1,721,179 research outputs found
Guided tours of Palazzo Bo: planning of an inclusive itinerary
Full text linkopenMasiero Lucrezia
Visite guidate a Palazzo Bo: progettazione di un percorso inclusivo
Progettazione e Gestione del Turismo culturale
Relatore: Orio Nicola
Progettazione di un percorso di visita guidata inclusiva a Palazzo Bo. Nello specifico dedicata a ciechi.
Creazione di un percorso inclusivo come test, con annessa progettazione di strumenti specifici.
Impianto teorico di riferimento: Museo Tattile Omero. Fonti consultate: testi di Grassini, testi di Tiberti, tesi di laurea precedenti sull'argomento.
Progettazione da zero, con ideazione di strumenti specifici per l'inclusione complessiva all'interno delle visite guidate.
Risultati ipotetici: acquisizione di feedback per la comprensione e l'adeguamento degli strumenti e delle tecniche utilizzate
Automatic identification of audio recordings based on statistical modeling
No full textThis paper describes a methodology for the automatic identification of audio recordings of ethnic music. The identification is based on an application of hidden Markov models (HMMs), which are automatically built from a representation of the music pieces to be identified. States of the HMMs are labeled with music events, and the transition and observation probabilities are directly computed from the information on the music piece. The recordings are modeled by a set of acoustic features that are computed according with the characteristics of the music events. Three alternative approaches, based on typical applications of HMMs, are proposed to perform the identification. Tests carried out on collections of recordings showed that the methodology can achieve good results, and the identification rate is high enough to suggest applications for automatic retrieval of metadata and for the identification of alternative recordings of the same piece
Music Indexing and Retrieval for Multimedia Digital Libraries
No full textThis chapter addresses the problem of the retrieval of music documents from multimedia digital libraries. Some of the peculiarities of the music language are described, showing similarities and differences between indexing and retrieval of textual and music documents. After reviewing the main approaches to music retrieval, a novel methodology is presented, which combines an approximate matching approach with an indexing scheme. The methodology is based on the statistical modeling of musical lexical units with weighted transducers, which are automatically built from the melodic and rhythmic information of lexical units. An experimental evaluation of the methodology is presented, showing encouraging results
A System for the Automatic Identification of Music Works
No full textThis paper describes a system able to identify a music work through the analysis of the audio recording of a performance. The approach is based on the statistical modeling of the expected audio features of music performances, given a database of known music works. In particular, the automatic identification is based on an application of hidden Markov models, which are automatically built from music scores available in digital format. States of the HMMs are labeled by score events, and transition and observation probabilities are directly computed from the information on the score. Three alternative approaches to the identification task have been proposed and tested on a set of audio excerpts. Results showed that the methodology can achieve satisfactory results. A prototype system has been developed, and will be demonstrated, which allows in a few seconds to identify an unknown recording from a dataset of hundreds of scores
Indexing and Retrieval of Music Documents through Pattern Analysis and Data Fusion Techniques
No full textOne of the challenges of music information retrieval is the automatic extraction of effective content descriptors of music documents, which can be used at indexing and at retrieval time to match queries with documents. In this paper it is proposed to index music documents with frequent musical patterns. A musical pattern is a sequence of features in the score that is repeated at least twice: features can regard perceptually relevant characteristics, such as rhythm, pitch, or both. Data fusion techniques are applied to merge the results obtained using different features. A set of experimental tests has been carried out on retrieval effectiveness, robustness to query errors, and dependency on query length on a collection of Beatles' songs using a set of queries. The proposed approach gave good results, both using single features and, in particular, merging the rank lists obtained by different features with a data fusion approach
Song Identification through HMM-based Modeling of the Main Melody
No full textThis paper describes a methodology for the identification of pop and rock songs based on the statistical modeling of the leading voice. The identification is based on the use of hidden Markov models (HMM), which are automatically built from digital music scores. States of the HMMs are labeled by the notes of the leading voice, and the transition and observation probabilities are directly computed from the information on the score. The methodology has been experimentally evaluated on a collection of pop and rock songs, with encouraging results
An Automatic Accompanist Based on Hidden Markov Model
No full textThe behavior of a human accompanist is simulated using a hidden Markov model. The model is divided in two levels. The lower level models directly the incoming signal, without requiring analysis techniques that are prone to errors; the higher level models the performance, taking into account all the possible errors made by the musician. Alignment is performed through a decoding technique alternative to classic Viterbi decoding. A novel technique for the training is also proposed. After the performance has been aligned with the score, the information is used to compute local tempo and drive the automatic accomaniment
Experiments on Segmentation Techniques for Music Documents Indexing
No full textThis paper presents an overview of different approaches to melody segmentation aimed at extracting music lexical units, which can be used as content descriptors of music documents. Four approaches have been implemented and compared on a test collection of real documents and queries, showing their impact on index term size and on retrieval effectiveness. From the results, simple but extensive approaches seem to give better performances than more sophisticated segmentation algorithms
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