Standard Dictionary Research Articles

Soft hearts and hard souls

AbstractOne of the most fundamental claims of the Cognitive Theory of Metaphor is the direction of mapping from concrete to abstract. The pervasiveness of this path of semantic change has been widely accepted among researchers interested in the study of the history and development of emotional expressions. Whereas most studies focus on the analysis of one specific target domain (i.e., one emotion or one family of emotions), less attention has been paid to the reconstruction and analysis of the set of diachronic changes that affected one single source domain. Within this framework, in this paper I have used data extracted from standard Old English dictionaries and thesauri, in order to propose a complete analysis of the set of Old English adjectives for different textural properties of physical objects (such as roughness, smoothness, softness and hardness). I am especially interested in the reconstruction and analysis of the paths of semantic change (from concrete to abstract) illustrated by this section of the Old English vocabulary. Broadly speaking, apart from the original senses for physical texture, these adjectives developed secondary meanings in the fields of feelings and emotions, which I have classified into three categories:physical sensations(such as weakness and pleasantness),sensorial sensations(such as auditive, visual or gustative sensations) andemotional sensations(such as grief, anger, compassion and empathy). Furthermore, the resulting figurative meanings (which I have analysed in terms of metonymic, synaesthetic and metaphoric extensions) can also be grouped into positive and negative sensations. The present paper supports the idea that the origin of our understanding of abstract concepts is deeply rooted in our physical experiences. This is indeed a conceptual pattern showed by the diachronic evolution of Old English adjectives for texture. This paper concludes with some remarks on the social and cultural changes that prompted some of these semantic changes, paying special attention to the Christianization of Anglo-Saxon England and the introduction of Christian values.

Near Synonymy Analysis of Three Adverbials: Surprisingly, Astonishingly and Amazingly

The purpose of this study is to investigate the extent of the similarities and differences among one-word adverbials (surprisingly, astonishingly, amazingly) in terms of meaning, register and collocational constraints. These adverbials are considered roughly synonymous of one another. But we should be skeptical about their full synonymy, though their dictionary meanings show that these words can be substitutable with one another. In order to demonstrate the extent of the similarities in terms of their meanings, three standard dictionaries of English were used. As for the extent of the differences in terms of their meanings, two dictionaries of synonymy discriminations were used. Also, the Corpus of Contemporary American English (COCA) was analyzed to provide further understanding to the differences among these words in terms of meaning, register and collocational constraints. According to the findings, though these words were given as interchangeable in meaning and considered synonyms of one another, they were actually not completely substitutable with one another. Rather, they differ in their shades of meanings. That is why these three words should be considered as near-synonyms. Also, the findings revealed that these three words differed from one another in terms of frequency of occurrences and the frequency of use across registers to a great extent. Finally, the findings showed that these three words mostly collocate with enough as post-modifier. However, only surprisingly collocate with not as pre-modifier.

Morphological Process of COVID-19 Neologisms: A Study of Compounding

This study investigates the compounding process in COVID-19 neologisms. It focuses on words that coexist with words synonymous with the COVID-19 pandemic and the level of public understanding of neologisms that will enter general acceptance through standard English dictionaries. This research is qualitative research. The data comes from Urban Dictionary as a non-standard dictionary involving the community as neologism makers. Data was collected from the first confirmed case of COVID-19 in China on December 8, 2019 to January 31, 2022. Each neologism that resulted from the compounding process with two constituent words was collected to get the most widely used identical word, then compounding by including these words would be analysed to know the results and also the score. We have been found that the lower the score obtained by neologisms with match results, the greater the expectation that neologisms can be accepted by the general public as a global language through standard English dictionaries. Vice versa, the higher the score obtained by neologisms, the smaller the expectations of neologisms can be accepted. However, neologisms with mismatch results are difficult to accept, and even the resulting scores cannot predict anything. Another fact that was found was the error result as a result of the absence of the definition referred to in the standard dictionary. From the overall analysis, nouns are the most used word class.

Technology Focus: Intelligent Operations (May 2022)

The trend of increasing automation and integration of digital work flows continues in all disciplines within the industry. An obvious driver is the increasing digital nature of our world; today’s phones and tablets connected to the cloud perhaps have more computing capabilities than supercomputers from 5 or 10 years ago. Another key driver, arguably the reason why intelligent operations came on the radar of most companies, is being able to improve safety and efficiency in the complex operations that are routinely performed in the oil patch. The last couple of years, I have highlighted efforts around remote operations of fields, smart wells, and the acquisition and integration of real-time data. This year, I have focused on recent drilling-related papers that highlight how safety and performance can be improved with more intelligent operations. Paper SPE 208711 discusses a key requirement I see for successful intelligent operations, especially when the operations span disciplines and companies. Having a standard, consistent, and unambiguous lexicon is critical for automation and digital work flows. This paper highlights an effort to spur the standardization of codes across companies to describe drilling, completions, and other well activities. Anybody who has gone through old well files will recognize immediately the value and the need for such standardization of well activity codes. The other two papers (SPE 208764 and SPE 208784) highlight how automation can lead to increased safety on rigs during operations. Companies are using a combination of cameras, wearables, and other technology to monitor personnel in safety zones on rigs to ensure no one is unknowingly in the wrong spot at the wrong time. A familiar analog to this would be the safety improvements in driving because of collision-avoidance systems in cars (where a combination of technologies including cameras, radar, and lidar are used). Standardization of Well Activity Codes. - Paper SPE 208711 describes the efforts of one operator to standardize well activity reporting codes. A key highlighted improvement is a new coding system that captures both what was done (the typical focus of historical well activity codes) and the broader context on why the activity was performed. The new codes have enabled more granular tracking of performance metrics and a simplification of reporting. Significantly, the operator has recognized the need for a standardized set of codes across the industry and has donated the codes they have developed to an industrywide open-source environment. I hope this spurs wider adoption and refinement of reporting standards across the industry. Using Computer Vision To Monitor Safety Zones and Automate Drillpipe Tallies. - Paper SPE 208764 highlights how digitalization can result in safer operations and improved accuracy through the automation of manual tasks. The paper discusses a computer vision system coupled with a neural network model that detects if any personnel are within a restricted pipe-delivery red zone at an unsafe time and sets off an audible warning alarm. The paper also describes how the use of multiple cameras on different levels of the mast automates the measurement and tallying of the drillpipe being run into the hole. Both these aspects have enhanced existing processes (such as the use of buffer zones and barricades and the manual counting of drill pipe) to further improve safety and accuracy. This article in JPT might also be of interest. Automatic Kick Detection and Dynamic Well Monitoring. - Paper SPE 208784 discusses how to reduce the time gap between when drilling operators detect a kick and when they activate the blowout preventers (BOPs). The paper identifies accurate positioning of the drillstring before activating BOPs as a critical step that affects the time gap. The paper describes an architecture that allows automation of the space-out operation and achieves quick and accurate positioning of the tool joint with minimum movement of the drillstring. A critical enabler that the authors describe is being aware in real time of the depth of each tool joint in the wellbore.

Landscape of esophageal submucosal tunneling endoscopic resection-related adverse events in a standardized lexicon: a large volume of 1701 cases.

Submucosal tunneling endoscopic resection (STER) has been widely applied for esophageal submucosal tumors. This large volume study aims to provide a standard landscape of STER-related AEs for reference. 1701 patients with esophageal SMTs undergoing STER were included at Zhongshan Hospital, Fudan University. Data of clinical characteristics and adverse events were collected and analyzed in depth. Adverse events were recorded by ASGE lexicon and graded by ASGE grading/Clavien-Dindo system. Risk factors for major AEs were analyzed by univariate and multivariate logistic regression. Three hundred and twenty (18.8%) patients with 962 cases of adverse events were observed. Accordingly, 84 (5.0%) were classified as major AEs (moderate and severe) by ASGE grading and 37 (2.2%) were classified as major AEs (grades III-V) by Clavien-Dindo grading. First 1 year operation, distance>6cm from incision to tumor, piecemeal resection, partially extraluminal location, mucosal injury, and operation time>60min were included in the risk score model for major AEs of STER, with 57.1% sensitivity and 87.5% specificity. STER was a safe procedure for diagnosis and treatment of esophageal SMTs with a total 18.8% incidence of AEs, among which only 5.0% were major AEs requiring therapeutic measurements.

Evaluation of the NANDA International, Inc. diagnostic classification in Spain: Development and validation of the EVALUAN-I tool.

To develop and validate a tool to evaluate the NANDA International, Inc. diagnostic classification. The tool, EVALUAN-I, was validated in a non-probabilistic sample (N = 460) on Spanish Registered Nurses (September-December 2019) in two phases. First, design and construct the instrument in three steps: (1) literature review to define the construct focusing on the orientation toward nursing concepts and theoretical foundations, the level of scientific evidence, the structural configuration, the applicability, the nurses' clinical reasoning skills, and the attitudes toward nursing diagnosis, (2) substantiation of the questionnaire items and design according to the criteria for a diagnostic classification, (3) expert test to establish the face validity and content validity. The second phase revolved around (4) conducting a pilot test and measuring the temporal stability (test-retest) and Cohen's kappa coefficient; assessing psychometric properties by measuring (5) reliability (internal consistency using Cronbach alpha and interfactor correlation) and (6) construct validity (exploratory and confirmatory factor analysis). The manuscript follows the STROBE checklist. The study was approved by the Research Ethics Committee with registration number 2019-190-1. EVALUAN-I displayed moderate test-retest stability, adequate construct validity, and excellent reliability. The confirmatory factor analysis provided evidence about the configuration of EVALUAN-I in relation to nine analytical dimensions: clinical competence, nurses' reasoning skills, attitudes towards nursing diagnosis, discipline's central concepts, classification's contents, physiopathological attributes, level of scientific evidence, diagnostic precision, and conceptual correspondence between terminologies. EVALUAN-I is a valid and reliable instrument, which can be used to improve the epistemological, normative, and intuitive configuration of NANDA International, Inc. in a structured, systematic manner. Comprehensive evaluation of NANDA International, Inc. in different clinical settings around the world using a validated instrument, like EVALUAN-I, would allow strengths and weaknesses to be identified and contribute to the classification's development and practical application.

Liver imaging: it is time to adopt standardized terminology.

Liver imaging plays a vital role in the management of patients at risk for hepatocellular carcinoma (HCC); however, progress in the field is challenged by nonuniform and inconsistent terminology in the published literature. The Steering Committee of the American College of Radiology (ACR)'s Liver Imaging Reporting And Data System (LI-RADS), in conjunction with the LI-RADS Lexicon Writing Group and the LI-RADS International Working Group, present this consensus document to establish a single universal liver imaging lexicon. The lexicon is intended for use in research, education, and clinical care of patients at risk for HCC (i.e., the LI-RADS population) and in the general population (i.e., even when LI-RADS algorithms are not applicable). We anticipate that the universal adoption of this lexicon will provide research, educational, and clinical benefits. KEY POINTS: •To standardize terminology, we encourage authors of research and educational materials on liver imaging to use the standardized LI-RADS Lexicon. •We encourage reviewers to promote the use of the standardized LI-RADS Lexicon for publications on liver imaging. •We encourage radiologists to use the standardized LI-RADS Lexicon for liver imaging in clinical care.

A Rule-Based Grammar and Spell Checking

Rule-Based Grammar and spell checking is the task of checking the content of any specific language using a particular set of rules for their grammar and a set of spellings for spell checking. In this work, libraries and functions of Python useful for Natural Language Processing are used to perform grammar and Spell checking. Python Libraries NLTK (for Sentence Boundary Detection and POS tagging), pyEnchant (for Spell checking by comparing with a standard dictionary), and Inflect (for indefinite article). The article includes information about these libraries, techniques, and steps used for Grammar and Spell Check.

The Differences of Pati and Kudus Dialect: Dialectological Studies

Dialectology is the study of dialects or the study of language variations. Kudus and Pati are two neighbouring towns. Even though the towns are close, there are many different dialects between the two. The objectives of this study are to find out the characteristics and the differences between Pati and Kudus dialect. The research design is descriptive qualitative method and the data collection method to get the data are simak, interview and introspective methods. The results of this study show that there are some differences in both dialects. The dialect variations which occurs in both observation areas are phonological differences which consist of the process of vowel and consonant change, morphological differences with the affixation differences, syntax differences for affirmation, and lexical differences in which the different words have the same meaning. The research gives contribution to the development of local language, especially Javanese related to the Javanese teaching at school, so that it will make the teaching and learning process getting easier in Kudus and Pati. Meanwhile for practical contribution, it completes Javanese standard and Javanese dictionary.

An Empirical Performance Analysis of the Speak Correct Computerized Interface

The way in which people speak reveals a lot about where they are from, where they were raised, and also where they have recently lived. When communicating in a foreign language or second language, accents from one’s first language are likely to emerge, giving an individual a ‘strange’ accent. This is a great and challenging problem. Not particularly, because it is a part of one’s personality that they do not have to give up. It is only challenging when pronunciation causes a disruption in communication between an individual and the individuals with whom they are speaking. Making oneself understandable is the goal of perfecting English pronunciations. Many people require their pronunciation to be perfect, such as those individuals working in the healthcare industry, where it is rather critical that each term be read precisely. Speak Correct offers each of its users a service that assists them with any English pronunciation concerns that may arise. Some of the pronunciation improvements will only apply to a specific customer’s dictionary; however, in some cases, the modifications can be applied to the standard dictionary as well, benefiting our whole customer base. Speak Correct is a computerized linguist interface that can assist its users in many different places around the world with their English pronunciation issues due to Saudi or Egyptian accents. In this study, the authors carry out an empirical investigation of the Speak Correct computerized interface to assess its performance. The results of this research reveal that Speak Correct is highly effective at delivering pronunciation correction.

Auto-CORPus: A Natural Language Processing Tool for Standardizing and Reusing Biomedical Literature.

To analyse large corpora using machine learning and other Natural Language Processing (NLP) algorithms, the corpora need to be standardized. The BioC format is a community-driven simple data structure for sharing text and annotations, however there is limited access to biomedical literature in BioC format and a lack of bioinformatics tools to convert online publication HTML formats to BioC. We present Auto-CORPus (Automated pipeline for Consistent Outputs from Research Publications), a novel NLP tool for the standardization and conversion of publication HTML and table image files to three convenient machine-interpretable outputs to support biomedical text analytics. Firstly, Auto-CORPus can be configured to convert HTML from various publication sources to BioC. To standardize the description of heterogenous publication sections, the Information Artifact Ontology is used to annotate each section within the BioC output. Secondly, Auto-CORPus transforms publication tables to a JSON format to store, exchange and annotate table data between text analytics systems. The BioC specification does not include a data structure for representing publication table data, so we present a JSON format for sharing table content and metadata. Inline tables within full-text HTML files and linked tables within separate HTML files are processed and converted to machine-interpretable table JSON format. Finally, Auto-CORPus extracts abbreviations declared within publication text and provides an abbreviations JSON output that relates an abbreviation with the full definition. This abbreviation collection supports text mining tasks such as named entity recognition by including abbreviations unique to individual publications that are not contained within standard bio-ontologies and dictionaries. The Auto-CORPus package is freely available with detailed instructions from GitHub at: https://github.com/omicsNLP/Auto-CORPus.

Sensory descriptors for pulses and pulse-derived ingredients: Toward a standardized lexicon and sensory wheel.

The organoleptic quality of pulses and their derived ingredients is fundamental in human utilization and evolution of food. However, the widespread use of pulses is hindered by their inherent sensorial aspects, which are regarded as atypical by the consumers who are unfamiliar to them. In most studies involving sensory assessment of pulses and pulse-ingredients using classical descriptive analysis methods, assessors establish their own lexica. This review is a synthesis of descriptive terms by which sensations emanating from pea, chickpea, lentil, faba bean, dry bean, bambara groundnut, lupin, pigeon pea and cowpea, and their derived ingredients have been described in the literature. Studies involving sensory assessment of processed whole seeds, slurries of raw flour, slurries of protein extracted from raw flour, and food products containing components of pulses were considered. The terms are categorized into those denoting basic taste, aroma, flavor, and trigeminal sensations. Bitterness is the most widely perceived basic taste. Beany, which is broad and complex with subcharacter notes, is predominantly used to describe aroma and flavor. The frequency of use of the collated terms in the reviewed studies was used to establish a sensory wheel. Inconsistency in the use of descriptive terms in the literature necessitates establishment of a standard lexicon that can be applied in both classical and increasingly popular rapid descriptive methods (e.g., check-all-that-apply) throughout the pulse value chain. This review is timely considering the dominance of pulses in plant-based foods and their increasing appeal to the food industry.

Evaluating the Effectiveness of a Conservation Project on Two Threatened Birds: Applying Expert-Based Threat Analysis and Threat Reduction Assessment in a Mediterranean Wetland

We applied two recent approaches largely used in biological conservation: Threat Analysis (TAN) and Threat Reduction Assessments (TRAs), assessing the effectiveness of a project focused on two water-related bird species (common tern, Sterna hirundo and little tern, Sternula albifrons), commonly breeding in some wetlands of Italy. We used the IUCN standardized lexicon for the classification of threats, utilizing a panel of experts to assess a set of regime attributes (extent, severity and magnitude) of each human-induced disturbance. Our aims were: (i) through the TAN approach, to carry out an arrangement and quantification of the main threats acting on our focal species and select the priority ones; (ii) through the TRA approach, to test the effectiveness of an operational project focused on mitigating the threats and improving the breeding success of species (i.e., building rafts and floating islands to encourage their nesting). Using the TAN approach, experts identified the following human-induced threats (IUCN code): 6.1—Generic disturbance; 7.2—Water stress; 7.3—Salinization; 8.8—Vagrant dogs; 8.8—Mediterranean gulls; 8.8—Wild boars, all significantly different in their magnitude. Among them, wild boars and Mediterranean gulls appeared the priority threats with the greatest extent, intensity and magnitude. Using the TRA approach, after the project, we assessed an overall decrease in the threat magnitude of 23.08% (21.42% when considering only the threats directly affected by our project). These data suggest that further efforts should be devoted to achieving greater effectiveness of conservation actions focused on our target species. With limited time and resources to quantify threats, expert-based approaches could be useful for rapidly assessing the effectiveness of small conservation projects by providing a range of scores obtained following an analytical procedure. In this regard, Threat Analysis and Threat Reduction Assessment could be considered useful tools to support adaptive management in project management cycles.

Circumventing the curse of dimensionality in magnetic resonance fingerprinting through a deep learning approach.

Magnetic resonance fingerprinting (MRF) is a rapidly developing approach for fast quantitative MRI. A typical drawback of dictionary-based MRF is an explosion of the dictionary size as a function of the number of reconstructed parameters, according to the "curse of dimensionality", which determines an explosion of resource requirements. Neural networks (NNs) have been proposed as a feasible alternative, but this approach is still in its infancy. In this work, we design a deep learning approach to MRF using a fully connected network (FCN). In the first part we investigate, by means of simulations, how the NN performance scales with the number of parameters to be retrieved in comparison with the standard dictionary approach. Four MRF sequences were considered: IR-FISP, bSSFP, IR-FISP-B1 , and IR-bSSFP-B1 , the latter two designed to be more specific for parameter encoding. Estimation accuracy, memory usage, and computational time required to perform the estimation task were considered to compare the scalability capabilities of the dictionary-based and the NN approaches. In the second part we study optimal training procedures by including different data augmentation and preprocessing strategies during training to achieve better accuracy and robustness to noise and undersampling artifacts. The study is conducted using the IR-FISP MRF sequence exploiting both simulations and in vivo acquisitions. Results demonstrate that the NN approach outperforms the dictionary-based approach in terms of scalability capabilities. Results also allow us to heuristically determine the optimal training strategy to make an FCN able to predict T1 , T2 , and M0 maps that are in good agreement with those obtained with the original dictionary approach. k-SVD denoising is proposed and found to be critical as a preprocessing step to handle undersampled data.

Signed Languages: A Triangular Semiotic Dimension.

Since the beginning of signed language research, the linguistic units have been divided into conventional, standard and fixed signs, all of which were considered as the core of the language, and iconic and productive signs, put at the edge of language. In the present paper, we will review different models proposed by signed language researchers over the years to describe the signed lexicon, showing how to overcome the hierarchical division between standard and productive lexicon. Drawing from the semiotic insights of Peirce we proposed to look at signs as a triadic construction built on symbolic, iconic, and indexical features. In our model, the different iconic, symbolic, and indexical features of signs are seen as the three sides of the same triangle, detectable in the single linguistic sign (Capirci, 2018; Puupponen, 2019). The key aspect is that the dominance of the feature will determine the different use of the linguistic unit, as we will show with examples from different discourse types (narratives, conference talks, poems, a theater monolog).

Aspekte van vernuwing in die Afrikaanse leksikografie: Standaard- en pedagogiese woordeboeke as barometer

Innovative Aspects of Afrikaans Lexicography: Standard and Pedagogical Dictionaries as Barometer. The aim of this contribution is to offer an overview of the areas of most significant innovation in the Afrikaans lexicography over the past two decades, with specific reference to standard and pedagogical dictionaries, since they represent the typological categories in which most development is visible. However, reference will also be made to other dictionary types and contexts where relevant. Firstly, the current state of affairs with regard to the Afrikaans lexicography will be outlined in terms of existing lexicographic products. Secondly, some comments will be offered on the professionalisation of Afrikaans lexicography — a topic which has not really been dealt with in metalexicographical research. The roles of the Bureau of the Woordeboek van die Afrikaanse Taal and commercial dictionary publishers will also be highlighted. Thereafter, secondary and specific lexicographic processes will be discussed, with reference to corpus lexicography and lemma selection, macrostructural innovation, and microstructural innovation. The discussion of the latter will include integrated microstructures in bilingual dictionaries, lexicographic definitions in monolingual dictionaries, cotext entries, and aspects of grammatical data. The state of affairs and future of the Afrikaans e-lexicography will also be addressed. Finally, some comments on special dictionaries will be offered. Keywords: commercial lexicography, corpus lexicography, e-lexicography, explanatory dictionary, lexicographic definition, macrostructure, microstructure, pedagogical lexicography, school dictionary, translation dictionary

Guske, daske i drolje - semantička derogacija žene u francuskom i srpskom žargonu

The paper uses a cognitive linguistic approach to analyse slang lexemes derogatively denoting and qualifying women in two languages neither genealogically close nor in direct contact. Starting from the conceptual metaphor theory and the linguocultural approach, our aim is to determine the similarities and differences related to the cultural knowledge about the concept of women in French and Serbian culture. Our research corpus encompasses examples excerpted from French and Serbian slang and standard dictionaries. The analysis shows that most of the slang expressions that derisively qualify women emphasise physical appearance, intellectual characteristics, and forms of behaviour that the sociolinguistic community assesses as unacceptable and undesirable. The results confirm the deeply rooted and widespread prevalence of collective prejudice, generalisations, stereotypes, and the tendency to marginalise women.

Standardized Gaussian Dictionary for ECG Analysis a Metrological Approach

An approach based on dictionary-based Gaussian decomposition of electrocardiogram (ECG) traces is presented and characterized, and its performance potential is demonstrated using traces from the MIT-BIH Arrythmia Database. A Gaussian model is employed to describe ECG morphology. Parameters are estimated using a dictionary-based approach, that is purposely designed to obtain accurate representations with limited complexity and ensure comparability among different traces and subjects. The standardized Gaussian dictionary allows compact representations, enhances comparability and provides the support for machine learning-based diagnostics of ECG traces. Data-oriented large-scale medical analyses of ECG data are made possible, allowing the investigation of elusive cardiac phenomena and personalized diagnostics.

Mlphon: A Multifunctional Grapheme-Phoneme Conversion Tool Using Finite State Transducers

In this article we present the design and the development of a knowledge based computational linguistic tool, Mlphon [em.el.foːɳ] for Malayalam language. Mlphon computationally models linguistic rules using finite state transducers and performs multiple functions including grapheme to phoneme (g2p) and phoneme to grapheme (p2g) conversions, syllabification, phonetic feature analysis and script grammar check. This open source software tool, released under MIT license, is developed as a one-stop solution to handle different speech related text processing tasks for automatic speech recognition, text to speech synthesis and non-speech natural language processing tasks including syllable subword based language modeling, phoneme diversity analysis and text sanity check. The tool is evaluated on a manually crafted gold standard lexicon. Mlphon performs orthographic syllabification with 99% accuracy with a syllable error rate of 0.62% on the gold standard lexicon. For grapheme to phoneme conversion task, overall phoneme recognition accuracy of 99% with a phoneme error rate of 0.55% is obtained on gold standard lexicon. Additionally an extrinsic evaluation of Mlphon is performed by employing the pronunciation lexicon created using Mlphon, in Malayalam automatic speech recognition (ASR) task. Performance analysis in terms of the computation time of lexicon creation process and the word error rate (WER) on ASR task are presented along with a comparison over other automated tools for lexicon creation. Pronunciation lexicons with more than 100k commonly used Malayalam words in phonemised and syllabified forms is created and they are published as open language resources along with this work. We also demonstrate the usage of Mlphon on different natural language processing applications - syllable subword ASR, assisted pronunciation learning, phoneme diversity analysis and text sanity check. Being a knowledge based solution with open source code, Mlphon can be adapted to other languages of similar script nature.

C. Louis Leipoldt se bydrae tot die materiaalversameling van J.J. Smith se Afrikaanse standaardwoordeboek

C. Louis Leipoldt's Contribution to the Collection of Materials for J.J. Smith's Afrikaans Standard Dictionary. The friendship between Smith and Leipoldt originated during their years of study in London. This led to Leipoldt showing some of his poems to Smith. Oom Gert vertel en ander gedigte with an introduction by Smith was the first poetry collection by Leipoldt. Subsequent collections of his were linguistically edited by Smith. J.C. Kannemeyer writes extensively about this in his biography of Leipoldt. When Smith started with the collection of materials for the Afrikaans standard dictionary, Leipoldt on a smaller scale made contributions with the elucidation of plant and animal names, and folk medicine. This article discusses a representative collection of this material with regard to kind, method, etc. Keywords: Afrikaans standard dictionary, plant names, animal names, folk medicine