Brain oscillation recordings of the audience in a live concert-like setting

There are only a few previous EEG studies that were conducted while the audience is listening to live music. However, in laboratory settings using music recordings, EEG frequency bands theta and alpha are connected to music improvisation and creativity. Here, we measured EEG of the audience in a concert-like setting outside the laboratory and compared the theta and alpha power evoked by partly improvised versus regularly performed familiar versus unfamiliar live classical music. To this end, partly improvised and regular versions of pieces by Bach (familiar) and Melartin (unfamiliar) were performed live by a chamber trio. EEG data from left and right frontal and central regions of interest were analysed to define theta and alpha power during each performance. After the performances, the participants rated how improvised and attractive each of the performances were. They also gave their affective ratings before and after each performance. We found that theta power was enhanced during the familiar improvised Bach piece and the unfamiliar improvised Melartin piece when compared with the performance of the same piece performed in a regular manner. Alpha power was not modulated by manner of performance or by familiarity of the piece. Listeners rated partly improvised performances of a familiar Bach and unfamiliar Melartin piece as more improvisatory and innovative than the regular performances. They also indicated more joy and less sadness after listening to the unfamiliar improvised piece of Melartin and less fearful and more enthusiastic after listening to the regular version of Melartin than before listening. Thus, according to our results, it is possible to study listeners’ brain functions with EEG during live music performances outside the laboratory, with theta activity reflecting the presence of improvisation in the performances.

The Treatment of Cultural Services in Latin American Countries’ Trade Agreements

Cultural products (including goods and services) encompass visual, performing and literary arts as well as newspapers, magazines, books, movies, video and music recordings, radio and television, and now multimedia. To the extent that they are associated with the cultural identity of various States, their treatment in international trade has been debated as to whether, or the extent to which, they should be exempted from trade regulations. The proliferation of preferential trade agreements (PTAs) has further complexified this debate. The article summarizes the provisions relating to cultural services in Latin American PTAs and discusses the scope of these provisions, notably in light of the cultural policy measures involved and States’ ability to conduct cultural policies. The focus is on Chile, Colombia, Mexico and Peru as these are the leading countries in the negotiation of PTAs in Latin America as regards the number of agreements and the scope of cultural provisions.

Efficient Retrieval of Music Recordings Using Graph-Based Index Structures

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.

Informing Piano Multi-Pitch Estimation with Inferred Local Polyphony Based on Convolutional Neural Networks

In this work, we propose considering the information from a polyphony for multi-pitch estimation (MPE) in piano music recordings. To that aim, we propose a method for local polyphony estimation (LPE), which is based on convolutional neural networks (CNNs) trained in a supervised fashion to explicitly predict the degree of polyphony. We investigate two feature representations as inputs to our method, in particular, the Constant-Q Transform (CQT) and its recent extension Folded-CQT (F-CQT). To evaluate the performance of our method, we conduct a series of experiments on real and synthetic piano recordings based on the MIDI Aligned Piano Sounds (MAPS) and the Saarland Music Data (SMD) datasets. We compare our approaches with a state-of-the art piano transcription method by informing said method with the LPE knowledge in a postprocessing stage. The experimental results suggest that using explicit LPE information can refine MPE predictions. Furthermore, it is shown that, on average, the CQT representation is preferred over F-CQT for LPE.

Multimedia Archives: New Digital Filters to Correct Equalization Errors on Digitized Audio Tapes

Multimedia archives face the problem of obsolescing and degrading analogue media (e.g., speech and music recordings and video art). In response, researchers in the field have recently begun studying ad hoc tools for the preservation and access of historical analogue documents. This paper investigates the active preservation process of audio tape recordings, specifically focusing on possible means for compensating equalization errors introduced in the digitization process. If the accuracy of corrective equalization filters is validated, an archivist or musicologist would be able to experience the audio as a historically authentic document such that their listening experience would not require the recovery of the original analogue audio document or the redigitization of the audio. Thus, we conducted a MUSHRA-inspired perception test (n = 14) containing 6 excerpts of electronic music (3 stimuli recorded NAB and 3 recorded CCIR). Participants listened to 6 different equalization filters for each stimulus and rated them in terms of similarity. Filters included a correctly digitized “Reference,” an intentionally incorrect “Foil” filter, and a subsequent digital correction of the Foil filter that was produced with a MATLAB script. When stimuli were collapsed according to their filter type (NAB or CCIR), no significant differences were observed between the Reference and MATLAB correction filters. As such, the digital correction appears to be a promising method for compensation of equalization errors although future study is recommended, specifically containing an increased sample size and additional correction filters for comparison.

Los Tres Grandes

This chapter examines the different manifestations of mambo in Havana and New York to demonstrate the musical connections between the big bands, son conjuntos, and charangas across three decades of regular Cuban dance music performance. The Palladium, in addition to the music venues in the Bronx, provided various opportunities for New York-based musicians to create their own versions of Cuban dance music. Recordings by mambo big bands are analyzed alongside Arsenio Rodríguez’s mambo diablos and Antonio Arcaño’s charanga composition “Mambo” to outline the historic connections between these formats.

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

We 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.