Unknown Words Research Articles

Reliable Part-of-Speech Tagging of Historical Corpora through Set-Valued Prediction

Syntactic annotation of corpora in the form of part-of-speech (POS) tags is a key requirement for both linguistic research and subsequent automated natural language processing (NLP) tasks. This problem is commonly tackled using machine learning methods, i.e., by training a POS tagger on a sufficiently large corpus of labeled data. While the problem of POS tagging can essentially be considered as solved for modern languages, historical corpora turn out to be much more difficult, especially due to the lack of native speakers and sparsity of training data. Moreover, most texts have no sentences as we know them today, nor a common orthography. These irregularities render the task of automated POS tagging more difficult and error-prone. Under these circumstances, instead of forcing the POS tagger to predict and commit to a single tag, it should be enabled to express its uncertainty. In this paper, we consider POS tagging within the framework of set-valued prediction, which allows the POS tagger to express its uncertainty via predicting a set of candidate POS tags instead of guessing a single one. The goal is to guarantee a high confidence that the correct POS tag is included while keeping the number of candidates small. In our experimental study, we find that extending state-of-the-art POS taggers to set-valued prediction yields more precise and robust taggings, especially for unknown words, i.e., words not occurring in the training data.

BiLSTM-Filt: Neural network for radar word segmentation

Radar word extraction is the analysis foundation for multi-function radars (MFRs) in electronic intelligence (ELINT). Although neural networks enhance performance in radar word extraction, current research still faces challenges from complex electromagnetic environments and unknown radar words. Therefore, in this paper, we propose a promising two-stage radar word extraction framework, consisting of segmentation and recognition. To fill the vacancy of radar word segmentation, we establish the mathematical model from the time series analysis viewpoint and design a novel segmentation neural network based on Bi-direction Long Short-Term Memory with a filter module (BiLSTM-Filt). Specific radar word structure characteristics are extracted by training the network and applied for detecting radar words in the pulse train. To further improve segmentation performance, a bounding box regression method is designed to merge information from sub-region structures. Simulation experiments on a typical MFR, Mercury, reveal that the proposed method can outperform the baseline methods within complex electromagnetic environments, containing corrupted environments, various pulse backgrounds, and variable pulse train lengths. Due to the artificial design structure, the proposed method can also make a trial on unknown radar word segmentation.

Introducing Mr. Three: Attention, Perception, and Meaning Selection in the Acquisition of Number and Color Words.

Children learn their first number words gradually over the course of many months, which is surprising given their ability to discriminate small numerosities. One potential explanation for this is that children are sensitive to the numerical features of stimuli, but don't consider exact cardinality as a primary hypothesis for novel word meanings. To test this, we trained 144 children on a number word they hadn't yet learned, and contrasted this with a condition in which they were merely required to attend to number to identify the word's referent, without encoding number as its meaning. In the first condition, children were trained to find a "giraffe with three spots." In the second condition, children were instead trained to find "Mr. Three", which also named a giraffe with three spots. In both conditions, children had to attend to number to identify the target giraffe, but, because proper nouns refer to individuals rather than their properties, the second condition did not require children to encode number as the meaning of the expression. We found that children were significantly better at identifying the giraffe when it had been labeled with the proper noun than with the number word. This finding contrasted with a second experiment involving color words, in which children (n = 56) were equally successful with a proper noun ("Mr. Purple") and an adjective ("the giraffe with purple spots"). Together, these findings suggest that, for number, but not for color, children's difficulty acquiring new words cannot be solely attributed to problems with attention or perception, but instead may be due to difficulty selecting the correct meaning from their hypothesis space for learning unknown words.

Strategies for Guessing Meaning of English Words among Secondary Schools in Gasabo District, Rwanda

This study focused on morphological strategies that may alleviate the students’ learning of new English words in Gasabo, Rwanda. The study used the descriptive research design. A systematic sampling technique determined three representative schools to participate. The total population in the three schools was 126 students and three teachers from language combinations. The sample of 56 students and three teachers participated through questionnaire and an interview guide. Data analysis took place through descriptive statistics and the thematic approach. Based on the findings, the study concluded that morphology is a vital tool for guessing the meaning of unknown words in English. Therefore, the awareness of morphology is necessary to improve learners’ attention when they predict the meaning of an unknown word. The study recommends that secondary school teachers need to encourage their learners to grasp the meaning of unknown words by identifying their morphemes and context. Teachers of English language should avoid defective educational practices, like teacher-centered activities that attract memorization instead of linguistic skills development strategies. Therefore, this study remains an eye-opening contribution to the linguistic development of teachers.

Comparative Analysis of Deep Learning Models for Part of Speech Tagging in the Malay Language

Despite the widespread use of Malay, under-resourced languages like Malay face challenges in Natural Language Processing (NLP), particularly in Part-of-Speech (POS) tagging. The scarcity of annotated corpora poses a primary obstacle to POS tagging in Malay. This study aims to enhance the effectiveness and reliability of POS tagging models explicitly tailored for under-resourced languages within the field of NLP, focusing on Malay. Existing models, which rely on Conditional Random Fields and Hidden Markov Models, exhibit limitations, underscoring the need for more robust approaches. The research conducts a comparative analysis of various deep-learning models with different encoders for POS tagging in Malay sentences. The experimental analysis demonstrates that the Bidirectional Long Short-Term Memory (Bi-LSTM) model, leveraging a pre-trained Bidirectional Encoder Representations from Transformers (BERT) embedding model, achieves exceptional accuracy, precision, recall, and F1 scores in predicting tags. Notably, the BERT + Bi-LSTM model, boasting an accuracy of 98.82%, outperforms other models, showcasing superior performance across all evaluated metrics. Additionally, this combined model effectively handles known and unknown words, yielding highly accurate POS tagging results for Malay sentences. Doi: 10.28991/HIJ-2024-05-02-04 Full Text: PDF

SENSE RELATION IN VOCABULARY ACQUISITION

Foreign language teachers must select vocabulary carefully to ensure that high quality items are included and provide varied opportunities for practice. Teachers should pay the most prudent attention in organization of lexis for the classroom as to offer as wide a range of practice ideas in order to facilitateeffective learning. Acquiring a large, coloured and nuanced vocabulary knowledge does not imply simply studying a list of words alongside with dictionary definitions. Language diversity implies great possibilities of lexical choice as means of enhancing the effectiveness and accuracy of speech. Modern foreign languages teaching methods should aim at building a broad, deep, rich and flexible vocabulary corpus of words. Grouping of words is based upon similarities and contrasts. Every language has in its lexicon a variety of words, kindred in meaning, but distinct in morphemic composition and usage, ensuring the expression of the most delicate and somehow hidden shades of human perception, thought, feeling and imagination. The use of synonyms and antonyms is a quick and effective way of explaining unknown words and teachers can resort to them as means of describing words’ meanings.

The Impacts of Explicit Strategy Instruction on Reading Performance from Students Perspective: A Case Study

This paper reported on part of a larger study to explore how Vietnamese non-English major students perceived the impacts of explicit strategy instruction (ESI) on reading comprehension. Instruction on reading strategies was conducted for 6 weeks in which students were taught explicitly previewing and predicting, skimming, scanning, guessing the meaning of the unknown words from the context and summarizing strategies. Data were collected from forty-five non-English major students at a university in Vietnam through group interviews and learning reflections. Three semi-structured interviews were conducted in groups of three to four students, and thirty-nine learning reflections were collected to obtain in-depth information about the impact of the ESI. The findings revealed that, after the instruction, the students reported using various reading strategies in four strategy categories, namely problem-solving, global, support and local strategies. In addition, the ESI was perceived to be cognitively beneficial, as students reported heightened awareness of using reading strategies in reading comprehension, expanded reading strategy repertoire, greater reading fluency, and higher reading scores. From a non-cognitive affective perspective, students reported that the ESI motivated them to read with a higher level of confidence and become more autonomous in reading in English. The study offers implications for teachers, students and materials writers in teaching and learning English reading skills in non-English major learning contexts and perhaps in other settings.

The Most Ideal L2 Teaching Method

Though it is possible to see numerous researches on the so-called language teaching methods, there is still a pressing need to study them comparatively and from different angles. The article studies some specific methods with regard to covering language skills, mother tongue usage, usage of cutting-edge technological devices, comprehensibility gain. Besides, there is a strong focus on the conduction of the lesson regarding whether the lesson is student-centered, teacher-centered or self-centered. The aim of the article is to reveal the best language learning method combining the positive features of all language learning criteria. In the study, 20 local and foreign non-English speaking students with B1 level were involved in the experiment. They were divided into four groups which learnt English through a specific method. Most of the participants were locals except 6 who were of Turkish and Iranian origins. Speaking skill of the Iranian students was relatively better in comparison with others. At the end of the experiment, the comprehensibility gain of each group was graded accordingly. The Uniskills method proved to be the most effective and qualitative method compared to other methods in terms of coverage of language skills. The second effective method was CLT which also encompassed all four skills. It was revealed that the usage of mother tongue in English language learning is better than not using it. Since language input makes progress while using native language. Comparing the source and target languages makes a clear picture of language structure in the brain. Operation function is activated and cognitive skills develop significantly. It turned out that the usage of mother tongue in language learning is more effective and the students find the meanings of some unknown words obscure when they don’t use the native language. It became obvious that teacher-centered lesson is more efficient than the student-centered education.

An analysis of customer perception using lexicon-based sentiment analysis of Arabic Texts framework

Sentiment Analysis (SA) employing Natural Language Processing (NLP) is pivotal in determining the positivity and negativity of customer feedback. Although significant research in SA is focused on English texts, there is a growing demand for SA in other widely spoken languages, such as Arabic. This is predominantly due to the global reach of social media which enables users to express opinions on products in any language and, in turn, necessitates a thorough understanding of customers’ perceptions of new products based on social media conversations. However, the current research studies demonstrate inadequacies in furnishing text analysis for comprehending the perceptions of Arabic customers towards coffee and coffee products. Therefore, this study proposes a comprehensive Lexicon-based Sentiment Analysis on Arabic Texts (LSAnArTe) framework applied to social media data, to understand customer perceptions of coffee, a widely consumed product in the Arabic-speaking world. The LSAnArTe Framework incorporates the existing AraSenTi dictionary, an Arabic database of sentiment scores for Arabic words, and lemmatizes unknown words using the Qalasadi open platform. It classifies each word as positive, negative or neutral before conducting sentence-level sentiment classification. Data collected from X (formerly known as Twitter, resulted in a cleaned dataset of 10,769 tweets, is used to validate the proposed framework, which is then compared with Amazon Comprehend. The dataset was annotated manually to ensure maximum accuracy and reliability in validating the proposed LSAnArTe Framework. The results revealed that the proposed LSAnArTe Framework, with an accuracy score of 93.79 %, outperformed the Amazon Comprehend tool, which had an accuracy of 51.90 %.

Exploring Translation Students’ Dictionary Use, Preferences, and Attitudes in Translation Courses

The study aimed to explore translation students’ dictionary use, and preferences in their translation courses. Moreover, it aimed to explore the students’ attitudes toward the dictionary while using it as a major tool in the translation process. To achieve the purpose of the study, a questionnaire was prepared in advance by the researcher. It consisted of 35 items. The quantitative method based on a questionnaire was used in this study. Data were collected by administrating the questionnaire to 84 students, who were purposefully chosen at Isra University in the first semester of the academic year 2023/2024. The results revealed that the participants agreed that they knew how to use an online and a book dictionary in their translation tasks and lessons. Moreover, the results indicated that the majority of them preferred using an online dictionary in their tasks because it was a quick and easy tool that students could deal with in a perfect way to look for difficult or unknown words. In addition, the analysis showed that the majority of the participants agreed that they had a positive attitude toward using different types of dictionaries because they were helpful in doing different tasks in their translation lessons. Finally, the study recommended that students should be provided with enough training and practice on how to use online as well as book dictionaries. In addition, students must be encouraged to depend on the context first to guess the meaning of the new words before they start looking for their meanings using different types of dictionaries.

Deep Learning Model for Tamil Part-of-Speech Tagging

Abstract Part-of-Speech (POS) tagging is one of the popular Natural Language Processing (NLP) tasks. It is also considered to be a preliminary task for other NLP applications such as speech recognition, machine translation, and sentiment analysis. A few works have been published on POS tagging for the Tamil language. However, the performance of the POS tagger with unknown words is not explored in the literature. The appearance of unknown words is a frequently occurring problem in POS tagging and makes it a challenging task. In this paper, we propose a deep learning-based POS tagger for Tamil using Bi-directional Long Short Term Memory (BLSTM). The performance of the POS tagger was evaluated using known and unknown words. The POS tagger with regular word-level embeddings produces 99.83 and 92.46% accuracies for all known and 63.21% unknown words. It clearly shows that the accuracy decreases when the number of unknown words increases. To improve the performance of the POS tagger with unknown words, the proposed BLSTM model that uses word-level, character-level and pre-trained word embeddings. Test results of this model show a 2.57% improvement for 63.21% of unknown words, with an accuracy of 95.03%.

A Study of Interactive Alignment in EFL Reading-to-Writing Continuation Tasks

The reading-to-writing continuation task has been used in the Chinese national matriculation English test due to its apparent interactive alignment effect. But empirical studies of the alignment effect and how it happens are limited. Herein, this paper reports on a study following Wang’s (2015) research to investigate whether this interactive alignment effect actually occurs in EFL learning and how it functions in continuation tasks with the think-aloud method to collect qualitative data from two participants. The participants’ continuation works were analyzed and interviews were carried out to obtain information about their thinking process. The results show that there are strong connections between what students read and their continuation writing. The results confirm that there is an alignment effect at both the content and language levels in continuation tasks. Readers consciously tend to align the content of their writing with that of the original text across five dimensions: entity (person and object), time, space, causation/causality, and motivation/intentionality. Meanwhile, language alignment is highly related to the act of rereading, which enables the would-be writer to look for the certain vocabulary, learn the grammatical structures, and check for the unknown words. The continuation task facilitates various interactions among the text, the reader, and their resulting writing work. Furthermore, learners use strategies like rereading and “mining” that enable them to engage in creative expression in the writing tasks. This study theoretically highlights the importance of alignment effect in language learning and has practical implications for using CT in reading-to-writing task design and writing pedagogy in EFL classrooms. Teachers can design and use continuation tasks to promote students’ reading ability and overall language development.

Exploring L2 learners’ processing of unknown words during subtitled viewing through self-reports

Abstract Studies have shown the benefits of subtitled viewing for incidental vocabulary learning, but the effects of different subtitling types varied across studies. The effectiveness of different types of subtitled viewing could be related to how unknown vocabulary is processed during viewing. However, no studies have investigated L2 learners’ processing of unknown words in viewing beyond exploring learners’ attention allocation. The present research followed a qualitative approach to explore L2 learners’ processing of unknown words during subtitled viewing under three conditions (i.e., captions, L1 subtitles, and bilingual subtitles) by tapping into learners’ reported awareness of the unknown words and the vocabulary processing strategies used to engage with unknown words. According to stimulated recall data (elicited by eye-tracking data) from 45 intermediate-to-advanced-level Chinese learners of English, captions led to increased awareness of the unknown words. Moreover, the types of strategies learners used to cope with unknown vocabulary were determined by subtitling type.

Vocabulary acquisition in the language classroom: what it is, how it works, which strategies and approaches are suitable for Latin instruction

Abstract This paper aims to guide the training of all Latin instructors and learners who want to optimise the process of acquiring the language by applying the results of research carried out in the field of Second Language Acquisition (SLA), specifically here those related to the acquisition of vocabulary. Consequently, some theoretical considerations on the psycholinguistic operations that govern vocabulary learning are first offered, in order to build a better understanding of language acquisition and to make instructors and learners more knowledgeable about the vocabulary learning process, from the noticing of an unknown word and its integration into the subject's competence to the expansion and development of knowledge about the acquired words. The theoretical aspects of vocabulary learning will be illustrated at all times with practical examples taken from methods and books for learning Latin, as well as, in the fourth section, with a wide catalogue of practical advice – must-do items for the class – that can be easily implemented by Latin instructors.

Exploring Gender Based Listening Anxieties in Computer Based IELTS Tests: An In-depth Investigation

The current study investigates diverse listening anxieties experienced by both genders during the computer-based IELTS listening test. Three key anxieties are examined: cognitive and physical stress, pronunciation and accent challenges, and language and vocabulary knowledge issues. A notable difference in responses between genders is observed, with females exhibiting increased anxiety levels when listening and typing simultaneously. In contrast, males face challenges comprehending different accents within the same audio. Both genders express significant apprehension regarding encountering unknown words. Employing a quantitative approach, the study analyses data from 88 participants who have recently appeared in the Computer-Based IELTS exam. Descriptive statistics serve as the primary analytical tool. Results indicate that the transition to screen-based IELTS introduces a few challenges for students accustomed to paper-based testing, exacerbating existing anxieties. The study advocates for integrating realistic practice tests into classroom curricula to alleviate screen related fears and prepare students for the exam environment. This research sheds light on the nuanced dynamics of listening anxieties in screen-based testing contexts, providing insights for educators and test administrators to enhance student preparation and performance.

An Adaptive Harmony Search Part-of-Speech tagger for Square Hmong Corpus

Data-driven models perform poorly on part-of-speech tagging problems with the square Hmong language, a low-resource corpus. This paper designs a weight evaluation function to reduce the influence of unknown words. It proposes an improved harmony search algorithm utilizing the roulette and local evaluation strategies for handling the square Hmong part-of-speech tagging problem. The experiment shows that the average accuracy of the proposed model is 6%, 8% more than HMM and BiLSTM-CRF models, respectively. Meanwhile, the average F1 of the proposed model is also 6%, 3% more than HMM and BiLSTM-CRF models, respectively.

Challenging The Students by Using Video Movie to Improve Students’ Vocabulary on Independent Curriculum

Based on Independent Curriculum in Indonesia, the goal of teaching learning at junior high school is that the students must be able to develop communicative competence in written as well as in spoken form. The use of video movie was chosen as video is an appropriate media to stimulate and motivate the students’ interest and attention in understanding the unknown words since video makes language more alive and meaningful and helps to bring the real worlds into classroom. This study is Classroom Action Research (CAR) study, means applied 2 cycles. The result shown, cycle 1, there were 18 students (54.54%) who gained score ≥ 55, while in cycle 2 there were 32 students (96 %) who gained score ≥ 60. For the learning process, that is, the students’ activities, there were only 23 students (66%) who did 80% of the activities in cycle 1, but there were 32 students (96%) who did 80% of the activities in cycle 2. Meanwhile, for the teacher’s performance, the teacher got score 62 in cycle 1, then she got 84 in cycle 2 which means that she could teach the students well after implementing the use of video movie.

The effects of NMT as a de facto dictionary on vocabulary learning: a comparison of three look-up conditions

Many language learners have reported using Neural machine translation (NMT) such as Google Translate as a reference tool for writing production or as a dictionary substitute to facilitate reading comprehension. Although increasing evidence has suggested that editing with NMT can help learners make improvement on the vocabulary level, no study has explored how consulting NMT for unknown vocabulary may impact the retention of word meaning compared to more conventional look-up conditions. Using a 3 × 3 quasi-experimental design, this study investigated the extent to which the use of NMT to learn unknown target words during reading comprehension activities yielded vocabulary retention compared to that of an online dictionary and how the findings varied by learners’ proficiency levels. The research questions focused on the comparison of the outcomes of three different look-up conditions: (1) NMT word search, (2) NMT sentence search, and (3) online dictionary search. ANOVA results showed that learners who performed online dictionary search and NMT sentence search demonstrated significantly higher levels of word retention than those who carried out NMT single-word search, and the same pattern was observed regardless of their proficiency levels.

An AN ANALYSIS OF TRANSLATION ERROR MADE BY STUDENTS AT THE SIXTH SEMESTER OF ENGLISH DEPARTMENT IN IKIP MUHAMMADIYAH MAUMERE

The research aims to describe the kinds of translation errors made by Students at the Sixth Semester of English Department in IKIP Muhammadiyah Maumere. The method used in the research was descriptive qualitative. The subject of the research was the sixth semester students from English Department. The translation text consisting of 1 paragraphs (source texts) and all of it’s’ translations in English (the target texts) were used in the research to find out the translation errors. Then the researchers classified them into 5 kinds of translation errors according to Vilar et al. (2006, p. 698). The results of the research revealed that there were 241 translation errors found in students’ translation. There were translation errors in the form of incorrect word (35, 6%), punctuation (11, 6%), missing word (30, 7 %), word order (15, 3%), and unknown words (6, 6%). In conclusion, the three most prominent error categories made by the students were incorrect word, punctuation and missing word errors.

Processing of emotional connotations in Chinese monomorphic and compound words reflected by the early posterior negativity.

Writing stands as one of humanity's most profound inventions, facilitating the efficient sharing and transmission of vast amounts of information. Similar to images and facial expressions, visual (written) words possess the ability to evoke emotional connotations. Understanding how the brain perceives these emotional nuances encoded in highly symbolic visual words is a key focus of the emerging field of "affective neurolinguistics." At the core of this inquiry lies the examination of the early posterior negativity (EPN), an event-related potentials (ERPs) component peaking around 300 ms after stimulus onset in the occipitotemporal scalp region. EPN has consistently emerged in response to emotional stimuli, encompassing pictures, faces, and visual words. However, prior research has notably lacked observation of EPN in response to Chinese emotional words, raising questions about potential differences in emotional processing between Chinese and other languages. Given the logographic nature of the Chinese writing system and the prevalence of compound words in the Chinese lexicon, this study aims to explore whether the emotional processing of Chinese monomorphic and compound words elicits an EPN response. Two experiments were conducted: Experiment 1 utilized one-character words (monomorphic words), while Experiment 2 employed two-character words (compound words). Participants were assigned a go/no-go task, instructed to respond to unknown words (word recognition task) or blue stimuli (color decision task). Data analysis using a data-driven mass univariate approach revealed significant ERP differences between emotional and neutral words. Notably, the time course, scalp topography, and cortical generators of the difference ERP presented a characteristic EPN response in both experiments. These findings strongly support the notion that the processing of emotional connotations in both Chinese monomorphic and compound words is reflected by the EPN, paving the way for future research using EPN as an emotion-related ERP component for investigating emotional processing of Chinese words.