Essays about: "Audio Classification"

Showing result 11 - 15 of 58 essays containing the words Audio Classification.

  1. 11. Attribute Embedding for Variational Auto-Encoders : Regularization derived from triplet loss

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

    Author : Anton E. L. Dahlin; [2022]
    Keywords : Variational Auto-Encoder; Triplet Loss; Contrastive Loss; Generative Models; Metric Learning; Latent Space; Attribute Manipulation; Variationsautokodare; Triplettförlust; Kontrastiv Förlust; Generativa Modeller; Metrisk Inlärning; Latent Utrymme; Attributmanipulation;

    Abstract : Techniques for imposing a structure on the latent space of neural networks have seen much development in recent years. Clustering techniques used for classification have been used to great success, and with this work we hope to bridge the gap between contrastive losses and Generative models. READ MORE

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

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

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

    Abstract : 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). READ MORE

  4. 13. Students' Influences on Sustainability Education : Going Beyond Listening to Students' Voices

    University essay from KTH/Hållbar utveckling, miljövetenskap och teknik

    Author : Silvio Niessner; [2022]
    Keywords : ;

    Abstract : While many actors agree that higher education plays a key role for a sustainability trans- formation of our society, there is no consensus on how higher sustainability education should look like. In this discourse, the students’ perspectives are currently underrepre- sented and their participation rarely goes beyond passive consultation, which means that they cannot have any real influence. READ MORE

  5. 14. Multi-Class Emotion Classification for Interactive Presentations : A case study on how emotional sentiment analysis can help end users better convey intended emotion

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

    Author : Charlotte Andersson; [2022]
    Keywords : Interactive Presentations; Audience Engagement Platform; Emotion Prediction; Natural Language Processing; Text Classification; Sentiment Analysis; BERT; Case Study; Interaktiva Presenationer; Publikengagemangsplattform; Förutsägelse av Känslor; Natural Language Processing; Textklassificering; Attitydanalys; BERT; Fallstudie;

    Abstract : Mentimeter is one of the fastest-growing startups in Sweden. They are an audience engagement platform that allows users to create interactive presentations and engage an audience. As online information spreads increasingly faster, methods of analyzing, understanding, and categorizing information are developing and improving rapidly. READ MORE

  6. 15. Compare Accuracy of Alternative Methods for Sound Classification on Environmental Sounds of Similar Characteristics

    University essay from Stockholms universitet/Statistiska institutionen

    Author : Olov Rudberg; [2022]
    Keywords : Machine Learning; Algorithms; Neural Networks; Computer Vision; Image Recognition; Environmental Sound Classification; Data Augmentation;

    Abstract : Artificial neural networks have in the last decade been a vital tool in image recognition, signal processing and speech recognition. Because of these networks' ability to be highly flexible, they suit a vast amount of different data. This flexible attribute is very sought for within the field of environmental sound classification. READ MORE