Sökning: "low-resource language"
Visar resultat 1 - 5 av 14 uppsatser innehållade orden low-resource language.
1. SPEECH SYNTHESIS AND RECOGNITION FOR A LOW-RESOURCE LANGUAGE Connecting TTS and ASR for mutual benefitMaster-uppsats, Göteborgs universitet / Institutionen för filosofi, lingvistik och vetenskapsteori
Sammanfattning : Speech synthesis (text-to-speech, TTS) and speech recognition (automatic speech recognition, ASR) are the NLP technologies that are the least available for low-resource and indigenous languages. Lack of computational and data resources is the major obstacle when it comes to the development of linguistic tools for these languages. LÄS MER
- Uppsats för yrkesexamina på avancerad nivå, Mittuniversitetet/Institutionen för informationssystem och –teknologi
Sammanfattning : The complexity for being at the forefront regarding information retrieval systems are constantly increasing. Recent technology of natural language processing called BERT has reached superhuman performance in high resource languages for reading comprehension tasks. LÄS MER
- Master-uppsats, Linköpings universitet/Medie- och InformationsteknikLinköpings universitet/Tekniska fakulteten; Linköpings universitet/Medie- och InformationsteknikLinköpings universitet/Tekniska fakulteten
Sammanfattning : Extractive text summarization has over the years been an important research area in Natural Language Processing. Numerous methods have been proposed for extracting information from text documents. Recent works have shown great success for English summarization tasks by fine-tuning the language model BERT using large summarization datasets. LÄS MER
4. Automatic Speech Recognition for low-resource languages using Wav2Vec2 : Modern Standard Arabic (MSA) as an example of a low-resource languageMaster-uppsats, Högskolan Dalarna/Institutionen för information och teknik
Sammanfattning : The need for fully automatic translation at DigitalTolk, a Stockholm-based company providing translation services, leads to exploring Automatic Speech Recognition as a first step for Modern Standard Arabic (MSA). Facebook AI recently released a second version of its Wav2Vec models, dubbed Wav2Vec 2. LÄS MER
- Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi
Sammanfattning : Models based around the transformer architecture have become one of the most prominent for solving a multitude of natural language processing (NLP)tasks since its introduction in 2017. However, much research related to the transformer model has focused primarily on achieving high performance and many problems remain unsolved. LÄS MER