Sökning: "Parallel languages"

Visar resultat 1 - 5 av 99 uppsatser innehållade orden Parallel languages.

1. 1. How negation influences word order in languages : Automatic classification of word order preference in positive and negative transitive clauses

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Chen Lyu; [2023]
   Nyckelord :;

   Sammanfattning : In this work, we explore the possibility of using word alignment in parallel corpus to project language annotations such as Part-of-Speech tags and dependency relation from high-resource languages to low-resource languages. We use a parallel corpus of Bible translations, including 1,444 translations in 986 languages, and a well-developed parser is used to annotate source languages (English, French, German, and Czech). LÄS MER

3. 2. Head-to-head Transfer Learning Comparisons made Possible : A Comparative Study of Transfer Learning Methods for Neural Machine Translation of the Baltic Languages

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Mathias Stenlund; [2023]
   Nyckelord :machine translation; transfer learning; Latvian; Lithuanian; low-resource languages; transformers; parent language; child language; comparative study;

   Sammanfattning : The struggle of training adequate MT models using data-hungry NMT frameworks for low-resource language pairs has created a need to alleviate the scarcity of sufficiently large parallel corpora. Different transfer learning methods have been introduced as possible solutions to this problem, where a new model for a target task is initialized using parameters learned from some other high-resource task. LÄS MER

4. 3. Neural maskinöversättning av gawarbati

   Kandidat-uppsats, Stockholms universitet/Avdelningen för datorlingvistik

   Författare :Katarina Gillholm; [2023]
   Nyckelord :Machine translation; neural machine translation; NMT; low resource language; Gawarbati; transfer learning; GPT; Maskinöversättning; neural maskinöversättning; NMT; lågresursspråk; gawarbati; överföringsinlärning; GPT;

   Sammanfattning : Nya neurala modeller har lett till stora framsteg inom maskinöversättning, men fungerar fortfarande sämre på språk som saknar stora mängder parallella data, så kallade lågresursspråk. Gawarbati är ett litet, hotat lågresursspråk där endast 5000 parallella meningar finns tillgängligt. LÄS MER

5. 4. Adjectives expressing sadness in Swedish and English : A contrastive lexical analysis

   Kandidat-uppsats, Stockholms universitet/Institutionen för lingvistik

   Författare :Sandra Magni; [2023]
   Nyckelord :sadness; lexical typology; predicative; attributive; experiencer; stimulus; edsenhet; lexikal typologi; predikativ; attributiv; upplevare; stimulus;

   Sammanfattning : This study examines how Swedish and English adjectives relating to the semantic domain of SADNESS are used and what some of their semantic and syntactic characteristics are. The primary objectives of this study are to determine whether the adjectives in question are used more often attributively or predicatively, whether they are used more frequently along with the semantic role of stimulus or experiencer and whether there are any syntactic, semantic or lexical disparities in how Swedish and English encode the domain of SADNESS. LÄS MER

7. 5. Det svengelska språket : En överblick över engelskans roll och anpassning till den moderna svenskan.

   Kandidat-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Felicia Svensson; [2023]
   Nyckelord :Lingvistik; engelska; ortografisk integrering; språkanpassning;

   Sammanfattning : This essay aims to give an overview of the function and incorporation of English into the Swedish language in the present day. To do this I have compiled previous studies from the last few years about the presence of English in Sweden, code switching between the languages and the purpose it serves as well as loanwords and their formal integration into Swedish structures and written conventions. LÄS MER