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Found 28 papers, 3 papers with code
Detecting Trending Terms in Cybersecurity Forum Discussions
We present a lightweight method for identifying currently trending terms in relation to a known prior of terms, using a weighted log-odds ratio with an informative prior.
Towards an open-domain chatbot for language practice
State-of-the-art chatbots for English are now able to hold conversations on virtually any topic (e. g. Adiwardana et al., 2020; Roller et al., 2021).
ALEN App: Argumentative Writing Support To Foster English Language Learning
We present an approach which automatically detects claim-premise structures and provides visual feedback to the learner to prompt them to repair any broken argumentation structures. To investigate, if our persuasive feedback on language learners’ essay writing tasks engages and supports them in learning better English language, we designed the ALEN app (Argumentation for Learning English).
The Specificity and Helpfulness of Peer-to-Peer Feedback in Higher Education
This peer-to-peer feedback has become increasingly important whether in MOOCs to provide feedback to thousands of students or in large-scale classes at universities.
Efficient Unsupervised NMT for Related Languages with Cross-Lingual Language Models and Fidelity Objectives
The most successful approach to Neural Machine Translation (NMT) when only monolingual training data is available, called unsupervised machine translation, is based on back-translation where noisy translations are generated to turn the task into a supervised one.
Prompting open-source and commercial language models for grammatical error correction of English learner text
Thanks to recent advances in generative AI, we are able to prompt large language models (LLMs) to produce texts which are fluent and grammatical.
CLIMB: Curriculum Learning for Infant-inspired Model Building
We describe our team's contribution to the STRICT-SMALL track of the BabyLM Challenge.
On the application of Large Language Models for language teaching and assessment technology
The recent release of very large language models such as PaLM and GPT-4 has made an unprecedented impact in the popular media and public consciousness, giving rise to a mixture of excitement and fear as to their capabilities and potential uses, and shining a light on natural language processing research which had not previously received so much attention.
Finding the Needle in a Haystack: Unsupervised Rationale Extraction from Long Text Classifiers
Long-sequence transformers are designed to improve the representation of longer texts by language models and their performance on downstream document-level tasks.
Probing for targeted syntactic knowledge through grammatical error detection
Targeted studies testing knowledge of subject-verb agreement (SVA) indicate that pre-trained language models encode syntactic information.
Towards a parallel corpus of Portuguese and the Bantu language Emakhuwa of Mozambique
Major advancement in the performance of machine translation models has been made possible in part thanks to the availability of large-scale parallel corpora.
Grammatical error detection in transcriptions of spoken English
We describe the collection of transcription corrections and grammatical error annotations for the CrowdED Corpus of spoken English monologues on business topics.
The Teacher-Student Chatroom Corpus
The Teacher-Student Chatroom Corpus (TSCC) is a collection of written conversations captured during one-to-one lessons between teachers and learners of English.
An Expectation Maximisation Algorithm for Automated Cognate Detection
In historical linguistics, cognate detection is the task of determining whether sets of words have common etymological roots.
Investigating the effect of auxiliary objectives for the automated grading of learner English speech transcriptions
We address the task of automatically grading the language proficiency of spontaneous speech based on textual features from automatic speech recognition transcripts.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
REPROLANG 2020: Automatic Proficiency Scoring of Czech, English, German, Italian, and Spanish Learner Essays
We report on our attempts to reproduce the work described in Vajjala {\&} Rama 2018, {`}Experiments with universal CEFR classification{'}, as part of REPROLANG 2020: this involves featured-based and neural approaches to essay scoring in Czech, German and Italian.
Adaptive Forgetting Curves for Spaced Repetition Language Learning
The forgetting curve has been extensively explored by psychologists, educationalists and cognitive scientists alike.
CAMsterdam at SemEval-2019 Task 6: Neural and graph-based feature extraction for the identification of offensive tweets
We describe the CAMsterdam team entry to the SemEval-2019 Shared Task 6 on offensive language identification in Twitter data.
Aggressive language in an online hacking forum
We probe the heterogeneity in levels of abusive language in different sections of the Internet, using an annotated corpus of Wikipedia page edit comments to train a binary classifier for abuse detection.
A Text Normalisation System for Non-Standard English Words
This paper investigates the problem of text normalisation; specifically, the normalisation of non-standard words (NSWs) in English.
Parsing transcripts of speech
We present an analysis of parser performance on speech data, comparing word type and token frequency distributions with written data, and evaluating parse accuracy by length of input string.
Collecting fluency corrections for spoken learner English
We present crowdsourced collection of error annotations for transcriptions of spoken learner English.
Automated speech-unit delimitation in spoken learner English
In order to apply computational linguistic analyses and pass information to downstream applications, transcriptions of speech obtained via automatic speech recognition (ASR) need to be divided into smaller meaningful units, in a task we refer to as {`}speech-unit (SU) delimitation{'}.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Crowdsourcing a Multi-lingual Speech Corpus: Recording, Transcription and Annotation of the CrowdIS Corpora
We announce the release of the CROWDED CORPUS: a pair of speech corpora collected via crowdsourcing, containing a native speaker corpus of English (CROWDED{\_}ENGLISH), and a corpus of German/English bilinguals (CROWDED{\_}BILINGUAL).
Reclassifying subcategorization frames for experimental analysis and stimulus generation
The premise was not only to compare the results of two quite different methods for our own interest, but also to enable other researchers to choose whichever reclassification better suited their purpose (one being grounded purely in theoretical linguistics and the other in practical language engineering).
Annotating progressive aspect constructions in the spoken section of the British National Corpus
We present a set of stand-off annotations for the ninety thousand sentences in the spoken section of the British National Corpus (BNC) which feature a progressive aspect verb group.
