XML in the field of information technology in general. A system for automatic detection of non-standard scripts in text messages has been developed. System programming consists of stages of ontology formation, sentence parsing and scenario comparison. the classic natural language processing (NLP) method, which supports the most common tasks such as tokenization, sentence segmentation, tagging of a part of speech, extraction of named entities, partitioning, parsing and co-referential resolution, is used for parsing sentences in the system. Maximum entropy and machine learning based on perceptrons are also possible. Ontologies are stored using OWL technology. The object-target sentence parsers with the described OWL are compared in the analysis process. From a SPARQL query on a source object, query models are returned to the table object. The table class is the base class for all table objects and provides an interface for accessing values in the rows and columns of the results table. If the table object has exactly three columns, it can be used to build a new data source object. This provides a convenient mechanism for retrieving a subset of data from one data source and adding them to another. In the context of the RDF API, a node is defined as all statements about the subject of a URI. The content of the table is compared with the semantics of the sentence. If the sentence scenario does not match the OWL ontology model, there is a possibility of atypical object actions. In this case, a conclusion is formed about the suspicion of the message. For more correct use of possibilities of the analysis of the text it is necessary to form the case of ontologies or to use existing (Akutan, Amazon, etc.) taking into account their features. To increase the ontologies of objects, it is possible to use additional neural network teaching methods.