From Music Tracks to Google Maps: Who Owns Computer-generated Works?
نویسندگان
چکیده
Increasingly the digital content used in everyday life has little or no human intervention in its creation. Typically, when such content is delivered to consumers it comes with attached claims of copyright. However, depending on the jurisdiction, approaches to ownership of computer-generated works vary from legislated to uncertain. In this paper we look at the various approaches taken by the common law, and the legislative approach take in the United Kingdom.
منابع مشابه
A Data Focusing method for Microwave Imaging of Extended Targets
This paper presents a data focusing method (DFM) to image extended targets using the multiple signal classification (MUSIC) algorithm. The restriction on the number of transmitter-receiver antennas in a microwave imaging system deteriorates profiling an extended target that comprises many point scatterers. Under such situation, the subspace-based linear inverse scattering methods, like the MUSI...
متن کاملExploring the Semantic Annotation and Retrieval of Sound
We present a computer audition system that can both annotate novel audio tracks with semantically meaningful words and use a semantic query to retrieve relevant tracks from database of unlabeled audio content. We consider the related tasks of content-based audio annotation and retrieval as one supervised multi-class problem in which we model the joint probability of acoustic features and words....
متن کاملMusic Clustering with Constraints
This paper studies the problem of building clusters of music tracks in a collection of popular music in the presence of constraints. The constraints come naturally in the context of music applications. For example, constraints can be generated from the background knowledge (e.g., two artists share similar styles) and the user access patterns (e.g., two pieces of music share similar access patte...
متن کاملScaffolding for Interactively Evolving Novel Drum Tracks for Existing Songs
A major challenge in computer-generated music is to produce music that sounds natural. This paper introduces NEAT Drummer, which takes steps toward natural creativity. NEAT Drummer evolves a kind of artificial neural network called a Compositional Pattern Producing Network (CPPN) with the NeuroEvolution of Augmenting Topologies (NEAT) method to produce drum patterns. An important motivation for...
متن کاملCopyright and the Production of Hip-Hop Music
Whereas the role of patents in cumulative innovation has been well established, little work has examined the impact that copyright policy may have on cumulative innovation in creative content industries. Utilizing U.S. federal court decisions that strengthened the breadth of copyright policy, this paper examines the implications of those decisions on the re-use of original content in the popula...
متن کامل