Essays about: "low-resource"

Showing result 1 - 5 of 60 essays containing the word low-resource.

1. 1. A Comparative Analysis of Whisper and VoxRex on Swedish Speech Data

   University essay from Uppsala universitet/Statistiska institutionen

   Author : Max Fredriksson; Elise Ramsay Veljanovska; [2024]
   Keywords : ASR; Automatic Speech Recognition; Swedish Speech Recognition; Speech Recognition Models; Speech-to-Text; Whisper; VoxRex; Wav2Vec; Model Comparison; Transformer Models; Neural Networks; Machine Learning; WER; Word Error Rate; Transcription;

   Abstract : With the constant development of more advanced speech recognition models, the need to determine which models are better in specific areas and for specific purposes becomes increasingly crucial. Even more so for low-resource languages such as Swedish, dependent on the progress of models for the large international languages. READ MORE

3. 2. Data Augmentation: Enhancing Named Entity Recognition Performance on Swedish Medical Texts

   University essay from Göteborgs universitet/Institutionen för data- och informationsteknik

   Author : Lucas Rosvall; Niklas Paasonen; [2023-10-05]
   Keywords : Machine Learning; Information Extraction; Named Entity Recognition; BERT; Data Augmentation;

   Abstract : Named Entity Recognition (NER) refers to the task of locating relevant information within text sequences. Within the medical domain, it can benefit applications such as de-identifying patient records or extracting valuable data for other downstream tasks. READ MORE

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

   University essay from Uppsala universitet/Institutionen för lingvistik och filologi

   Author : Chen Lyu; [2023]
   Keywords : ;

   Abstract : 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). READ MORE

5. 4. Exploration and Evaluation of RNN Models on Low-Resource Embedded Devices for Human Activity Recognition

   University essay from KTH/Mekatronik och inbyggda styrsystem

   Author : Helgi Hrafn Björnsson; Jón Kaldal; [2023]
   Keywords : Recurrent Neural Networks; Long Short-Term Memory Networks; Embedded Systems; Human Activity Recognition; Edge AI; TensorFlow Lite Micro; Recurrent Neural Networks; Long Short-Term Memory Networks; Innbyggda systyem; Mänsklig aktivitetsigenkänning; Edge AI; TensorFlow Lite Micro;

   Abstract : Human activity data is typically represented as time series data, and RNNs, often with LSTM cells, are commonly used for recognition in this field. However, RNNs and LSTM-RNNs are often too resource-intensive for real-time applications on resource constrained devices, making them unsuitable. READ MORE

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

   University essay from Uppsala universitet/Institutionen för lingvistik och filologi

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

   Abstract : 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. READ MORE