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- All Subjects: Music
- All Subjects: Disney
- Creators: Libman, Jeffrey
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
My work comes in two parts: an illustration book titled The Butanding and an illustration exhibition. The book will be published through lulu.com and made available to the public. The exhibition component will be held from March 2nd to March 6th in Gallery 100 as part of my senior exhibition Post Pre-Production with six other colleagues in the School of Art. The illustration book is a narration of a little girl and her growing friendship with a whale shark. The overarching theme of the creative project is closure with the passing away of loved ones.
The Butanding is a narrative illustration book about a young girl befriending the local menace of her village, the whale shark. Similar to my own experience, the main subject—the young girl—of my narrative is shown suffering from grief and guilt over her grandmother’s death. My work illustrates a progression of the young girl’s emotional state as she goes on a journey with the whale shark or locally known in the Philippines as the “butanding”. It provides the scenario of a grieving individual who gets the chance to reconnect with a deceased loved one and rebuild relationships that were lost.
For my honors thesis, I chose a creative project that would incorporate expertise and skills from both of my undergraduate degrees at Arizona State University: Music Performance and Music Theory and Composition. The main goal for this project was to design and experience an artistic process of musical production and create a professional musical work to release on digital platforms. The musical process included five main components: Listening, Transcribing, Composing, Recording, and Post Production. The final product is a full album, titled This is Jam Music, that consists of eight pieces and a run time of 33 minutes.
Using two interviews with local Phoenix professional chamber musicians, this document aims to compare their experiences across musical styles to find common ground and understand the value of chamber music as a professional and educational tool.
Standardization is sorely lacking in the field of musical machine learning. This thesis project endeavors to contribute to this standardization by training three machine learning models on the same dataset and comparing them using the same metrics. The music-specific metrics utilized provide more relevant information for diagnosing the shortcomings of each model.