Khalid Alnajjar

University of Helsinki | HY · Department of Digital Humanities

This paper presents a methodology for training a transformer-based model to classify lexical and morphosyntactic features of Skolt Sami, an endangered Uralic language characterized by complex morphology. The goal of our approach is to create an effective system for understanding and analyzing Skolt Sami, given the limited data availability and ling...

We present a novel digital humanities method for representing our Twitch chatters as user em-beddings created by a large language model (LLM). We cluster these embeddings automatically using affinity propagation and further narrow this clustering down through manual analysis. We analyze the chat of one stream by each Twitch streamer: SmallAnt, Doug...

We present a novel digital humanities method for representing our Twitch chatters as user embeddings created by a large language model (LLM). We cluster these embeddings automatically using affinity propagation and further narrow this clustering down through manual analysis. We analyze the chat of one stream by each Twitch streamer: SmallAnt, DougD...

After the introduction of large language models (LLMs), science has not remained the same. Researchers from several different fields of science have been rushing to conduct research on LLMs. This is due to the fact that LLMs are no longer something only machine learning experts can understand. As the middle L in LLM stands for language, it is evide...

This paper presents a methodology for training a transformer-based model to classify lexical and morphosyntactic features of Skolt Sami, an endangered Uralic language characterized by complex morphology. The goal of our approach is to create an effective system for understanding and analyzing Skolt Sami, given the limited data availability and ling...

We present an encoder-decored based model for normalization of Arabic dialects using both BERT and GPT-2 based models. Arabic is a language of many dialects that not only differ from the Modern Standard Arabic (MSA) in terms of pronunciation but also in terms of morphology, grammar and lexical choice. This diversity can be troublesome even to a nat...

We present our work towards building an infrastructure for documenting endangered languages with the focus on Uralic languages in particular. Our infrastructure consists of tools to write dictionaries so that entries are struc-tured in XML format. These dictionaries are the foundation for rule-based NLP tools such as FSTs. We also work actively tow...

In this paper, we present an FST based approach for conducting morphological analysis, lemmatization and generation of Lushootseed words. Furthermore, we use the FST to generate training data for an LSTM based neural model and train this model to do morphological analysis. The neural model reaches a 71.9% accuracy on the test data. Furthermore, we...

Automated generation of textual advertisements for specific products is a natural language generation problem that has not received too wide a research interest in the past. In this paper, we present a genetic algorithm based approach that models the key components of advertising: creativity , ability to draw attention, memo-rability, clarity, info...

In this paper, we present an approach for translating word embeddings from a majority language into 4 minority languages: Erzya, Moksha, Udmurt and Komi-Zyrian. Furthermore, we align these word embeddings and present a novel neural network model that is trained on English data to conduct sentiment analysis and then applied on endangered language da...

In this paper, we present an approach for translating word embeddings from a majority language into 4 minority languages: Erzya, Moksha, Udmurt and Komi-Zyrian. Furthermore, we align these word em-beddings and present a novel neural network model that is trained on English data to conduct sentiment analysis and then applied on endangered language d...

Neural Machine Translation (NMT) has made significant strides in breaking down language barriers around the globe. For lesser-resourced languages like Moksha and Erzya, however, the development of robust NMT systems remains a challenge due to the scarcity of parallel corpora. This paper presents a novel approach to address this challenge by leverag...

In this paper, we describe our work on reimplementing HFST optimized lookup on Python. Our tool is called PYHFST and it is available on GitHub (https:// github.com/Rootroo-ltd/pyhfst), PyPi (https://pypi.org/ project/pyhfst/) and Zenodo (https://zenodo.org/ records/7791470).

We present the first openly available multimodal metaphor annotated corpus. The corpus consists of videos including audio and subtitles that have been annotated by experts. Furthermore, we present a method for detecting metaphors in the new dataset based on the textual content of the videos. The method achieves a high F1-score (62\%) for metaphoric...

We present the first openly available multi-modal metaphor annotated corpus. The corpus consists of videos including audio and subtitles that have been annotated by experts. Furthermore , we present a method for detecting metaphors in the new dataset based on the tex-tual content of the videos. The method achieves a high F1-score (62%) for metaphor...

We present a DialGPT based model for generating creative dialog responses that are conditioned based on one of the following emotions: anger, disgust, fear, happiness, pain, sadness and surprise. Our model is capable of producing a contextually apt response given an input sentence and a desired emotion label. Our model is capable of expressing the...

We present a novel neural model for modern poetry generation in French. The model consists of two pretrained neural models that are fine-tuned for the poem generation task. The encoder of the model is a RoBERTa based one while the decoder is based on GPT-2. This way the model can benefit from the superior natural language understanding performance...

We present a novel approach to generating news headlines in Finnish for a given news story. We model this as a summarization task where a model is given a news article, and its task is to produce a concise headline describing the main topic of the article. Because there are no openly available GPT-2 models for Finnish, we will first build such a mo...

We present a method for extracting a multilingual sentiment annotated dialog data set from Fallout New Vegas. The game developers have preannotated every line of dialog in the game in one of the 8 different sentiments: \textit{anger, disgust, fear, happy, neutral, pained, sad } and \textit{surprised}. The game has been translated into English, Span...

We present a DialGPT based model for generating creative dialog responses that are conditioned based on one of the following emotions: anger, disgust, fear, happiness, pain, sadness and surprise. Our model is capable of producing a contextually apt response given an input sentence and a desired emotion label. Our model is capable of expressing the...

Prerecorded laughter accompanying dialog in comedy TV shows encourages the audience to laugh by clearly marking humorous moments in the show. We present an approach for automatically detecting humor in the Friends TV show using multimodal data. Our model is capable of recognizing whether an utterance is humorous or not and assess the intensity of i...

Prerecorded laughter accompanying dialog in comedy TV shows encourages the audience to laugh by clearly marking humorous moments in the show. We present an approach for automatically detecting humor in the Friends TV show using multimodal data. Our model is capable of recognizing whether an utterance is humorous or not and assess the intensity of i...

We present a method for extracting a multilingual sentiment annotated dialog data set from Fallout New Vegas. The game developers have preannotated every line of dialog in the game in one of the 8 different sentiments: anger, disgust, fear, happy, neutral, pained, sad and surprised. The game has been translated into English, Spanish, German, French...

This document is dedicated to a young man, who, despite the number of times he has traveled around the Sun, is always open to new thoughts on ways to include languages, especially the smaller ones, and the people who speak them in far-reaching and sustainable open-source development. Since Trond Trosterud in Tromsø is attributed a terrific track re...

We present a novel approach to generating news headlines in Finnish for a given news story. We model this as a summarization task where a model is given a news article, and its task is to produce a concise headline describing the main topic of the article. Because there are no openly available GPT-2 models for Finnish, we will first build such a mo...

Role-playing games (RPGs) have a considerable amount of text in video game dialogues. Quite often this text is semi-annotated by the game developers. In this paper, we extract a multilingual dataset of persuasive dialogue from several RPGs. We show the viability of this data in building a persuasion detection system using a natural language process...

Role-playing games (RPGs) have a considerable amount of text in video game dialogues. Quite often this text is semi-annotated by the game developers. In this paper, we extract a multilingual dataset of persuasive dialogue from several RPGs. We show the viability of this data in building a persuasion detection system using a natural language process...

We present a novel neural model for modern poetry generation in French. The model consists of two pretrained neural models that are fine-tuned for the poem generation task. The encoder of the model is a RoBERTa based one while the decoder is based on GPT-2. This way the model can benefit from the superior natural language understanding performance...

Many endangered Uralic languages have multilingual machine readable dictionaries saved in an XML format. However, the dictionaries cover translations very inconsistently between language pairs, for instance, the Livonian dictionary has some translations to Finnish, Lat-vian and Estonian, and the Komi-Zyrian dictionary has some translations to Finni...

The goal of the paper is to predict answers to questions given a passage of Qur'an. The answers are always found in the passage, so the task of the model is to predict where an answer starts and where it ends. As the initial data set is rather small for training, we make use of multilingual BERT so that we can augment the training data by using dat...

While standard Estonian is not a low-resourced language, the different dialects of the language are under-resourced from the point of view of NLP, given that there are no vast hand normalized resources available for training a machine learning model to normalize dialectal Estonian to standard Estonian. In this paper, we crawl a small corpus of para...

The study forms a technical report of various tasks that have been performed on the materials collected and published by Finnish ethnographer and linguist, Matthias Alexander Castr\'en (1813-1852). The Finno-Ugrian Society is publishing Castr\'en's manuscripts as new critical and digital editions, and at the same time different research groups have...

Measuring the semantic similarity of different texts has many important applications in Digital Humanities research such as information retrieval, document clustering and text summarization. The performance of different methods depends on the length of the text, the domain and the language. This study focuses on experimenting with some of the curre...

We present a new approach to inducing a bilingual dictionary between the endangered Erzya and Moksha languages automatically based on existing dictionaries in other languages. This work is, for the most part, complementary to the Mordvin research done by PhD László Keresztes, who has demonstrated the alignment of the two language forms in morpholog...

Measuring the semantic similarity of different texts has many important applications in Digital Humanities research such as information retrieval, document clustering and text summarization. The performance of different methods depends on the length of the text, the domain and the language. This study focuses on experimenting with some of the curre...

The study forms a technical report of various tasks that have been performed on the materials collected and published by Finnish ethnographer and linguist, Matthias Alexander Castrén (1813-1852). The Finno-Ugrian Society is publishing Castrén's manuscripts as new critical and digital editions, and at the same time different research groups have als...

We present the first openly available corpus for detecting depression in Thai. Our corpus is compiled by expert verified cases of depression in several online blogs. We experiment with two different LSTM based models and two different BERT based models. We achieve a 77.53% accuracy with a Thai BERT model in detecting depression. This establishes a...

We present our current work on developing keyboard layouts for a critically endangered Uralic language called Livonian. Our layouts work on Windows, MacOS and Linux. In addition, we have developed keyboard apps with predictive text for Android and iOS. This work has been conducted in collaboration with the language community.

We present the first openly available corpus for detecting depression in Thai. Our corpus is compiled by expert verified cases of depression in several online blogs. We experiment with two different LSTM based models and two different BERT based models. We achieve a 77.53\% accuracy with a Thai BERT model in detecting depression. This establishes a...

Finnish is a language with multiple dialects that not only differ from each other in terms of accent (pronunciation) but also in terms of morphological forms and lexical choice. We present the first approach to automatically detect the dialect of a speaker based on a dialect transcript and transcript with audio recording in a dataset consisting of...

Finnish is a language with multiple dialects that not only differ from each other in terms of accent (pronunciation) but also in terms of morphological forms and lexical choice. We present the first approach to automatically detect the dialect of a speaker based on a dialect transcript and transcript with audio recording in a dataset consisting of...

There are a lot of tools and resources available for processing Finnish. In this paper, we survey recent papers focusing on Finnish NLP related to many different subcategories of NLP such as parsing, generation, semantics and speech. NLP research is conducted in many different research groups in Finland, and it is frequently the case that NLP tools...

There are a lot of tools and resources available for processing Finnish. In this paper , we survey recent papers focusing on Finnish NLP related to many different sub-categories of NLP such as parsing, generation , semantics and speech. NLP research is conducted in many different research groups in Finland, and it is frequently the case that NLP to...

Automated news generation has become a major interest for new agencies in the past. Oftentimes headlines for such automatically generated news articles are unimaginative as they have been generated with ready-made templates. We present a computationally creative approach for headline generation that can generate humorous versions of existing headli...

Automated news generation has become a major interest for new agencies in the past. Oftentimes headlines for such automatically generated news articles are unimaginative as they have been generated with ready-made templates. We present a computationally creative approach for headline generation that can generate humorous versions of existing headli...

Presentamos nuestra infraestructura para la documentación de lenguas urálicas, que consiste en herramientas para redactar diccionarios de tal forma que las entradas sean estructuradas en el formato XML (Extensible Markup Language). Desde los diccionarios en XML podemos generar código para analizadores morfológicos que son útiles para todo tipo de a...

Tässä artikkelissa kokeilemme erilaisia menetelmiä kuvaavien piirteiden tuottamiseksi 151:lle alkuperäiselle Pokémonille. Tuotamme eri menetelmillä sanavektorimalleja nettikorpuksen avulla, ja luokittelemme niillä automaattisesti englannin kielen adjektiiveja sen perusteella, kuinka ominaisia ne ovat tietylle Pokémonille. Kokeidemme perusteella voi...

We present different methods for obtaining descriptive properties automatically for the 151 original Pokémon. We train several different word embeddings models on a crawled Pokémon corpus, and use them to rank automatically English adjectives based on how characteristic they are to a given Pokémon. Based on our experiments, it is better to train a...

We survey human evaluation in papers presenting work on creative natural language generation that have been published in INLG 2020 and ICCC 2020. The most typical human evaluation method is a scaled survey, typically on a 5 point scale, while many other less common methods exist. The most commonly evaluated parameters are meaning, syntactic correct...

In this paper, we present our free and open-source online dictionary editing system that has been developed for editing the new edition of the Finnish-Skolt Sami dictionary. We describe how the system can be used in post-editing a dictionary and how NLP methods have been incorporated as a part of the workflow. In practice, this means the use of FST...

Texts written in Old Literary Finnish represent the first literary work ever written in Finnish starting from the 16th century. There have been several projects in Finland that have digitized old publications and made them available for research use. However, using modern NLP methods in such data poses great challenges. In this paper we propose an...

Texts written in Old Literary Finnish represent the first literary work ever written in Finnish starting from the 16th century. There have been several projects in Finland that have digitized old publications and made them available for research use. However, using modern NLP methods in such data poses great challenges. In this paper we propose an...

This study presents a new dataset on rumor detection in Finnish language news headlines. We have evaluated two different LSTM based models and two different BERT models, and have found very significant differences in the results. A fine-tuned FinBERT reaches the best overall accuracy of 94.3% and rumor label accuracy of 96.0% of the time. However,...

This study presents a new dataset on rumor detection in Finnish language news headlines. We have evaluated two different LSTM based models and two different BERT models , and have found very significant differences in the results. A fine-tuned FinBERT reaches the best overall accuracy of 94.3% and rumor label accuracy of 96.0% of the time. However,...

We construct the first ever multimodal sarcasm dataset for Spanish. The audiovisual dataset consists of sarcasm annotated text that is aligned with video and audio. The dataset represents two varieties of Spanish, a Latin American variety and a Peninsular Spanish variety , which ensures a wider dialectal coverage for this global language. We presen...

We train neural models for morphological analysis, generation and lemmatization for morphologically rich languages. We present a method for automatically extracting substantially large amount of training data from FSTs for 22 languages, out of which 17 are endangered. The neural models follow the same tagset as the FSTs in order to make it possible...

We train neural models for morphological analysis, generation and lemmatization for morphologically rich languages. We present a method for automatically extracting substantially large amount of training data from FSTs for 22 languages, out of which 17 are endangered. The neural models follow the same tagset as the FSTs in order to make it possible...

We construct the first ever multimodal sarcasm dataset for Spanish. The audiovisual dataset consists of sarcasm annotated text that is aligned with video and audio. The dataset represents two varieties of Spanish, a Latin American variety and a Peninsular Spanish variety, which ensures a wider dialectal coverage for this global language. We present...

We outline the Great Misalignment Problem in natural language processing research, this means simply that the problem definition is not in line with the method proposed and the human evaluation is not in line with the definition nor the method. We study this misalignment problem by surveying 10 randomly sampled papers published in ACL 2020 that rep...

We outline the Great Misalignment Problem in natural language processing research, this means simply that the problem definition is not in line with the method proposed and the human evaluation is not in line with the definition nor the method. We study this misalignment problem by surveying 10 randomly sampled papers published in ACL 2020 that rep...

Big languages such as English and Finnish have many natural language processing (NLP) resources and models, but this is not the case for low-resourced and endangered languages as such resources are so scarce despite the great advantages they would provide for the language communities. The most common types of resources available for low-resourced a...

Big languages such as English and Finnish have many natural language processing (NLP) resources and models, but this is not the case for low-resourced and endangered languages as such resources are so scarce despite the great advantages they would provide for the language communities. The most common types of resources available for low-resourced a...

Computational creativity has received a good amount of research interest in generating creative artefacts programmatically. At the same time, research has been conducted in computational aesthetics, which essentially tries to analyse creativity exhibited in art. This thesis aims to unite these two distinct lines of research in the context of natura...

This is a Festschrift for Dr. Jack Rueter, compiled on the occasion of his 60th birthday. The book consists of peer-reviewed scientific work by Dr. Rueter’s colleagues. Its contents, compiled by well-established scholars and researchers in NLP, linguistics, philology and digital humanities, pertain to latest advances in natural language processing,...

Every NLP researcher has to work with different XML or JSON encoded files. This often involves writing code that serves a very specific purpose. Corpona is meant to streamline any workflow that involves XML and JSON based corpora, by offering easy and reusable func-tionalities. The current functionalities relate to easy parsing and access to XML fi...

We present an open-source online dictionary editing system, Ve'rdd, that offers a chance to re-evaluate and edit grassroots dictionaries that have been exposed to multiple amateur editors. The idea is to incorporate community activities into a state-of-the-art finite-state language description of a seriously endangered minority language, Skolt Sami...

We present an open-source online dictionary editing system, Ve rdd, that offers a chance to re-evaluate and edit grassroots dictionaries that have been exposed to multiple amateur editors. The idea is to incorporate community activities into a state-of-the-art finite-state language description of a seriously endangered minority language, Skolt Sami...

Our study presents a dialect normalization method for different Finland Swedish dialects covering six regions. We tested 5 different models, and the best model improved the word error rate from 76.45 to 28.58. Contrary to results reported in earlier research on Finnish dialects, we found that training the model with one word at a time gave best res...

We present an open-source online dictionary editing system, Ve'rdd, that offers a chance to re-evaluate and edit grassroots dictionaries that have been exposed to multiple amateur editors. The idea is to incorporate community activities into a state-of-the-art finite-state language description of a seriously endangered minority language, Skolt Sami...

Our study presents a dialect normalization method for different Finland Swedish dialects covering six regions. We tested 5 different models, and the best model improved the word error rate from 76.45 to 28.58. Contrary to results reported in earlier research on Finnish dialects, we found that training the model with one word at a time gave best res...

This study uses a character level neural machine translation approach trained on a long short-term memory-based bi-directional recurrent neural network architecture for diacritization of Medieval Arabic. The results improve from the online tool used as a baseline. A diacritization model have been published openly through an easy to use Python packa...

We present a novel approach for adapting text written in standard Finnish to different dialects. We experiment with character level NMT models both by using a multi-dialectal and transfer learning approaches. The models are tested with over 20 different dialects. The results seem to favor transfer learning, although not strongly over the multi-dial...

We present a novel approach for adapting text written in standard Finnish to different dialects. We experiment with character level NMT models both by using a multi-dialectal and transfer learning approaches. The models are tested with over 20 different dialects. The results seem to favor transfer learning, although not strongly over the multi-dial...

In advertising, slogans are used to enhance the recall of the advertised product by consumers and to distinguish it from others in the market. Creating effective slogans is a resource-consuming task for humans. In this paper, we describe a novel method for automatically generating slogans, given a target concept (e.g., car) and an adjectival proper...

We present a novel environment for exploratory search in large collections of historical newspapers developed as a part of the NewsEye project. In this paper we focus on the intelligent Personal Research Assistant (PRA) component in the environment and the web interface. The PRA is an interactive exploratory engine that combines results of various...

We present an open online infrastructure for editing and visualization of dictionaries of different Uralic languages (e.g. Erzya, Moksha, Skolt Sami and Komi-Zyrian). Our infrastructure integrates fully into the existing Giellatekno one in terms of XML dictionaries and FST morphology. Our code is open source, and the system is being actively used i...

We present a novel approach for adapting text written in standard Finnish to different dialects. We experiment with character level NMT models both by using a multi-dialectal and transfer learning approaches. The models are tested with over 20 different dialects. The results seem to favor transfer learning, although not strongly over the multi-dial...

We compare different LSTMs and transformer models in terms of their effectiveness in normalizing dialectal Finnish into the normative standard Finnish. As dialect is the common way of communication for people online in Finnish, such a normalization is a necessary step to improve the accuracy of the existing Finnish NLP tools that are tailored for n...

We present a novel approach for generating poetry automatically for the morphologically rich Finnish language by using a genetic algorithm. The approach improves the state of the art of the previous Finnish poem generators by introducing a higher degree of freedom in terms of structural creativity. Our approach is evaluated and described within the...

We present a creative poem generator for the morphologically rich Finnish language. Our method falls into the master-apprentice paradigm, where a computationally creative genetic algorithm teaches a BRNN model to generate poetry. We model several parts of poetic aesthetics in the fitness function of the genetic algorithm, such as sonic features, se...