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- All Subjects: Violin and piano music
ContributorsChang, Ruihong (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-29
Description
Four Souvenirs for Violin and Piano was composed by Paul Schoenfeld (b.1947) in 1990 as a showpiece, spotlighting the virtuosity of both the violin and piano in equal measure. Each movement is a modern interpretation of a folk or popular genre, re- envisioned over intricate jazz harmonies and rhythms. The work was commissioned by violinist Lev Polyakin, who specifically requested some short pieces that could be performed in a local jazz establishment named Night Town in Cleveland, Ohio. The result is a work that is approximately fifteen minutes in length. Schoenfeld is a respected composer in the contemporary classical music community, whose Café Music (1986) for piano trio has recently become a staple of the standard chamber music repertoire. Many of his other works, however, remain in relative obscurity. It is the focus of this document to shed light on at least one other notable composition; Four Souvenirs for Violin and Piano. Among the topics to be discussed regarding this piece are a brief history behind the genesis of this composition, a structural summary of the entire work and each of its movements, and an appended practice guide based on interview and coaching sessions with the composer himself. With this project, I hope to provide a better understanding and appreciation of this work.
ContributorsJanczyk, Kristie Annette (Author) / Ryan, Russell (Thesis advisor) / Campbell, Andrew (Committee member) / Norton, Kay (Committee member) / Arizona State University (Publisher)
Created2015
ContributorsWhite, Aaron (Performer) / Kim, Olga (Performer) / Hammond, Marinne (Performer) / Shaner, Hayden (Performer) / Yoo, Katie (Performer) / Shoemake, Crista (Performer) / Gebe, Vladimir, 1987- (Performer) / Wills, Grace (Performer) / McKinch, Riley (Performer) / Freshmen Four (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-27
ContributorsRosenfeld, Albor (Performer) / Pagano, Caio, 1940- (Performer) / ASU Library. Music Library (Publisher)
Created2018-10-03
ContributorsCao, Yuchen (Performer) / Chen, Sicong (Performer) / Soberano, Chino (Performer) / Nam, Michelle (Performer) / Collins, Clarice (Performer) / Witt, Juliana (Performer) / Liu, Jingting (Performer) / Chen, Neilson (Performer) / Zhang, Aihua (Performer) / Jiang, Zhou (Performer) / ASU Library. Music Library (Publisher)
Created2018-04-25
ContributorsMcLin, Katherine (Performer) / Campbell, Andrew (Pianist) (Performer) / Ericson, John Q. (John Quincy), 1962- (Performer) / McLin/Campbell Duo (Performer) / ASU Library. Music Library (Publisher)
Created2018-09-23
Description
Speech recognition and keyword detection are becoming increasingly popular applications for mobile systems. While deep neural network (DNN) implementation of these systems have very good performance,
they have large memory and compute resource requirements, making their implementation on a mobile device quite challenging. In this thesis, techniques to reduce the memory and computation cost
of keyword detection and speech recognition networks (or DNNs) are presented.
The first technique is based on representing all weights and biases by a small number of bits and mapping all nodal computations into fixed-point ones with minimal degradation in the
accuracy. Experiments conducted on the Resource Management (RM) database show that for the keyword detection neural network, representing the weights by 5 bits results in a 6 fold reduction in memory compared to a floating point implementation with very little loss in performance. Similarly, for the speech recognition neural network, representing the weights by 6 bits results in a 5 fold reduction in memory while maintaining an error rate similar to a floating point implementation. Additional reduction in memory is achieved by a technique called weight pruning,
where the weights are classified as sensitive and insensitive and the sensitive weights are represented with higher precision. A combination of these two techniques helps reduce the memory
footprint by 81 - 84% for speech recognition and keyword detection networks respectively.
Further reduction in memory size is achieved by judiciously dropping connections for large blocks of weights. The corresponding technique, termed coarse-grain sparsification, introduces
hardware-aware sparsity during DNN training, which leads to efficient weight memory compression and significant reduction in the number of computations during classification without
loss of accuracy. Keyword detection and speech recognition DNNs trained with 75% of the weights dropped and classified with 5-6 bit weight precision effectively reduced the weight memory
requirement by ~95% compared to a fully-connected network with double precision, while showing similar performance in keyword detection accuracy and word error rate.
they have large memory and compute resource requirements, making their implementation on a mobile device quite challenging. In this thesis, techniques to reduce the memory and computation cost
of keyword detection and speech recognition networks (or DNNs) are presented.
The first technique is based on representing all weights and biases by a small number of bits and mapping all nodal computations into fixed-point ones with minimal degradation in the
accuracy. Experiments conducted on the Resource Management (RM) database show that for the keyword detection neural network, representing the weights by 5 bits results in a 6 fold reduction in memory compared to a floating point implementation with very little loss in performance. Similarly, for the speech recognition neural network, representing the weights by 6 bits results in a 5 fold reduction in memory while maintaining an error rate similar to a floating point implementation. Additional reduction in memory is achieved by a technique called weight pruning,
where the weights are classified as sensitive and insensitive and the sensitive weights are represented with higher precision. A combination of these two techniques helps reduce the memory
footprint by 81 - 84% for speech recognition and keyword detection networks respectively.
Further reduction in memory size is achieved by judiciously dropping connections for large blocks of weights. The corresponding technique, termed coarse-grain sparsification, introduces
hardware-aware sparsity during DNN training, which leads to efficient weight memory compression and significant reduction in the number of computations during classification without
loss of accuracy. Keyword detection and speech recognition DNNs trained with 75% of the weights dropped and classified with 5-6 bit weight precision effectively reduced the weight memory
requirement by ~95% compared to a fully-connected network with double precision, while showing similar performance in keyword detection accuracy and word error rate.
ContributorsArunachalam, Sairam (Author) / Chakrabarti, Chaitali (Thesis advisor) / Seo, Jae-Sun (Thesis advisor) / Cao, Yu (Committee member) / Arizona State University (Publisher)
Created2016
Description
Samuel Máynez Prince (1886-1966), was a prolific and important Mexican musician. Prince’s musical style followed the trends of the nineteenth-century salon music genre. His compositions include lullabies, songs, dances, marches, mazurkas, waltzes, and revolutionary anthems. Prince’s social status and performances in the famed Café Colón in Mexico City increased his popularity among high-ranking political figures during the time of the Mexican Revolution as well as his status in the Mexican music scene.
Unfortunately there is virtually no existing scholarship on Prince and even basic information regarding his life and works is not readily available. The lack of organization of the manuscript scores and the absence of dates of his works has further pushed the composer into obscurity. An investigation therefore was necessary in order to explore the neglected aspects of the life and works of Prince as a violinist and composer. This document is the result of such an investigation by including extensive new biographical information, as well as the first musical analysis and edition of the complete recovered works for violin and piano.
In order to fill the gaps present in the limited biographical information regarding Prince’s life, investigative research was conducted in Mexico City. Information was drawn from archives of the composer’s grandchildren, the Palacio de Bellas Artes, the Conservatorio Nacional de Música de México, and the Orquesta Sinfónica Nacional. The surviving relatives provided first-hand details on events in the composer’s life; one also offered the researcher access to their personal archive including, important life documents, photographs, programs from concert performances, and manuscript scores of the compositions. Establishing connections with the relatives also led the researcher to examining the violins owned and used by the late violinist/composer.
This oral history approach led to new and updated information, including the revival of previously unpublished music for violin and piano. These works are here compiled in an edition that will give students, teachers, and music-lovers access to this unknown repertoire. Finally, this research seeks to promote the beauty and nuances of Mexican salon music, and the complete works for violin and piano of Samuel Máynez Prince in particular.
Unfortunately there is virtually no existing scholarship on Prince and even basic information regarding his life and works is not readily available. The lack of organization of the manuscript scores and the absence of dates of his works has further pushed the composer into obscurity. An investigation therefore was necessary in order to explore the neglected aspects of the life and works of Prince as a violinist and composer. This document is the result of such an investigation by including extensive new biographical information, as well as the first musical analysis and edition of the complete recovered works for violin and piano.
In order to fill the gaps present in the limited biographical information regarding Prince’s life, investigative research was conducted in Mexico City. Information was drawn from archives of the composer’s grandchildren, the Palacio de Bellas Artes, the Conservatorio Nacional de Música de México, and the Orquesta Sinfónica Nacional. The surviving relatives provided first-hand details on events in the composer’s life; one also offered the researcher access to their personal archive including, important life documents, photographs, programs from concert performances, and manuscript scores of the compositions. Establishing connections with the relatives also led the researcher to examining the violins owned and used by the late violinist/composer.
This oral history approach led to new and updated information, including the revival of previously unpublished music for violin and piano. These works are here compiled in an edition that will give students, teachers, and music-lovers access to this unknown repertoire. Finally, this research seeks to promote the beauty and nuances of Mexican salon music, and the complete works for violin and piano of Samuel Máynez Prince in particular.
ContributorsEkenes, Spencer Arvin (Author) / McLin, Katherine (Thesis advisor) / Feisst, Sabine (Committee member) / Jiang, Danwen (Committee member) / Arizona State University (Publisher)
Created2016