12,617 research outputs found
Sonification of probabilistic feedback through granular synthesis
We describe a method to improve user feedback, specifically the display of time-varying probabilistic information, through asynchronous granular synthesis. We have applied these techniques to challenging control problems as well as to the sonification of online probabilistic gesture recognition. We're using these displays in mobile, gestural interfaces where visual display is often impractical
ImageSpirit: Verbal Guided Image Parsing
Humans describe images in terms of nouns and adjectives while algorithms
operate on images represented as sets of pixels. Bridging this gap between how
humans would like to access images versus their typical representation is the
goal of image parsing, which involves assigning object and attribute labels to
pixel. In this paper we propose treating nouns as object labels and adjectives
as visual attribute labels. This allows us to formulate the image parsing
problem as one of jointly estimating per-pixel object and attribute labels from
a set of training images. We propose an efficient (interactive time) solution.
Using the extracted labels as handles, our system empowers a user to verbally
refine the results. This enables hands-free parsing of an image into pixel-wise
object/attribute labels that correspond to human semantics. Verbally selecting
objects of interests enables a novel and natural interaction modality that can
possibly be used to interact with new generation devices (e.g. smart phones,
Google Glass, living room devices). We demonstrate our system on a large number
of real-world images with varying complexity. To help understand the tradeoffs
compared to traditional mouse based interactions, results are reported for both
a large scale quantitative evaluation and a user study.Comment: http://mmcheng.net/imagespirit
Robust semantic analysis for adaptive speech interfaces
The DUMAS project develops speech-based applications that are adaptable to different users and domains. The paper describes the project's robust semantic analysis strategy, used both in the generic framework for the development of multilingual speech-based dialogue systems which is the main project goal, and in the initial test application, a mobile phone-based e-mail interface
Human interaction with digital ink : legibility measurement and structural analysis
Literature suggests that it is possible to design and implement pen-based computer
interfaces that resemble the use of pen and paper. These interfaces appear to
allow users freedom in expressing ideas and seem to be familiar and easy to use.
Different ideas have been put forward concerning this type of interface, however
despite the commonality of aims and problems faced, there does not appear to be
a common approach to their design and implementation.
This thesis aims to progress the development of pen-based computer interfaces
that resemble the use of pen and paper. To do this, a conceptual model is proposed
for interfaces that enable interaction with "digital ink". This conceptual model is
used to organize and analyse the broad range of literature related to pen-based
interfaces, and to identify topics that are not sufficiently addressed by published
research. Two issues highlighted by the model: digital ink legibility and digital
ink structuring, are then investigated.
In the first investigation, methods are devised to objectively and subjectively
measure the legibility of handwritten script. These methods are then piloted in
experiments that vary the horizontal rendering resolution of handwritten script
displayed on a computer screen. Script legibility is shown to decrease with rendering
resolution, after it drops below a threshold value.
In the second investigation, the clustering of digital ink strokes into words is
addressed. A method of rating the accuracy of clustering algorithms is proposed:
the percentage of words spoiled. The clustering error rate is found to vary among
different writers, for a clustering algorithm using the geometric features of both
ink strokes, and the gaps between them.
The work contributes a conceptual interface model, methods of measuring
digital ink legibility, and techniques for investigating stroke clustering features, to
the field of digital ink interaction research
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