Music Technology and Sound Studies

No abstract yet.

• BİLAL ALATAŞ

In this study, the effects of physical parameters on sound absorption properties of nonwoven fabrics were investigated. Eight different nonwoven composites including different fiber types mixed with different ratios were tested. Along with sound absorption properties, thickness, weight per area, and air permeability p…

• YASEMİN KORKMAZ

Today, music is a very important and perhaps inseparable part of people's daily life. There are many genres of music and these genres are different from each other, resulting in people to have different preferences of music. As a result, it is an important and up‐to‐date issue to classify music and to recommend people…

• NİZAMETTİN AYDIN

Today, music is a very important and perhaps inseparable part of people's daily life. There are many genres of music and these genres are different from each other, resulting in people to have different preferences of music. As a result, it is an important and up‐to‐date issue to classify music and to recommend people…

• AHMET ELBİR

Music genre classification has a significant role in information retrieval for the organization of growing collections of music. It is challenging to classify music with reliable accuracy. Many methods have utilized handcrafted features to identify unique patterns but are still unable to determine the original music c…

• MERVE ERSOY

Music genre classification has a significant role in information retrieval for the organization of growing collections of music. It is challenging to classify music with reliable accuracy. Many methods have utilized handcrafted features to identify unique patterns but are still unable to determine the original music c…

• JAWAD RASHEED

We propose a novel framework for learning many-to-many statistical mappings from musical measures to dance figures towards generating plausible music-driven dance choreographies. We obtain music-to-dance mappings through use of four statistical models: 1) musical measure models, representing a many-to-one relation, ea…

• YÜCEL YEMEZ

We propose a novel framework for learning many-to-many statistical mappings from musical measures to dance figures towards generating plausible music-driven dance choreographies. We obtain music-to-dance mappings through use of four statistical models: 1) musical measure models, representing a many-to-one relation, ea…

• ENGİN ERZİN

We report our findings on using MIDI files and audio features from MIDI, separately and combined together, for MIDI music genre classification. We use McKay and Fujinaga's 3-root and 9-leaf genre data set. In order to compute distances between MIDI pieces, we use normalized compression distance (NCD). NCD uses the com…

• YUSUF YASLAN

We report our findings on using MIDI files and audio features from MIDI, separately and combined together, for MIDI music genre classification. We use McKay and Fujinaga's 3-root and 9-leaf genre data set. In order to compute distances between MIDI pieces, we use normalized compression distance (NCD). NCD uses the com…

• ABDULLAH SÖNMEZ

No abstract yet.

• ALİ CENK GEDİK

Music genre prediction is one of the topics that digital music processing is interested in. In this study, acoustic features of music have been extracted by using digital signal processing techniques and then music genre classification and music recommendations have been made by using machine learning methods. In addi…