A Novel Framework for Efficient Automated Singer Identification in Large Music Databases

10.1145/1508850.1508856ACM Transactions on Information Systems273ATIS

A computational study on outliers in world music

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country

A neurally-inspired musical instrument classification system based upon the sound onset

Physiological evidence suggests that sound onset detection in the auditory system may be performed by specialized neurons as early as the cochlear nucleus. Psychoacoustic evidence shows that the sound onset can be important for the recognition of musical sounds. Here the sound onset is used in isolation to form tone descriptors for a musical instrument classification task. The task involves 2085 isolated musical tones from the McGill dataset across five instrument categories. A neurally inspired tone descriptor is created using a model of the auditory system's response to sound onset. A gammatone filterbank and spiking onset detectors, built from dynamic synapses and leaky integrate-and-fire neurons, create parallel spike trains that emphasize the sound onset. These are coded as a descriptor called the onset fingerprint. Classification uses a time-domain neural network, the echo state network. Reference strategies, based upon mel-frequency cepstral coefficients, evaluated either over the whole tone or only during the sound onset, provide context to the method. Classification success rates for the neurally-inspired method are around 75%. The cepstral methods perform between 73% and 76%. Further testing with tones from the Iowa MIS collection shows that the neurally inspired method is considerably more robust when tested with data from an unrelated dataset

Polypeptide-grafted macroporous polyHIPE by surface-initiated N-Carboxyanhydride (NCA) polymerization as a platform for bioconjugation

A new class of functional macroporous monoliths from polymerized high internal phase emulsion (polyHIPE) with tunable surface functional groups was developed by direct polypeptide surface grafting. In the first step, amino-functional polyHIPEs were obtained by the addition of 4-vinylbenzyl or 4-vinylbenzylphthalimide to the styrenic emulsion and thermal radical polymerization. The obtained monoliths present the expected open-cell morphology and a high surface area. The incorporated amino group was successfully utilized to initiate the ring-opening polymer- ization of benzyl-L-glutamate N-carboxyanhydride (BLG NCA) and benzyloxycarbonyl-L-lysine (Lys(Z)) NCA, which resulted in a dense homogeneous coating of polypeptides throughout the internal polyHIPE surfaces as confirmed by SEM and FTIR analysis. The amount of polypeptide grafted to the polyHIPE surfaces could be modulated by varying the initial ratio of amino acid NCA to amino-functional polyHIPE. Subsequent removal of the polypeptide protecting groups yielded highly functional polyHIPE-g-poly(glutamic acid) and polyHIPE-g- poly(lysine). Both types of polypeptide-grafted monoliths responded to pH by changes in their hydrohilicity. The possibility to use the high density of function (−COOH or −NH2) for secondary reaction was demonstrated by the successful bioconjugation of enhanced green fluorescent protein (eGFP) and fluorescein isocyanate (FITC) on the polymer 3D-scaffold surface. The amount of eGFP and FITC conjugated to the polypeptide-grafted polyHIPE was significantly higher than to the amino- functional polyHIPE, signifying the advantage of polypeptide grafting to achieve highly functional polyHIPEs