78,791 research outputs found
The Future of the Internet III
Presents survey results on technology experts' predictions on the Internet's social, political, and economic impact as of 2020, including its effects on integrity and tolerance, intellectual property law, and the division between personal and work lives
Overcoming Language Dichotomies: Toward Effective Program Comprehension for Mobile App Development
Mobile devices and platforms have become an established target for modern
software developers due to performant hardware and a large and growing user
base numbering in the billions. Despite their popularity, the software
development process for mobile apps comes with a set of unique, domain-specific
challenges rooted in program comprehension. Many of these challenges stem from
developer difficulties in reasoning about different representations of a
program, a phenomenon we define as a "language dichotomy". In this paper, we
reflect upon the various language dichotomies that contribute to open problems
in program comprehension and development for mobile apps. Furthermore, to help
guide the research community towards effective solutions for these problems, we
provide a roadmap of directions for future work.Comment: Invited Keynote Paper for the 26th IEEE/ACM International Conference
on Program Comprehension (ICPC'18
Mandarin Singing Voice Synthesis Based on Harmonic Plus Noise Model and Singing Expression Analysis
The purpose of this study is to investigate how humans interpret musical
scores expressively, and then design machines that sing like humans. We
consider six factors that have a strong influence on the expression of human
singing. The factors are related to the acoustic, phonetic, and musical
features of a real singing signal. Given real singing voices recorded following
the MIDI scores and lyrics, our analysis module can extract the expression
parameters from the real singing signals semi-automatically. The expression
parameters are used to control the singing voice synthesis (SVS) system for
Mandarin Chinese, which is based on the harmonic plus noise model (HNM). The
results of perceptual experiments show that integrating the expression factors
into the SVS system yields a notable improvement in perceptual naturalness,
clearness, and expressiveness. By one-to-one mapping of the real singing signal
and expression controls to the synthesizer, our SVS system can simulate the
interpretation of a real singer with the timbre of a speaker.Comment: 8 pages, technical repor
Homiletical Aesthetics: A Paradigmatic Proposal for a Holistic Experience of Preaching
The article is a proposal for a paradigmatic change in homiletical pedagogy. In North America today, most homiletical training at the seminary or divinity school is either text-driven or know-how-driven (or, at times, topic-driven). Thus, the homiletical training focuses on (1) how to exposit a text for a key topic, (2) how to structure a sermon, (3) how to deliver a message, and (4) how to analyze the text-driven sermon. While admitting the usefulness of this current textual or know-how pedagogy, the article suggests the addition of a holistic-aesthetic component of preaching, which I will later call numen-participatory education or a numinous pedagogy of preaching. This proposed pedagogical paradigm has two great advantages that the ecclesial situation today demands: (1) the spiritual formation of the preacher and (2) the holistic-aesthetic and multisensory exposition and experience of the text both by the preacher and the audience
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
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