Sökning: "Wav2Vec 2.0"
Visar resultat 1 - 5 av 6 uppsatser innehållade orden Wav2Vec 2.0.
1. Domain Adaptation with N-gram Language Models for Swedish Automatic Speech Recognition : Using text data augmentation to create domain-specific n-gram models for a Swedish open-source wav2vec 2.0 model
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Automatic Speech Recognition (ASR) enables a wide variety of practical applications. However, many applications have their own domain-specific words, creating a gap between training and test data when used in practice. LÄS MER
2. Cross-lingual and Multilingual Automatic Speech Recognition for Scandinavian Languages
Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologiSammanfattning : Research into Automatic Speech Recognition (ASR), the task of transforming speech into text, remains highly relevant due to its countless applications in industry and academia. State-of-the-art ASR models are able to produce nearly perfect, sometimes referred to as human-like transcriptions; however, accurate ASR models are most often available only in high-resource languages. LÄS MER
3. Automatisk taligenkänning som metod för att undersöka artikulationshastighet i svenska
Kandidat-uppsats, Stockholms universitet/Institutionen för lingvistikSammanfattning : Den senaste tidens utveckling inom automatisk taligenkänning har lett till mindre resurskrävan-de och mer effektiva modeller. Detta innebär nya möjligheter för forskning kring spontant tal.I den här studien används Kungliga Bibliotekets svenska version av Wav2Vec 2. LÄS MER
4. Multilingual Speech Emotion Recognition using pretrained models powered by Self-Supervised Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Society is based on communication, for which speech is the most prevalent medium. In day to day interactions we talk to each other, but it is not only the words spoken that matters, but the emotional delivery as well. Extracting emotion from speech has therefore become a topic of research in the area of speech tasks. LÄS MER
5. Automatic Speech Recognition for low-resource languages using Wav2Vec2 : Modern Standard Arabic (MSA) as an example of a low-resource language
Master-uppsats, Högskolan Dalarna/Institutionen för information och teknikSammanfattning : 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