Sökning: "Speech Learning Model"

Visar resultat 1 - 5 av 37 uppsatser innehållade orden Speech Learning Model.

  1. 1. Perception of English /l/ and /r/ by Japanese listeners – the influence of living abroad.

    Kandidat-uppsats, Göteborgs universitet/Institutionen för språk och litteraturer

    Författare :Axel Hooper; [2019-03-05]
    Nyckelord :japanska; perception; phoneme; allophone; Speech Learning Model;

    Sammanfattning : This thesis explores the topic of perception of /l/ and /r/ phonemes in Japanese speakers, primarily divided into two groups: Speakers who have lived in Sweden for 3 or more years and speak conversational Swedish, and average Japanese speakers, in an attempt to observe the effects learning Swedish has on one’s English. A hypothesis dubbed the Speech Learning Model (SLM) as well as my own hypotheses were used as a base for comparison. LÄS MER

  2. 2. Utveckling av komplexitetsbedömningsmodell med XGBoost för att anpassa text-till-talsyntes inom Robot-Assisted Language Learning

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

    Författare :Maria Hardin; Joakim Wellenstam; [2019]
    Nyckelord :;

    Sammanfattning : Den sociala roboten Furhat har visat sig vara relevant för Robot-Assisted Language Learning. I dagsläget har Furhat en konstant talhastighet, men i tidigare studier har det framkommit att den skulle gynnas av att ha en mer dynamisk text-till-talsyntes. LÄS MER

  3. 3. A Semi-Supervised Approach to Automatic Speech Recognition Training For the Icelandic Language

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

    Författare :Atli Sigurgeirsson; [2019]
    Nyckelord :;

    Sammanfattning : Recent advances in deep learning have enabled certain systems to approach or even achieve human parity in certain tasks, including automatic speech recognition. These new state-of-the-art speech recognition models are most often dependent on vast amounts of expensive high-quality labeled speech data for supervised training. LÄS MER

  4. 4. Deep Learning for Speech Enhancement : A Study on WaveNet, GANs and General CNN-RNN Architectures

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

    Författare :Oscar Xing Luo; [2019]
    Nyckelord :;

    Sammanfattning : Clarity and intelligiblity are important aspects of speech, especially in a time of misinformation and mistrust. The breakthrough in generative models for audio files has brought massive improvements for speech enhancement. LÄS MER

  5. 5. An Analysis of Cloud-Based Machine Learning Models for Traffic-Sign Classification

    Master-uppsats, Linköpings universitet/Kommunikations- och transportsystemLinköpings universitet/Tekniska fakulteten

    Författare :Victor Lindeman; [2019]
    Nyckelord :machine learning traffic signcloud;

    Sammanfattning : The machine learning method deep neural networks are commonly used for artificial intelligence applications such as speech recognition, robotics, and computer vision. Deep neural networks often have very good accuracy, the downside is the complexity of the computations. LÄS MER