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Publikasjoner
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Guo, Jinyue; Riaz, Maham & Jensenius, Alexander Refsum
(2024).
Comparing Four 360-Degree Cameras for Spatial Video Recording and Analysis,
Proceedings of the Sound and Music Computing Conference 2024.
SMC Network.
ISSN 2518-3672.
Fulltekst i vitenarkiv
Vis sammendrag
This paper reports on a desktop investigation and a lab experiment comparing the video recording capabilities of four commercially available 360-degree cameras: GoPro MAX, Insta360 X3, Garmin VIRB 360, and Ricoh Theta S. The four cameras all use different recording formats and settings and have varying video quality and software support. This makes it difficult to conduct analyses and compare between devices. We have implemented new functions in the Musical Gestures Toolbox (MGT) for reading and merging files from the different platforms. Using the capabilities of FFmpeg, we have also made a new function for converting between different 360-degree video projections and formats. This allows (music) researchers to exploit 360-degree video recordings using regular video-based analysis pipelines.
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Riaz, Maham & Christodoulou, Anna-Maria
(2023).
Using SuperCollider with OSC Commands for Spatial Audio Control in a Multi-Speaker Setup.
I Andreopoulou, Areti & Boren, Braxton (Red.),
Proceedings of the Audio Engineering Society 155th Convention.
Audio Engineering Society, Inc..
Vis sammendrag
With the ever-increasing prevalence of technology, its application in various music-related processes, such as music composition and performance, has become increasingly prominent. One fascinating area where technology finds utility is in music performance, offering opportunities for extensive sound exploration and manipulation. In this paper, we introduce an approach utilizing SuperCollider and Open Sound Control (OSC) commands in a multi-speaker setup, enabling spatial audio control for a truly interactive audio spatialization experience. We delve into the musicological dimensions of these distinct methods, examining their integration within a live performance setting to uncover their artistic and expressive potential. By merging technology and musicology, our research aims to unlock new avenues for immersive and captivating musical experiences.
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Riaz, Maham
(2023).
An Investigation of Supervised Learning in Music Mood Classification for Audio and MIDI.
I Andreopoulou, Areti & Boren, Braxton (Red.),
Proceedings of the Audio Engineering Society 155th Convention.
Audio Engineering Society, Inc..
Vis sammendrag
This study aims to use supervised learning – specifically, support vector machines – as a tool for a music mood classification task. Four audio and MIDI datasets, each containing over four hundred files, were composed for use in the training and testing processes. Mood classes were formed according to the valence-arousal plane, resulting in the following: happy, sad, relaxed, and tense. Additional runs were also conducted with the linear discriminant analysis, a dimensionality reduction technique commonly used to better the performance of the classifier. The relevant audio and MIDI features were carefully selected for extraction. MIDI datasets for the same music generated better classification results than corresponding audio datasets. Furthermore, when music is composed with each mood associated with a particular key instead of mixed keys, the classification accuracy is higher.
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Riaz, Maham; Upham, Finn; Burnim, Kayla; Bishop, Laura & Jensenius, Alexander Refsum
(2023).
Comparing inertial motion sensors for capturing human micromotion,
Proceedings of the Sound and Music Computing Conference 2023.
SMC Network .
ISSN 978-91-527-7372-7.
doi:
10.5281/zenodo.8316051.
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The paper presents a study of the noise level of accelerometer data from a mobile phone compared to three commercially available IMU-based devices (AX3, Equivital, and Movesense) and a marker-based infrared motion capture system (Qualisys). The sensors are compared in static positions and for measuring human micromotion, with larger motion sequences as reference. The measurements show that all but one of the IMU-based devices capture motion with an accuracy and precision that is far below human micromotion. However, their data and representations differ, so care should be taken when comparing data between devices.
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Riaz, Maham; Hernandez Martinez, Diana & Roginska, Agnieszka
(2022).
Immersive Soundfield Microphone Techniques: An Experimental Approach to Recording Music,
Proceedings of the Audio Engineering Society 153rd Convention.
Audio Engineering Society, Inc..
ISSN 9781942220404.
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Multi-capsule microphone techniques are used in recording the multi-dimensionality of musical performances. This paper evaluates two such techniques: one developed with the 6-capsule Double Mid-Side-Z (DMS-Z) array, and the other with the 32-capsule spherical array. The recordings underwent a similar process of decoding using the 3DCC method, in which each set of arrays was mapped onto 8 directional signals on the horizontal plane. From the performance aspect, the music ensemble consisted of four speakers, a subwoofer and two singers moving within the recording space. Two mixes were produced: Mix A with a combination of the 3DCC-decoded DMS-Z array, spot microphones and Hamasaki Square microphones; and Mix B with the 3DCC-decoded spherical array, spot microphones and Hamasaki Square microphones. These immersive mixes were then evaluated for various perceptual characteristics. Detailed subjective testing is yet to be conducted, but the results so far suggest some perceptual differences in the acoustics and perceived movement of the singers. This is ongoing research that aims to understand whether using a similar audio decoding process on two different multi-array microphone configurations can sufficiently eliminate the perceptual differences between them.
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Riaz, Maham & Roginska, Agnieszka
(2022).
The Psychoacoustic Perception of Distance in Monophonic and Binaural Music,
Proceedings of the Audio Engineering Society 153rd Convention.
Audio Engineering Society, Inc..
ISSN 9781942220404.
Vis sammendrag
Music plays an important role in immersive environments. With the rise in immersive technology, scientists in the field have been researching how music is perceived in extended reality (XR), in an attempt to improve the authenticity of audiovisual experiences. The auditory perception of distance is an important issue in 3D virtual environments but has been considered an obscure area. The study aims to compare monophonic and binaural signals for more accurate localization, over different types of music audio sources.
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Riaz, Maham
(2023).
Sound Design in Unity: Immersive Audio for Virtual Reality Storytelling.
Vis sammendrag
Research talk on sound design for games and immersive environments. The Unity game engine is used for environmental modeling. The Oculus Spatializer plugin provides control over binaural spatialization with native head related transfer functions (HRTF). Game scenes included C# scripts, which accounted for intermittent emitters (randomly triggered sounds of nature, critters and birds), crossfades, occlusion and raycasting. In the mixing stage, mixer groups, mixer snapshsots, snapshot triggers, SFX reverb sends, and low/high-pass filters were some of the tools demonstrated.
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Riaz, Maham
(2023).
An Investigation of Supervised Learning in Music Mood Classification for Audio and MIDI.
Vis sammendrag
This study aims to use supervised learning – specifically, support vector machines – as a tool for a music mood classification task. Four audio and MIDI datasets, each containing over four hundred files, were composed for use in the training and testing processes. Mood classes were formed according to the valence-arousal plane, resulting in the following: happy, sad, relaxed, and tense. Additional runs were also conducted with the linear discriminant analysis, a dimensionality reduction technique commonly used to better the performance of the classifier. The relevant audio and MIDI features were carefully selected for extraction. MIDI datasets for the same music generated better classification results than corresponding audio datasets. Furthermore, when music is composed with each mood associated with a particular key instead of mixed keys, the classification accuracy is higher.
-
Riaz, Maham
(2023).
Using SuperCollider with OSC Commands for Spatial Audio Control in a Multi-Speaker Setup.
Vis sammendrag
With the ever-increasing prevalence of technology, its application in various music-related processes, such as music composition and performance, has become increasingly prominent. One fascinating area where technology finds utility is in music performance, offering opportunities for extensive sound exploration and manipulation. In this paper, we introduce an approach utilizing SuperCollider and Open Sound Control (OSC) commands in a multi-speaker setup, enabling spatial audio control for a truly interactive audio spatialization experience. We delve into the musicological dimensions of these distinct methods, examining their integration within a live performance setting to uncover their artistic and expressive potential. By merging technology and musicology, our research aims to unlock new avenues for immersive and captivating musical experiences.
-
Riaz, Maham; Upham, Finn; Burnim, Kayla; Bishop, Laura & Jensenius, Alexander Refsum
(2023).
Comparing inertial motion sensors for capturing human micromotion.
Vis sammendrag
The paper presents a study of the noise level of accelerometer data from a mobile phone compared to three commercially available IMU-based devices (AX3, Equivital, and Movesense) and a marker-based infrared motion capture system (Qualisys). The sensors are compared in static positions and for measuring human micromotion, with larger motion sequences as reference. The measurements show that all but one of the IMU-based devices capture motion with an accuracy and precision that is far below human micromotion. However, their data and representations differ, so care should be taken when comparing data between devices.
-
-
Riaz, Maham; Hernandez Martinez, Diana & Roginska, Agnieszka
(2022).
Immersive Soundfield Microphone Techniques: An Experimental Approach to Recording Music.
Vis sammendrag
Multi-capsule microphone techniques are used in recording the multi-dimensionality of musical performances. This paper evaluates two such techniques: one developed with the 6-capsule Double Mid-Side-Z (DMS-Z) array, and the other with the 32-capsule spherical array. The recordings underwent a similar process of decoding using the 3DCC method, in which each set of arrays was mapped onto 8 directional signals on the horizontal plane. From the performance aspect, the music ensemble consisted of four speakers, a subwoofer and two singers moving within the recording space. Two mixes were produced: Mix A with a combination of the 3DCC-decoded DMS-Z array, spot microphones and Hamasaki Square microphones; and Mix B with the 3DCC-decoded spherical array, spot microphones and Hamasaki Square microphones. These immersive mixes were then evaluated for various perceptual characteristics. Detailed subjective testing is yet to be conducted, but the results so far suggest some perceptual differences in the acoustics and perceived movement of the singers. This is ongoing research that aims to understand whether using a similar audio decoding process on two different multi-array microphone configurations can sufficiently eliminate the perceptual differences between them.
-
Riaz, Maham
(2022).
The Psychoacoustic Perception of Distance in Monophonic and Binaural Music.
Vis sammendrag
Music plays an important role in immersive environments. With the rise in immersive technology, scientists in the field have been researching how music is perceived in extended reality (XR), in an attempt to improve the authenticity of audiovisual experiences. The auditory perception of distance is an important issue in 3D virtual environments but has been considered an obscure area. The study aims to compare monophonic and binaural signals for more accurate localization, over different types of music audio sources.
Se alle arbeider i Cristin
Publisert
5. sep. 2022 10:31
- Sist endret
26. aug. 2024 19:00