Ensemble Size Classification in Colombian Andean String Music Recordings

Sound or audio engineering is a branch of the field of engineering, which involves the process of recording sound and reproducing it by various means, as well as storing in order to be reproduced later. Known as sound or audio engineers, these trained professionals work in a variety of sound production fields and expert in recording methods. They can be instrumental to implement the affordable technologies and technical process to distribute the audio data hence, making it accessible for future generations. The current role of these engineers not only to perform or limited to recording session but they create metadata for archiving and preservation for future needs. Currently, product sleeves of ethnographic recordings represent no technical elements of how traditional music recordings are produced. The product details focus only to some extent on historical elements and musical notation. To an audio archivist, declaring what devices are in a recording is not linked with preservation data. Apart from the format, the sleeved design, technical specification is essential to other social scientists such as audio engineer and field recordist of the future. The aim of the present research is to capture optimum dynamic range of the sound and applying a signal processing that would not alter the tonality, timbre and harmonic of the sound. Further applying a suitable information storage for the metadata to be preserve or archived for future accessing and reproduction.

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Strategy and Performance across Size Classification of Small Firms in the United States

INTERNATIONAL BUSINESS REVIEW ◽

10.21739/ibr.2004.12.8.2.207 ◽

2004 ◽

Vol 8 (2) ◽

pp. 207

Author(s):

Jin Han Kim

Keyword(s):

United States ◽

Small Firms ◽

The United States ◽

Size Classification ◽

And Performance

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Bali 1928 Music Recordings and 1930s Films

The Oxford Handbook of Musical Repatriation ◽

10.1093/oxfordhb/9780190659806.013.20 ◽

2018 ◽

pp. 348-372

Author(s):

Edward Herbst

Keyword(s):

United States ◽

The United States ◽

The Internet ◽

Grass Roots ◽

Emerging Media ◽

Dominate Discourse ◽

Music Recordings

Bali 1928 is a restoration and repatriation project involving the first published recordings of music in Bali and related film footage and photographs from the 1930s, and a collaboration with Indonesians in all facets of vision, planning, and implementation. Dialogic research among centenarian and younger performers, composers and indigenous scholars has repatriated their knowledge and memories, rekindled by long-lost aural and visual resources. The project has published a series of five CD and DVD volumes in Indonesia by STIKOM Bali and CDs in the United States by Arbiter Records, with dissemination through emerging media and the Internet, and grass-roots repatriation to the genealogical and cultural descendants of the 1928 and 1930s artists and organizations. Extensive research has overcome anonymity, so common with archival materials, which deprives descendants of their unique identities, local epistemologies, and techniques, marginalizing and homogenizing a diverse heritage so that entrenched hegemonies prevail and dominate discourse, authority, and power.

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Low Resource Audio-To-Lyrics Alignment from Polyphonic Music Recordings

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp39728.2021.9414395 ◽

2021 ◽

Author(s):

Emir Demirel ◽

Sven Ahlback ◽

Simon Dixon

Keyword(s):

Low Resource ◽

Music Recordings ◽

Polyphonic Music

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Efficient Retrieval of Music Recordings Using Graph-Based Index Structures

Signals ◽

10.3390/signals2020021 ◽

2021 ◽

Vol 2 (2) ◽

pp. 336-352

Author(s):

Frank Zalkow ◽

Julian Brandner ◽

Meinard Müller

Keyword(s):

Nearest Neighbor ◽

Response Times ◽

Negative Impact ◽

Nearest Neighbor Search ◽

Index Structure ◽

Search Problem ◽

Index Structures ◽

Music Retrieval ◽

Retrieval Systems ◽

Music Recordings

Flexible retrieval systems are required for conveniently browsing through large music collections. In a particular content-based music retrieval scenario, the user provides a query audio snippet, and the retrieval system returns music recordings from the collection that are similar to the query. In this scenario, a fast response from the system is essential for a positive user experience. For realizing low response times, one requires index structures that facilitate efficient search operations. One such index structure is the K-d tree, which has already been used in music retrieval systems. As an alternative, we propose to use a modern graph-based index, denoted as Hierarchical Navigable Small World (HNSW) graph. As our main contribution, we explore its potential in the context of a cross-version music retrieval application. In particular, we report on systematic experiments comparing graph- and tree-based index structures in terms of the retrieval quality, disk space requirements, and runtimes. Despite the fact that the HNSW index provides only an approximate solution to the nearest neighbor search problem, we demonstrate that it has almost no negative impact on the retrieval quality in our application. As our main result, we show that the HNSW-based retrieval is several orders of magnitude faster. Furthermore, the graph structure also works well with high-dimensional index items, unlike the tree-based structure. Given these merits, we highlight the practical relevance of the HNSW graph for music information retrieval (MIR) applications.

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Sparse pursuit and dictionary learning for blind source separation in polyphonic music recordings

EURASIP Journal on Audio Speech and Music Processing ◽

10.1186/s13636-020-00190-4 ◽

2021 ◽

Vol 2021 (1) ◽

Author(s):

Sören Schulze ◽

Emily J. King

Keyword(s):

Single Channel ◽

Spectral Characteristics ◽

Musical Instruments ◽

Model Parameters ◽

Blind Separation ◽

Audio Signals ◽

Frequency Spectra ◽

Acoustic Instruments ◽

Invariant Properties ◽

Music Recordings

AbstractWe propose an algorithm for the blind separation of single-channel audio signals. It is based on a parametric model that describes the spectral properties of the sounds of musical instruments independently of pitch. We develop a novel sparse pursuit algorithm that can match the discrete frequency spectra from the recorded signal with the continuous spectra delivered by the model. We first use this algorithm to convert an STFT spectrogram from the recording into a novel form of log-frequency spectrogram whose resolution exceeds that of the mel spectrogram. We then make use of the pitch-invariant properties of that representation in order to identify the sounds of the instruments via the same sparse pursuit method. As the model parameters which characterize the musical instruments are not known beforehand, we train a dictionary that contains them, using a modified version of Adam. Applying the algorithm on various audio samples, we find that it is capable of producing high-quality separation results when the model assumptions are satisfied and the instruments are clearly distinguishable, but combinations of instruments with similar spectral characteristics pose a conceptual difficulty. While a key feature of the model is that it explicitly models inharmonicity, its presence can also still impede performance of the sparse pursuit algorithm. In general, due to its pitch-invariance, our method is especially suitable for dealing with spectra from acoustic instruments, requiring only a minimal number of hyperparameters to be preset. Additionally, we demonstrate that the dictionary that is constructed for one recording can be applied to a different recording with similar instruments without additional training.

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Parameters Estimation and Prediction of Water Movement and Solute Transport in Layered, Variably Saturated Soils Using the Ensemble Kalman Filter

Water ◽

10.3390/w11071520 ◽

2019 ◽

Vol 11 (7) ◽

pp. 1520

Author(s):

Zheng Jiang ◽

Quanzhong Huang ◽

Gendong Li ◽

Guangyong Li

Keyword(s):

Kalman Filter ◽

Solute Transport ◽

Ensemble Kalman Filter ◽

Water Movement ◽

Parameters Estimation ◽

Saturated Soils ◽

Hydrological Models ◽

State Variables ◽

Ensemble Size ◽

Highly Nonlinear

The parameters of water movement and solute transport models are essential for the accurate simulation of soil moisture and salinity, particularly for layered soils in field conditions. Parameter estimation can be achieved using the inverse modeling method. However, this type of method cannot fully consider the uncertainties of measurements, boundary conditions, and parameters, resulting in inaccurate estimations of parameters and predictions of state variables. The ensemble Kalman filter (EnKF) is well-suited to data assimilation and parameter prediction in Situations with large numbers of variables and uncertainties. Thus, in this study, the EnKF was used to estimate the parameters of water movement and solute transport in layered, variably saturated soils. Our results indicate that when used in conjunction with the HYDRUS-1D software (University of California Riverside, California, CA, USA) the EnKF effectively estimates parameters and predicts state variables for layered, variably saturated soils. The assimilation of factors such as the initial perturbation and ensemble size significantly affected in the simulated results. A proposed ensemble size range of 50–100 was used when applying the EnKF to the highly nonlinear hydrological models of the present study. Although the simulation results for moisture did not exhibit substantial improvement with the assimilation, the simulation of the salinity was significantly improved through the assimilation of the salinity and relative solutetransport parameters. Reducing the uncertainties in measured data can improve the goodness-of-fit in the application of the EnKF method. Sparse field condition observation data also benefited from the accurate measurement of state variables in the case of EnKF assimilation. However, the application of the EnKF algorithm for layered, variably saturated soils with hydrological models requires further study, because it is a challenging and highly nonlinear problem.

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