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1,158 Research products

  • Digital Humanities and Cultural Heritage
  • 2014-2023
  • SE
  • English
  • Digitala Vetenskapliga Arkivet - Academic Archive On-line

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ait Lahmouch, Nadir;

    Uppgifter för behandling av naturliga språk (NLP) har under de senaste åren visat sig vara särskilt effektiva när man använder förtränade språkmodeller som BERT. Det enorma kravet på datorresurser som krävs för att träna sådana modeller gör det dock svårt att använda dem i verkligheten. För att lösa detta problem har komprimeringsmetoder utvecklats. I det här projektet studeras, genomförs och testas några av dessa metoder för komprimering av neurala nätverk för textbearbetning. I vårt fall var den mest effektiva metoden Knowledge Distillation, som består i att överföra kunskap från ett stort neuralt nätverk, som kallas läraren, till ett litet neuralt nätverk, som kallas eleven. Det finns flera varianter av detta tillvägagångssätt, som skiljer sig åt i komplexitet. Vi kommer att titta på två av dem i det här projektet. Den första gör det möjligt att överföra kunskap mellan ett neuralt nätverk och en mindre dubbelriktad LSTM, genom att endast använda resultatet från den större modellen. Och en andra, mer komplex metod som uppmuntrar elevmodellen att också lära sig av lärarmodellens mellanliggande lager för att utvinna kunskap. Det slutliga målet med detta projekt är att ge företagets datavetare färdiga komprimeringsmetoder för framtida projekt som kräver användning av djupa neurala nätverk för NLP. Natural language processing (NLP) tasks have proven to be particularly effective when using pre-trained language models such as BERT. However, the enormous demand on computational resources required to train such models makes their use in the real world difficult. To overcome this problem, compression methods have emerged in recent years. In this project, some of these neural network compression approaches for text processing are studied, implemented and tested. In our case, the most efficient method was Knowledge Distillation, which consists in transmitting knowledge from a large neural network, called teacher, to a small neural network, called student. There are several variants of this approach, which differ in their complexity. We will see two of them in this project, the first one which allows a knowledge transfer between any neural network and another smaller bidirectional LSTM, using only the output of the larger model. And a second, more complex approach that encourages the student model to also learn from the intermediate layers of the teacher model for incremental knowledge extraction. The ultimate goal of this project is to provide the company’s data scientists with ready-to-use compression methods for their future projects requiring the use of deep neural networks for NLP. 

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    Authors: Kotljarchuk, Andrej;

    On September 23, 2013, the leading Swedish daily newspaper, Dagens Nyheter, published a front-page story revealing that a classified listing of Roma had been found on a server belonging to the regional police of Skåne. The illegal database comprised a register of 4,029 persons of Romani descent, more than 1,000 of whom were children living all over Sweden. This news understandably elicited horrified reactions in Sweden and throughout the world. But how exceptional is the concept of such a register to Sweden? To answer this question, we must examine Sweden’s treatment of Romani people during World War II.

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    Authors: Edquist, Samuel;

    Hemligstämpla eller utplåna? Arkivbildningen och den personliga integriteten i Sverige 1900–2015

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    Authors: Barakat, Arian;

    Audiobook reading has traditionally been used for educational purposes but has in recent times grown into a popular alternative to the more traditional means of consuming literature. In order to differentiate themselves from other players in the market, but also provide their users enjoyable literature, several audiobook companies have lately directed their efforts on producing own content. Creating highly rated content is, however, no easy task and one reoccurring challenge is how to make a bestselling story. In an attempt to identify latent features shared by successful audiobooks and evaluate proposed methods for literary quantification, this thesis employs an array of frameworks from the field of Statistics, Machine Learning and Natural Language Processing on data and literature provided by Storytel - Sweden’s largest audiobook company. We analyze and identify important features from a collection of 3077 Swedish books concerning their promotional and literary success. By considering features from the aspects Metadata, Theme, Plot, Style and Readability, we found that popular books are typically published as a book series, cover 1-3 central topics, write about, e.g., daughter-mother relationships and human closeness but that they also hold, on average, a higher proportion of verbs and a lower degree of short words. Despite successfully identifying these, but also other factors, we recognized that none of our models predicted “bestseller” adequately and that future work may desire to study additional factors, employ other models or even use different metrics to define and measure popularity. From our evaluation of the literary quantification methods, namely topic modeling and narrative approximation, we found that these methods are, in general, suitable for Swedish texts but that they require further improvement and experimentation to be successfully deployed for Swedish literature. For topic modeling, we recognized that the sole use of nouns provided more interpretable topics and that the inclusion of character names tended to pollute the topics. We also identified and discussed the possible problem of word inflections when modeling topics for more morphologically complex languages, and that additional preprocessing treatments such as word lemmatization or post-training text normalization may improve the quality and interpretability of topics. For the narrative approximation, we discovered that the method currently suffers from three shortcomings: (1) unreliable sentence segmentation, (2) unsatisfactory dictionary-based sentiment analysis and (3) the possible loss of sentiment information induced by translations. Despite only examining a handful of literary work, we further found that books written initially in Swedish had narratives that were more cross-language consistent compared to books written in English and then translated to Swedish.

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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Publikationer från L...arrow_drop_down
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    Authors: Yurchuk, Yuliya;

    After the collapse of the Soviet Union, Ukrainian society faced a new reality. The new reality involved consolidation and transformation of collective identities. The reinvigoration of national identity led to a change in the emphasis on how the past was dealt with – many things which were regarded as negative by the Soviet regime became presented as positive in independent Ukraine. The war-time nationalist movement, represented by the Organization of Ukrainian Nationalists (OUN) and the Ukrainian Insurgent Army (UPA), became one of the re-configured themes of history. While most of the studies of memory of the OUN and UPA concentrated on the use of the history of the OUN and UPA by nationalist parties, this study goes beyond the analysis of such use of history and scrutinizes the meaning of this history in nation- and state-building processes in relation to memory work realized on the small-scale regional and local levels with the main focus on Rivne and Rivne oblast’. Moreover, this book focusses not only on the “producers” of memory, but also on the “consumers” of memory, the area which is largely understudied in the field of memory studies. In the book the main emphasis is put on monuments which are regarded as catalysts and symptoms of memory. The present study showed that the OUN and UPA are used more as the metaphors of the anti-Soviet and anti-communist struggle for independence than as historical entities. This past is largely mythologized. Functioning as a myth the memory of the OUN and UPA obliterates difficult knowledge that the historical research reveals on the questionable activities and ideology of those organizations. As a result, the past of the OUN and UPA is re-imagined, re-filled with new meanings so that it is used along even with the democratic and pro-European claims in the present. It was especially well-observed during the Orange Revolution in 2004 and during the Euromaidan in 2013-2014, when the European Union’s flags were seen next to the OUN’s red-and-black flags or when the pro-European slogans were proclaimed alongside the OUN and UPA slogans. At the same time, the results demonstrated an intricate complexity of memory work shaped by intensive dynamics of private and public, grassroots and official, local and national encounters. Although there have been attempts made by political actors to draw a direct link between the national identity, political allegiances and proposed heroic version of memory, the study showed, that such attempts did not really work. In the pluralistic context the meanings are too fluid and adherence to one version of history does not preclude adherences to other versions of history which are presented as diametrically opposite in the political sphere. As result, on the recipients’ grassroots level, the memory reveals its amalgamated characteristics. Drawing on studies about post-colonial subjectivities and theories of remediation developed in memory studies, this book explores the changes in memory culture of contemporary Ukraine and examines the role of memory in producing new meanings under the rapidly changing conditions after the collapse of the Soviet Union up to 2014. The book contributes to the studies of memory culture in post-Communist countries as well as to the studies of society in contemporary Ukraine.

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    Authors: Habetzeder, Julia;

    In a well-known passage of his De architectura (written during thelast decades BC) Vitruvius describes the Roman domus (house) as aself-evident part of the public image of its owner. To Vitruvius, thehouse is not a private sphere, at least not in the sense we like to thinkof our homes today. Instead, Vitruvius emphasizes that the domusserves as the backdrop for at least a part of its owner’s public life,and as such its layout and appearance has a bearing on the owner’spublic persona (Vitr. De arch. 6.5.1-3; Granger 1934:36–39). But itwas not just the appearance of the house itself that was important inthis regard: there was a similar relationship between the home-ownerand the possessions that he chose to put on display in his house. During the Late Republican era (133–31 BC), many members ofthe Roman elite set out to acquire art collections to be displayed intheir homes. This paper shows that the decorative luxury possessionsacquired had a power and a capacity of their own. The owner’s tasteand personality were established through the acquisition and displayof these collections. To illustrate this point, two motifs are discussed: kalathiskos dancersand pyrrhic dancers (fig. 1). Within the Roman cultural context,these motifs are primarily represented on decorative luxury items.The paper aims to explore the occurrence of the motifs and to explainwhy pyrrhic dancers were depicted less often than kalthiskos dancers(fig. 2), and to relate this circumstance to the agency of decorativeluxury possessions within the Roman cultural context.

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    Authors: Linderholm, Johan; Eriksson, Samuel; Hristov, Kristian; Wallin, Jan-Erik;
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    Authors: Nordin, Jonas M.; Ojala, Carl-Gösta;

    This article analyses the industrial enterprise of the Dutch-born brothers Abraham and Jakob Momma-Reenstierna and their investments in Sápmi and the upper parts of the Torne River Valley, northern Sweden, during the second half of the seventeenth century. The aim is to explore the driving forces behind the industrial projects of the two brothers in a larger global and colonial context. With inspiration from recent critical studies on the simplifications, and Eurocentrism, in earlier understandings of the birth of modernity, we focus on the modernizing processes taking place in the upper part of the Torne River Valley as a meeting zone between local populations and landscapes and external capital. Metal extraction was booming in the seventeenth-century Sámi areas. Both the Danish-Norwegian and the Swedish Crowns invested heavily in the mining of silver, copper and iron. The scientific focus in archaeology and history has hitherto been very much on the state-governed projects, and limited interest has been directed towards the private enterprises. Moreover, there is also a need to study the roles of the local Finnish and Sámi populations, as well as the global connections, in these colonial industrial projects. A Colonial Arena: Landscape, People and Globalization in Inland Northern Sweden in the Early Modern Period

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    Authors: Lameris, Harm;

    Pre-processing Arabic text for Text-to-Speech (TTS) systems poses major challenges, as Arabic omits short vowels in writing. This omission leads to a large number of homographs, and means that Arabic text needs to be diacritized to disambiguate these homographs, in order to be matched up with the intended pronunciation. Diacritizing Arabic has generally been achieved by using rule-based, statistical, or hybrid methods that combine rule-based and statistical methods. Recently, diacritization methods involving deep learning have shown promise in reducing error rates. These deep-learning methods are not yet commonly used in TTS engines, however. To examine neural diacritization methods for use in TTS engines, we normalized and pre-processed a version of the Tashkeela corpus, a large diacritized corpus containing largely Classical Arabic texts, for TTS purposes. We then trained and tested three state-of-the-art Recurrent-Neural-Network-based models on this data set. Additionally we tested these models on the Wiki News corpus, a test set that contains Modern Standard Arabic (MSA) news articles and thus more closely resembles most TTS queries. The models were evaluated by comparing the Diacritic Error Rate (DER) and Word Error Rate (WER) achieved for each data set to one another and to the DER and WER reported in the original papers. Moreover, the per-diacritic accuracy was examined, and a manual evaluation was performed. For the Tashkeela corpus, all models achieved a lower DER and WER than reported in the original papers. This was largely the result of using more training data in addition to the TTS pre-processing steps that were performed on the data. For the Wiki News corpus, the error rates were higher, largely due to the domain gap between the data sets. We found that for both data sets the models overfit on common patterns and the most common diacritic. For the Wiki News corpus the models struggled with Named Entities and loanwords. Purely neural models generally outperformed the model that combined deep learning with rule-based and statistical corrections. These findings highlight the usability of deep learning methods for Arabic diacritization in TTS engines as well as the need for diacritized corpora that are more representative of Modern Standard Arabic.

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    Authors: Herschend, Frands;

    This article discusses a text, a satire, in the manuscript Paris, Bibl. Nat. lat. 8121A. Conveniently this section of the codex is called Semiramis (see Dronke 1970). Based on Dronke’s (1970) and Gunnell’s (1995) research, the article looks further into Semiramis and discusses whether staging rather than reading it comes with a profit. While discussing this hypothesis four major reasons why Semiramis would benefit from being read as a dramatic script and staged can be singled out. Although the play is a distinctly Latin Semiramis shows affinities with the Anglo-Danish culture of it day and age as well as with Eddic plays, especially Skírnismál and Lokasenna (see Gunnell 1995).

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Ait Lahmouch, Nadir;

    Uppgifter för behandling av naturliga språk (NLP) har under de senaste åren visat sig vara särskilt effektiva när man använder förtränade språkmodeller som BERT. Det enorma kravet på datorresurser som krävs för att träna sådana modeller gör det dock svårt att använda dem i verkligheten. För att lösa detta problem har komprimeringsmetoder utvecklats. I det här projektet studeras, genomförs och testas några av dessa metoder för komprimering av neurala nätverk för textbearbetning. I vårt fall var den mest effektiva metoden Knowledge Distillation, som består i att överföra kunskap från ett stort neuralt nätverk, som kallas läraren, till ett litet neuralt nätverk, som kallas eleven. Det finns flera varianter av detta tillvägagångssätt, som skiljer sig åt i komplexitet. Vi kommer att titta på två av dem i det här projektet. Den första gör det möjligt att överföra kunskap mellan ett neuralt nätverk och en mindre dubbelriktad LSTM, genom att endast använda resultatet från den större modellen. Och en andra, mer komplex metod som uppmuntrar elevmodellen att också lära sig av lärarmodellens mellanliggande lager för att utvinna kunskap. Det slutliga målet med detta projekt är att ge företagets datavetare färdiga komprimeringsmetoder för framtida projekt som kräver användning av djupa neurala nätverk för NLP. Natural language processing (NLP) tasks have proven to be particularly effective when using pre-trained language models such as BERT. However, the enormous demand on computational resources required to train such models makes their use in the real world difficult. To overcome this problem, compression methods have emerged in recent years. In this project, some of these neural network compression approaches for text processing are studied, implemented and tested. In our case, the most efficient method was Knowledge Distillation, which consists in transmitting knowledge from a large neural network, called teacher, to a small neural network, called student. There are several variants of this approach, which differ in their complexity. We will see two of them in this project, the first one which allows a knowledge transfer between any neural network and another smaller bidirectional LSTM, using only the output of the larger model. And a second, more complex approach that encourages the student model to also learn from the intermediate layers of the teacher model for incremental knowledge extraction. The ultimate goal of this project is to provide the company’s data scientists with ready-to-use compression methods for their future projects requiring the use of deep neural networks for NLP. 

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    Authors: Kotljarchuk, Andrej;

    On September 23, 2013, the leading Swedish daily newspaper, Dagens Nyheter, published a front-page story revealing that a classified listing of Roma had been found on a server belonging to the regional police of Skåne. The illegal database comprised a register of 4,029 persons of Romani descent, more than 1,000 of whom were children living all over Sweden. This news understandably elicited horrified reactions in Sweden and throughout the world. But how exceptional is the concept of such a register to Sweden? To answer this question, we must examine Sweden’s treatment of Romani people during World War II.

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    Authors: Edquist, Samuel;

    Hemligstämpla eller utplåna? Arkivbildningen och den personliga integriteten i Sverige 1900–2015

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    Authors: Barakat, Arian;

    Audiobook reading has traditionally been used for educational purposes but has in recent times grown into a popular alternative to the more traditional means of consuming literature. In order to differentiate themselves from other players in the market, but also provide their users enjoyable literature, several audiobook companies have lately directed their efforts on producing own content. Creating highly rated content is, however, no easy task and one reoccurring challenge is how to make a bestselling story. In an attempt to identify latent features shared by successful audiobooks and evaluate proposed methods for literary quantification, this thesis employs an array of frameworks from the field of Statistics, Machine Learning and Natural Language Processing on data and literature provided by Storytel - Sweden’s largest audiobook company. We analyze and identify important features from a collection of 3077 Swedish books concerning their promotional and literary success. By considering features from the aspects Metadata, Theme, Plot, Style and Readability, we found that popular books are typically published as a book series, cover 1-3 central topics, write about, e.g., daughter-mother relationships and human closeness but that they also hold, on average, a higher proportion of verbs and a lower degree of short words. Despite successfully identifying these, but also other factors, we recognized that none of our models predicted “bestseller” adequately and that future work may desire to study additional factors, employ other models or even use different metrics to define and measure popularity. From our evaluation of the literary quantification methods, namely topic modeling and narrative approximation, we found that these methods are, in general, suitable for Swedish texts but that they require further improvement and experimentation to be successfully deployed for Swedish literature. For topic modeling, we recognized that the sole use of nouns provided more interpretable topics and that the inclusion of character names tended to pollute the topics. We also identified and discussed the possible problem of word inflections when modeling topics for more morphologically complex languages, and that additional preprocessing treatments such as word lemmatization or post-training text normalization may improve the quality and interpretability of topics. For the narrative approximation, we discovered that the method currently suffers from three shortcomings: (1) unreliable sentence segmentation, (2) unsatisfactory dictionary-based sentiment analysis and (3) the possible loss of sentiment information induced by translations. Despite only examining a handful of literary work, we further found that books written initially in Swedish had narratives that were more cross-language consistent compared to books written in English and then translated to Swedish.

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    Authors: Yurchuk, Yuliya;

    After the collapse of the Soviet Union, Ukrainian society faced a new reality. The new reality involved consolidation and transformation of collective identities. The reinvigoration of national identity led to a change in the emphasis on how the past was dealt with – many things which were regarded as negative by the Soviet regime became presented as positive in independent Ukraine. The war-time nationalist movement, represented by the Organization of Ukrainian Nationalists (OUN) and the Ukrainian Insurgent Army (UPA), became one of the re-configured themes of history. While most of the studies of memory of the OUN and UPA concentrated on the use of the history of the OUN and UPA by nationalist parties, this study goes beyond the analysis of such use of history and scrutinizes the meaning of this history in nation- and state-building processes in relation to memory work realized on the small-scale regional and local levels with the main focus on Rivne and Rivne oblast’. Moreover, this book focusses not only on the “producers” of memory, but also on the “consumers” of memory, the area which is largely understudied in the field of memory studies. In the book the main emphasis is put on monuments which are regarded as catalysts and symptoms of memory. The present study showed that the OUN and UPA are used more as the metaphors of the anti-Soviet and anti-communist struggle for independence than as historical entities. This past is largely mythologized. Functioning as a myth the memory of the OUN and UPA obliterates difficult knowledge that the historical research reveals on the questionable activities and ideology of those organizations. As a result, the past of the OUN and UPA is re-imagined, re-filled with new meanings so that it is used along even with the democratic and pro-European claims in the present. It was especially well-observed during the Orange Revolution in 2004 and during the Euromaidan in 2013-2014, when the European Union’s flags were seen next to the OUN’s red-and-black flags or when the pro-European slogans were proclaimed alongside the OUN and UPA slogans. At the same time, the results demonstrated an intricate complexity of memory work shaped by intensive dynamics of private and public, grassroots and official, local and national encounters. Although there have been attempts made by political actors to draw a direct link between the national identity, political allegiances and proposed heroic version of memory, the study showed, that such attempts did not really work. In the pluralistic context the meanings are too fluid and adherence to one version of history does not preclude adherences to other versions of history which are presented as diametrically opposite in the political sphere. As result, on the recipients’ grassroots level, the memory reveals its amalgamated characteristics. Drawing on studies about post-colonial subjectivities and theories of remediation developed in memory studies, this book explores the changes in memory culture of contemporary Ukraine and examines the role of memory in producing new meanings under the rapidly changing conditions after the collapse of the Soviet Union up to 2014. The book contributes to the studies of memory culture in post-Communist countries as well as to the studies of society in contemporary Ukraine.

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    Authors: Habetzeder, Julia;

    In a well-known passage of his De architectura (written during thelast decades BC) Vitruvius describes the Roman domus (house) as aself-evident part of the public image of its owner. To Vitruvius, thehouse is not a private sphere, at least not in the sense we like to thinkof our homes today. Instead, Vitruvius emphasizes that the domusserves as the backdrop for at least a part of its owner’s public life,and as such its layout and appearance has a bearing on the owner’spublic persona (Vitr. De arch. 6.5.1-3; Granger 1934:36–39). But itwas not just the appearance of the house itself that was important inthis regard: there was a similar relationship between the home-ownerand the possessions that he chose to put on display in his house. During the Late Republican era (133–31 BC), many members ofthe Roman elite set out to acquire art collections to be displayed intheir homes. This paper shows that the decorative luxury possessionsacquired had a power and a capacity of their own. The owner’s tasteand personality were established through the acquisition and displayof these collections. To illustrate this point, two motifs are discussed: kalathiskos dancersand pyrrhic dancers (fig. 1). Within the Roman cultural context,these motifs are primarily represented on decorative luxury items.The paper aims to explore the occurrence of the motifs and to explainwhy pyrrhic dancers were depicted less often than kalthiskos dancers(fig. 2), and to relate this circumstance to the agency of decorativeluxury possessions within the Roman cultural context.

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    Authors: Linderholm, Johan; Eriksson, Samuel; Hristov, Kristian; Wallin, Jan-Erik;
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    Authors: Nordin, Jonas M.; Ojala, Carl-Gösta;

    This article analyses the industrial enterprise of the Dutch-born brothers Abraham and Jakob Momma-Reenstierna and their investments in Sápmi and the upper parts of the Torne River Valley, northern Sweden, during the second half of the seventeenth century. The aim is to explore the driving forces behind the industrial projects of the two brothers in a larger global and colonial context. With inspiration from recent critical studies on the simplifications, and Eurocentrism, in earlier understandings of the birth of modernity, we focus on the modernizing processes taking place in the upper part of the Torne River Valley as a meeting zone between local populations and landscapes and external capital. Metal extraction was booming in the seventeenth-century Sámi areas. Both the Danish-Norwegian and the Swedish Crowns invested heavily in the mining of silver, copper and iron. The scientific focus in archaeology and history has hitherto been very much on the state-governed projects, and limited interest has been directed towards the private enterprises. Moreover, there is also a need to study the roles of the local Finnish and Sámi populations, as well as the global connections, in these colonial industrial projects. A Colonial Arena: Landscape, People and Globalization in Inland Northern Sweden in the Early Modern Period

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    Authors: Lameris, Harm;

    Pre-processing Arabic text for Text-to-Speech (TTS) systems poses major challenges, as Arabic omits short vowels in writing. This omission leads to a large number of homographs, and means that Arabic text needs to be diacritized to disambiguate these homographs, in order to be matched up with the intended pronunciation. Diacritizing Arabic has generally been achieved by using rule-based, statistical, or hybrid methods that combine rule-based and statistical methods. Recently, diacritization methods involving deep learning have shown promise in reducing error rates. These deep-learning methods are not yet commonly used in TTS engines, however. To examine neural diacritization methods for use in TTS engines, we normalized and pre-processed a version of the Tashkeela corpus, a large diacritized corpus containing largely Classical Arabic texts, for TTS purposes. We then trained and tested three state-of-the-art Recurrent-Neural-Network-based models on this data set. Additionally we tested these models on the Wiki News corpus, a test set that contains Modern Standard Arabic (MSA) news articles and thus more closely resembles most TTS queries. The models were evaluated by comparing the Diacritic Error Rate (DER) and Word Error Rate (WER) achieved for each data set to one another and to the DER and WER reported in the original papers. Moreover, the per-diacritic accuracy was examined, and a manual evaluation was performed. For the Tashkeela corpus, all models achieved a lower DER and WER than reported in the original papers. This was largely the result of using more training data in addition to the TTS pre-processing steps that were performed on the data. For the Wiki News corpus, the error rates were higher, largely due to the domain gap between the data sets. We found that for both data sets the models overfit on common patterns and the most common diacritic. For the Wiki News corpus the models struggled with Named Entities and loanwords. Purely neural models generally outperformed the model that combined deep learning with rule-based and statistical corrections. These findings highlight the usability of deep learning methods for Arabic diacritization in TTS engines as well as the need for diacritized corpora that are more representative of Modern Standard Arabic.

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    Authors: Herschend, Frands;

    This article discusses a text, a satire, in the manuscript Paris, Bibl. Nat. lat. 8121A. Conveniently this section of the codex is called Semiramis (see Dronke 1970). Based on Dronke’s (1970) and Gunnell’s (1995) research, the article looks further into Semiramis and discusses whether staging rather than reading it comes with a profit. While discussing this hypothesis four major reasons why Semiramis would benefit from being read as a dramatic script and staged can be singled out. Although the play is a distinctly Latin Semiramis shows affinities with the Anglo-Danish culture of it day and age as well as with Eddic plays, especially Skírnismál and Lokasenna (see Gunnell 1995).

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