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Web application for visualization of music recording parameters
Klimeš, Martin ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
This thesis focuses on the development of a web application for visualizing musical parameters. The goal is to provide users with an environment where they can easily visualize parameters of any music recording and compare these parameters across different interpretations of the composition. The musical parameters visualized in the application are based on the field of Music Information Retrieval. For each of these visualizations, the application implements various settings that are saved to a database for the loggedin user, allowing them to adjust the visualization display according to their individual needs. The reactive Vue.js framework was used for the client-side, Flask framework for the server-side, and the PostgreSQL relational database system for data storage.
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Exploring the Possibilities of Automated Annotation of Classical Music with Abrupt Tempo Changes
Ištvánek, Matěj ; Miklánek, Štěpán
In this paper, we introduce options for automatic measure detection based on synchronization, beat detection, and downbeat detection strategy. We evaluate proposed methods on two motifs from the dataset of Leos Janacek's string quartet music. We use specific user-driven metrics to capture annotation efficiency simulating a scenario where a musicologist has to use the output of an automated system to create ground-truth annotations on given recordings. In the case of the first motif, synchronization outperformed other methods by detecting most of the measure positions correctly. This procedure was also the most suitable for the second motif—it achieved a low number of correct detections, but the vast majority of transferred time positions belonged within the outer tolerance window. Therefore, in most cases, only shifting operations were needed resulting in higher annotation efficiency. Results suggest that the state-of-the-art downbeat tracking is not yet efficient for expressive music.
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Impulse noise detection in audio signals
Hůla, Josef ; Ištvánek, Matěj (referee) ; Mokrý, Ondřej (advisor)
Study disserts known method of detecting impulsive noise in audiosignal. Differential, filtering, autoregressive and ARMA methods are discussed. First, each method is theoretically examined and the character of impulsive disturbances is presented. Later an~implementation of each method is presented and results of their performance is compared. In order to have comparable results, the methods are tested on synthetic impulses with known position and duration and also on recordings containing real impulsive noise.
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Web interface for audio feature visualization
Putz, Viliam ; Ištvánek, Matěj (referee) ; Miklánek, Štěpán (advisor)
This thesis deals with methods of audio features extraction from audio files, visualization of these features and implementation of web interface, which provides the visualization. In the introduction, Music Information Retrieval field, with which this thesis is closely related, is described. Also, the current state in the area of applications for audio features extraction is described. Next, the most common libraries for audio feature extraction within the programming languages are listed. In the second chapter, the audio features that can be extracted from audio file are listed and described. In the third chapter, there is description of the process of implementation, used technologies, function diagram of the web interface, explanation of functionality and description of user interface and its functions.
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System for finding duplicate recordings based on audio information
Švejcar, Michael ; Miklánek, Štěpán (referee) ; Ištvánek, Matěj (advisor)
This diploma thesis discusses different methods of detecting duplicates in a music file database. The problem at hand is that files containing the same recording may differ in sound quality, applause at the end of a performance and other such parameters. The aim of this thesis is to design and implement a system that identifies duplicate recordings and provides an output file for the comparison. The system needs to not be affected by the mentioned parameters but precise enough to prevent matching non-identical recordings. The system is realized using the Python programming language, freely available libraries for computing chroma features, Image Hashing technique and multiple variants of the dynamic time warping algorithm. Three comparison methods were implemented in the system, differing in precision and computation complexity. The methods were then tested on a prepared dataset and four preset precision options were created. The final system seems very precise and insusceptible to detecting recordings that are very similar but not identical as duplicates, for example in case of different interpretations of the same musical piece.
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The Application Of Tempo Calculation For Musicological Purposes
Istvanek, Matej
Beat tracking systems capture time positions of beats within digital recordings. Theyare used, for example, in streaming portals, but applications in the musicological analysis are oftenneglected. In this article, two different methods of beat tracking systems are tested—conventionaland the state-of-the-art—on the specific motif of a string quartet music, which is one of the mostcomplex tasks for beat detectors in general. The aim here is to determine which system is better formusicology purposes. This often involves determining not only the position of individual beats andestimating the tempo but also the accuracy of determining their number. Evaluation analysis maybe suitable for comparing the accuracy of detectors, but may not necessarily reflect the requirementsof musicological analysis. The results of selected detectors show that a system based on a recurrentneural network seems to be the most suitable.
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Universal Audio 1176 Compressor
Pavlik, Miroslav ; Ištvánek, Matěj (referee) ; Koton, Jaroslav (advisor)
The aim of this bachelor thesis is to get acquainted with the issue of analog compressor Universal Audio 1176 and verify the functionality and principles of individual block diagrams of this compressor. The bachelor's thesis is carried out for a detailed analysis of individual blocks of compressor 1176. A practical implementation was constructed, to verify the correct functionality of compressor 1176 on measurements, which were performed in the laboratory.
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Tempo detector based on a neural network
Suchánek, Tomáš ; Smékal, Zdeněk (referee) ; Ištvánek, Matěj (advisor)
This Master’s thesis deals with beat tracking systems, whose functionality is based on neural networks. It describes the structure of these systems and how the signal is processed in their individual blocks. Emphasis is then placed on recurrent and temporal convolutional networks, which by they nature can effectively detect tempo and beats in audio recordings. The selected methods, network architectures and their modifications are then implemented within a comprehensive detection system, which is further tested and evaluated through a cross-validation process on a genre-diverse data-set. The results show that the system, with proposed temporal convolutional network architecture, produces comparable results with foreign publications. For example, within the SMC dataset, it proved to be the most successful, on the contrary, in the case of other datasets it was slightly below the accuracy of state-of-the-art systems. In addition,the proposed network retains low computational complexity despite increased number of internal parameters.
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Extraction of parameters for the research of music performance
Laborová, Anna ; Miklánek, Štěpán (referee) ; Ištvánek, Matěj (advisor)
Different music performances of the same piece may significantly differ from each other. Not only the composer and the score defines the listener’s music experience, but the music performance itself is an integral part of this experience. Four parameter classes can be used to describe a performance objectively: tempo and timing, loudness (dynamics), timbre, and pitch. Each of the individual parameters or their combination can generate a unique characteristic performance. The extraction of such objective parameters is one of the difficulties in the field of Music Performance Analysis and Music Information Retrieval. The submitted work summarizes knowledge and methods from both of the fields. The system is applied to extract data from 31 string quartet performances of 2. movement Lento of String Quartet no. 12 F major (1893) by czech romantic composer Antonín Dvořák (1841–1904).
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