Sökning: "Audio classification"

Visar resultat 1 - 5 av 64 uppsatser innehållade orden Audio classification.

1. 1. Hit song analysis on the Swedish music market : An exploration of hit song classification

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

   Författare :David Hurtig; Petter Lager; [2023]
   Nyckelord :Music; Audio; Machine-learning; Hit-songs; Hit song prediction;

   Sammanfattning : Assessing hit song potential is a challenge in the music industry. The question of what song to promote, which song to release first and whether or not it will succeed has always been an issue for stakeholders in the music business. The ability to statistically evaluate hit song potential is a growing field with several studies exploring the topic. LÄS MER

3. 2. Song Popularity Prediction with Deep Learning : Investigating predictive power of low level audio features

   Magister-uppsats, Luleå tekniska universitet/Institutionen för system- och rymdteknik

   Författare :Gustaf Holst; Jan Niia; [2023]
   Nyckelord :machine learning; deep learning; audio;

   Sammanfattning : Today streaming services are the most popular way to consume music, and with this the field of Music Information Retrieval (MIR) has exploded. Tangy market is a music investment platform and they want to use MIR techniques to estimate the value of not yet released songs. LÄS MER

4. 3. Violin Artist Identification by Analyzing Raga-vistaram Audio

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

   Författare :Nandakishor Ramlal; [2023]
   Nyckelord :Artist identification; Music information retrieval; Deep Learning; Convolutional Neural Network; Convolutional Recurrent Neural Network; Embeddings; log-Melspectrogram; Artistidentifiering; återhämtning av musikinformation; Deep Learning; Convolutional Neural Network; Convolutional Recurrent Neural Network; Inbäddningar; log-Melspektrogram;

   Sammanfattning : With the inception of music streaming and media content delivery platforms, there has been a tremendous increase in the music available on the internet and the metadata associated with it. In this study, we address the problem of violin artist identification, which tries to classify the performing artist based on the learned features. LÄS MER

5. 4. Decoding communication of non-human species - Unsupervised machine learning to infer syntactical and temporal patterns in fruit-bats vocalizations.

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Luigi Assom; [2023]
   Nyckelord :animal decision making; unsupervised machine learning; UMAP; autoencoders; classifiers; bioacoustics; combinatory syntax; animal communication;

   Sammanfattning : Decoding non-human species communication offers a unique chance to explore alternative intelligence forms using machine learning. This master thesis focuses on discreteness and grammar, two of five linguistic areas machine learning can support, and tackles inferring syntax and temporal structures from bioacoustics data annotated with animal behavior. LÄS MER

7. 5. Generating personalized music playlists based on desired mood and individual listening data

   Master-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

   Författare :Jennifer Svensson; [2023]
   Nyckelord :music recommendation; context-based music listening; mood regulation; affect regulation; Spotify Audio Features; music-mood classification; context-aware music recommendation;

   Sammanfattning : Music listening is considered one of the most ubiquitous activities in everyday life, and one of the main reasons why people listen is to affect and regulate their mood. The vast availability and unlimited access of music has made it difficult to find relevant music that fits both the context and the preferences of the music listener. LÄS MER