Essays about: "Pre-Trained BERT"

Showing result 1 - 5 of 62 essays containing the words Pre-Trained BERT.

  1. 1. Comparison of VADER and Pre-Trained RoBERTa: A Sentiment Analysis Application

    University essay from Lunds universitet/Statistiska institutionen

    Author : Linda Erwe; Xin Wang; [2024]
    Keywords : sentiment analysis; natural language processing; BERT; VADER; sustainability report; Mathematics and Statistics;

    Abstract : Purpose: The purpose of this study is to examine how the overall sentiment results from VADER and a pre-trained RoBERTa model differ. The study investigates potential differences in terms of the median and shape of the two distributions. Data: The sustainability reports of 50 independent random companies are selected as the sample. READ MORE

  3. 2. Nested Noun Phrase Detection in English Text with BERT

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Shweta Misra; [2023]
    Keywords : Phrase detection; nested noun phrase identification; phrase structure identification; sentence parsing; transformer models; machine learning; natural language processing; Frasdetektering; kapslad substantivfrasidentifiering; frasstrukturidentifiering; meningsanalys; transformers-modeller; maskininlärning; naturlig språkbehandling;

    Abstract : In this project, we address the task of nested noun phrase identification in English sentences, where a phrase is defined as a group of words functioning as one unit in a sentence. Prior research has extensively explored the identification of various phrases for language understanding and text generation tasks. READ MORE

  4. 3. Speech Classification using Acoustic embedding and Large Language Models Applied on Alzheimer’s Disease Prediction Task

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Maryam Kheirkhahzadeh; [2023]
    Keywords : Speech classification; Alzheimer’s disease detection; GPT-3; BERT; Text embedding; Dementia; wav2vec2.0; Klassificering av tal; detektion av Alzheimer’s sjukdom; GPT-3; BERT; textinbäddning; demens; wav2vec2.0;

    Abstract : Alzheimer’s sjukdom är en neurodegenerativ sjukdom som leder till demens. Den kan börja tyst i de tidiga stadierna och fortsätta under åren till en allvarlig och obotlig fas. Språkstörningar uppstår ofta som ett av de tidiga symptomen och kan till slut leda till fullständig mutism i de avancerade stadierna av sjukdomen. READ MORE

  5. 4. Performance Benchmarking and Cost Analysis of Machine Learning Techniques : An Investigation into Traditional and State-Of-The-Art Models in Business Operations

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Jacob Lundgren; Sam Taheri; [2023]
    Keywords : Artificial Intelligence AI ; Machine Learning; Big Data; Natural Language Processing NLP ; Pre-Trained BERT; Fine-Tuned BERT; TF-IDF; Logistic Regression; Support Vector Machine SVM ; Cloud GPU; Operating Costs; Performance Efficiency; Business Intelligence;

    Abstract : Eftersom samhället blir allt mer datadrivet revolutionerar användningen av AI och maskininlärning sättet företag fungerar och utvecklas på. Denna studie utforskar användningen av AI, Big Data och Natural Language Processing (NLP) för att förbättra affärsverksamhet och intelligens i företag. READ MORE

  6. 5. Punctuation Restoration as Post-processing Step for Swedish Language Automatic Speech Recognition

    University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Author : Ishika Gupta; [2023]
    Keywords : Transformer; BERT; KB-BERT; NLP; punctuation restoration; deep learning; neural networks;

    Abstract : This thesis focuses on the Swedish language, where punctuation restoration, especially as a postprocessing step for the output of Automatic Speech Recognition (ASR) applications, needs furtherresearch. I have collaborated with NewsMachine AB, a company that provides large-scale mediamonitoring services for its clients, for which it employs ASR technology to convert spoken contentinto text. READ MORE