Much has been written about theory and practice in the law, and the tension between practitioners and theorists. Judges do not cite theoretical articles often; they rarely "apply" theories to particular cases. These arguments are not revisited. Instead the Essay explores the working and interaction of theory and practice, practitioners and theorists. The Essay starts with a story about solving a legal issue using our intellectual tools - theory, practice, and their progenies: experience and "gut." Next the Essay elaborates on the nature of theory, practice, experience and "gut." The third part of the Essay discusses theories that are helpful to practitioners and those that are less helpful. The Essay concludes that practitioners theorize, and theorists practice. They use these intellectual tools differently because the goals and orientations of theorists and practitioners, and the constraints under which they act, differ. Theory, practice, experience and "gut" help us think, remember, decide and create. They complement each other like the two sides of the same coin: distinct but inseparable.

Of Theory and Practice

Text-to-Speech Synthesis provides a complete, end-to-end account of the process of generating speech by computer. Giving an in-depth explanation of all aspects of current speech synthesis technology, it assumes no specialized prior knowledge. Introductory chapters on linguistics, phonetics, signal processing and speech signals lay the foundation, with subsequent material explaining how this knowledge is put to use in building practical systems that generate speech. Including coverage of the very latest techniques such as unit selection, hidden Markov model synthesis, and statistical text analysis, explanations of the more traditional techniques such as format synthesis and synthesis by rule are also provided. Weaving together the various strands of this multidisciplinary field, the book is designed for graduate students in electrical engineering, computer science, and linguistics. It is also an ideal reference for practitioners in the fields of human communication interaction and telephony.

/pdf/text-to-speech-synthesis-2y7hiwoykk.pdf

Text-to-Speech Synthesis

Current approaches to accessible computing share a common goal of making technology accessible to users with disabilities. Perhaps because of this goal, they may also share a tendency to centralize disability rather than ability. We present a refinement to these approaches called ability-based design that consists of focusing on ability throughout the design process in an effort to create systems that leverage the full range of human potential. Just as user-centered design shifted the focus of interactive system design from systems to users, ability-based design attempts to shift the focus of accessible design from disability to ability. Although prior approaches to accessible computing may consider users’ abilities to some extent, ability-based design makes ability its central focus. We offer seven ability-based design principles and describe the projects that inspired their formulation. We also present a research agenda for ability-based design.

https://faculty.washington.edu/wobbrock/pubs/taccess-11.pdf

Ability-Based Design: Concept, Principles and Examples

From an accessibility perspective, voice-controlled, home-based intelligent personal assistants (IPAs) have the potential to greatly expand speech interaction beyond dictation and screen reader output. To examine the accessibility of off-the-shelf IPAs (e.g., Amazon Echo) and to understand how users with disabilities are making use of these devices, we conducted two exploratory studies. The first, broader study is a content analysis of 346 Amazon Echo reviews that include users with disabilities, while the second study more specifically focuses on users with visual impairments, through interviews with 16 current users of home-based IPAs. Findings show that, although some accessibility challenges exist, users with a range of disabilities are using the Amazon Echo, including for unexpected cases such as speech therapy and support for caregivers. Richer voice-based applications and solutions to support discoverability would be particularly useful to users with visual impairments. These findings should inform future work on accessible voice-based IPAs.

"Accessibility Came by Accident": Use of Voice-Controlled Intelligent Personal Assistants by People with Disabilities

Over the last three decades, video games have evolved from a pastime into a force of change that is transforming the way people perceive, learn about, and interact with the world around them. In addition to entertainment, games are increasingly used for other purposes such as education or health. Despite this increased interest, a significant number of people encounter barriers when playing games due to a disability. Accessibility problems may include the following: (1) not being able to receive feedback; (2) not being able to determine in-game responses; (3) not being able to provide input using conventional input devices. This paper surveys the current state-of-the-art in research and practice in the accessibility of video games and points out relevant areas for future research. A generalized game interaction model shows how a disability affects ones ability to play games. Estimates are provided on the total number of people in the United States whose ability to play games is affected by a disability. A large number of accessible games are surveyed for different types of impairments, across several game genres, from which a number of high- and low-level accessibility strategies are distilled for game developers to inform their design.

/pdf/game-accessibility-a-survey-4jl11mh4gd.pdf

Game accessibility: a survey

We present a system whereby the human voice may specify continuous control signals to manipulate a simulated 2D robotic arm and a real 3D robotic arm. Our goal is to move towards making accessible the manipulation of everyday objects to individuals with motor impairments. Using our system, we performed several studies using control style variants for both the 2D and 3D arms. Results show that it is indeed possible for a user to learn to effectively manipulate real-world objects with a robotic arm using only non-verbal voice as a control mechanism. Our results provide strong evidence that the further development of non-verbal voice controlled robotics and prosthetic limbs will be successful.

The VoiceBot: a voice controlled robot arm

Purpose. Mouse control has become a crucial aspect of many modern day computer interactions. This poses a challenge for individuals with motor impairments or those whose use of hands is restricted due to situational constraints. We present a system called the Vocal Joystick which allows the user to continuously control the mouse cursor by varying vocal parameters such as vowel quality, loudness and pitch.Method. Evaluations were conducted to characterize expert performance capability of the Vocal Joystick, and to compare novice user performance and preference for the Vocal Joystick and two other existing speech based cursor control methods.Results. Our results show that Fitts' law, a well adopted model of human motor performance for movement tasks, is a good predictor of the speed – accuracy tradeoff for the Vocal Joystick, and suggests that the optimal performance of the Vocal Joystick may be comparable to that of a conventional hand-operated joystick. Novice user evaluations show that the Vocal Joystick...

The Vocal Joystick: Evaluation of voice-based cursor control techniques for assistive technology

We present a novel classification model that is formulated as a ratio of semi-definite polynomials. We derive an efficient learning algorithm for this classifier, and apply it to two separate phoneme classification corpora. Results show that our disciminatively trained model can achieve accuracies comparable with state-of-the-art techniques such as multi-layer perceptrons, but does not posses the overconfident bias often found in models based on ratios of exponentials.

Ratio semi-definite classifiers

We present a novel approach for training a multi-layered perceptron (MLP) in a semi-supervised fashion. Our objective function, when optimized, balances training set accuracy with fidelity to a graph-based manifold over all points. Additionally, the objective favors smoothness via an entropy regularizer over classifier outputs as well as straightforward `2 regularization. Our approach also scales well enough to enable large-scale training. The results demonstrate significant improvement on several phone classification tasks over baseline MLPs.

On the semi-supervised learning of multi-layered perceptrons.

We propose and describe several methods for using speech power as an estimate of intentional loudness, and a mapping from this loudness estimate to a continuous control. This is performed in the context of a novel voice-based human-computer interface designed to enable individuals with motor impairments to use vocal tract parameters for both discrete and continuous control tasks. The interface uses vocal gestures to control continuous movement and discrete sounds for other events. We conduct a user preference survey to gauge user reaction to the various methods in a mouse cursor control context. We find that loudness is an effective mechanism to control mouse cursor movement speed when mapping vocalic gestures to spatial position

Energy and loudness for speed control in the vocal joystick

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