Sökning: "automatic speech recognition"

Visar resultat 16 - 20 av 77 uppsatser innehållade orden automatic speech recognition.

  1. 16. A Swedish wav2vec versus Google speech-to-text

    Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Ester Lagerlöf; [2022]
    Nyckelord :ASR; automatic speech recognition; speech-to-text; wav2vec; Google speech-to-text; model comparison;

    Sammanfattning : As the automatic speech recognition technology is becoming more advanced, the possibilities of in which fields it can operate are growing. The best automatic speech recognition technologies today are mainly based on - and made for - the English language. LÄS MER

  3. 17. Cross-lingual and Multilingual Automatic Speech Recognition for Scandinavian Languages

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

    Författare :Rafal Černiavski; [2022]
    Nyckelord :cross-lingual; multilingual; automatic speech recognition; ASR;

    Sammanfattning : 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

  4. 18. Swedish Language End-to-End Automatic Speech Recognition for Media Monitoring using Deep Learning

    Uppsats för yrkesexamina på avancerad nivå, Luleå tekniska universitet/Institutionen för system- och rymdteknik

    Författare :Hector Nyblom; [2022]
    Nyckelord :Automatic Speech Recognition; Deep Learning; Machine Learning; Natural Language Processing; Media Monitoring;

    Sammanfattning : In order to extract relevant information from speech recordings, the general approach is to first convert the audio into transcribed text. The text can then be analysed using well researched methods. NewsMachine AB provides customers with an overview of how they are represented in media by analysing articles in text form. LÄS MER

  5. 19. Automatic Podcast Chapter Segmentation : A Framework for Implementing and Evaluating Chapter Boundary Models for Transcribed Audio Documents

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Adam Feldstein Jacobs; [2022]
    Nyckelord :Machine Learning; Natural Language Processing; Speech Technology; Deep Learning; Podcast Segmentation; Maskininlärning; Språkteknologi; Djupinlärning; Podcast Segmentation;

    Sammanfattning : Podcasts are an exponentially growing audio medium where useful and relevant content should be served, which requires new methods of information sorting. This thesis is the first to look into the state-of-art problem of segmenting podcasts into chapters (structurally and topically coherent sections). LÄS MER

  7. 20. Automatisk taligenkänning som metod för att undersöka artikulationshastighet i svenska

    Kandidat-uppsats, Stockholms universitet/Institutionen för lingvistik

    Författare :Liv Martin Björkdahl; [2022]
    Nyckelord :ASR; automatic speech recognition; articulation rate; UID; dependency length; dependency minimization; information density; ASR; taligenkänning; artikulationshastighet; Wav2Vec 2.0; dependenslängd; korpusstudier; informationsdensitet; UID; dependenslängdsminimering;

    Sammanfattning : 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