The Songs of Our Past

Advancements in technology have resulted in unique changes in the way people interact with music today: Small, portable devices allow listening to it everywhere and provide access to thousands or, via streaming, even millions of songs. In addition, all played tracks can be logged with an accuracy down to the second. So far, these music listening histories are mostly used for music recommendation and hidden from their actual creators. But people may also benefit from this data more directly: as memory extensions that allow retrieving the name of a title, for rediscovering old favorites and reflecting about their lives. Additionally, listening histories can be representations of the implicit relationships between musical items. In this thesis, I discuss the contents of these listening histories and present software tools that give their owners the chance to work with them. As a first approach to understanding the patterns contained in listening histories I give an overview of the relevant literature from musicology, human-computer-interaction and music information retrieval. This literature review identifies the context as a main influence for listening: from the musical and temporal to the demographical and social. I then discuss music listening histories as digital memory extensions and a part of lifelogging data. Based on this notion, I present what an ideal listening history would look like and how close the real-world implementations come. I also derive a design space, centered around time, items and listeners, for this specific type of data and shortcomings of the real-world data regarding the previously identified contextual factors. The main part of this dissertation describes the design, implementation and evaluation of visualizations for listening histories. The first set of visualizations presents listening histories in the context of lifelogging, to allow analysing one’s behavior and reminiscing. These casual information visualizations vary in complexity and purpose. The second set is more concerned with the musical context and the idea that listening histories also represent relationships between musical items. I present approaches for improving music recommendation through interaction and integrating listening histories in regular media players. The main contributions of this thesis to HCI and information visualization are: First, a deeper understanding of relevant aspects and important patterns that make a person’s listening special and unique. Second, visualization prototypes and a design space of listening history visualizations that show approaches how to work with temporal personal data in a lifelogging context. Third, ways to improve recommender systems and existing software through the notion of seeing relationships between musical items in listening histories. Finally, as a meta-contribution, the casual approach of all visualizations also helps in providing non-experts with access to their own data, a future challenge for researchers and practitioners alike

Can You See Where I Point at?

Pointing on public displays is usually done in a relative and indirect fashion. However, such techniques have two drawbacks: first, a personal pointer is shown on the public screen which decreases the users ’ privacy in selection tasks. And second, when multiple displays are present, users need to connect to the one they want to interact with a priori. In this paper we review the strengths of Touch Projector as an absolute and direct pointing device in terms of spontaneously interacting with large public screens in a semiprivate fashion. We briefly describe the infrastructure to allow spontaneous interaction through the display and discuss the use of both the local and remote display to distribute information according to the necessary privacy

Rush: Repeated Recommendations on Mobile Devices

We present rush as a recommendation-based interaction and visualization technique for repeated item selection from large data sets on mobile touch screen devices. Proposals and choices are intertwined in a continuous finger gesture navigating a two-dimensional canvas of recommended items. This provides users with more flexibility for the resulting selections. Our design is based on a formative user study regarding orientation and occlusion aspects. Subsequently, we implemented a version of rush for music playlist creation. In an experimental evaluation we compared different types of recommendations based on similarity, namely the top 5 most similar items, five random selections from the list of similar items and a hybrid version of the two. Participants had to create playlists using each condition. Our results show that top 5 was too restricting, while random and hybrid suggestions had comparable results. interfaces for mobile recommender systems is scarce: existing systems ([14],[18]) mostly rely on established desktop interaction metaphors (e.g., critique-based recommendation [21]) and examine issues of mobility such as loss of connection ([19],[8]) and decentralization [13]. Peculiarities of mobile device interaction, such as occlusion problems [35], the influence of the reduced screen space [30] and possibly abrupt endings (e.g., when the bus arrives at the station) have mostly been ignored. Author Keywords Interaction technique, mobile; recommender system

Virtual Projection: Exploring Optical Projection as a Metaphor for Multi-Device Interaction

Figure 1. Virtual Projection is inspired by its optical counterpart for transferring information between handhelds and stationary displays such as tabletops, PC displays or large public displays. By fixing the virtual projection to the display, the frustum can also be used to (a) select regions, (b) interactively apply filters, and (c) post multiple views. Handheld optical projectors provide a simple way to overcome the limited screen real-estate on mobile devices. We present virtual projection (VP), an interaction metaphor inspired by how we intuitively control the position, size, and orientation of a handheld optical projector’s image. VP is based on tracking a handheld device without an optical projector and allows selecting a target display on which to position, scale, and orient an item in a single gesture. By relaxing the optical projection metaphor, we can deviate from modeling perspective projection, for example, to constrain scale or orientation, create multiple copies, or offset the image. VP also supports dynamic filtering based on the projection frustum, creating overview and detail applications, and selecting portions of a larger display for zooming and panning. We show exemplary use cases implemented using our optical feature-tracking framework and present the results of a user study demonstrating the effectiveness of VP in complex interactions with large displays. Author Keywords Interaction technique; mobile device; handheld projection