Pickup usability dominates: a brief history of mobile text entry research and adoption

Text entry on mobile devices (e.g. phones and PDAs) has been a research challenge since devices shrank below laptop size: mobile devices are simply too small to have a traditional full-size keyboard. There has been a profusion of research into text entry techniques for smaller keyboards and touch screens: some of which have become mainstream, while others have not lived up to early expectations. As the mobile phone industry moves to mainstream touch screen interaction we will review the range of input techniques for mobiles, together with evaluations that have taken place to assess their validity: from theoretical modelling through to formal usability experiments. We also report initial results on iPhone text entry speed

Shrimp - solving collision and out of vocabulary problems in mobile predictive input with motion gesture

ABSTRACT Dictionary-based disambiguation (DBD) is a very popular solution for text entry on mobile phone keypads but suffers from two problems: 1. the resolution of encoding collision (two or more words sharing the same numeric key sequence) and 2. entering out-of-vocabulary (OOV) words. In this paper, we present SHRIMP, a system and method that addresses these two problems by integrating DBD with camera based motion sensing that enables the user to express preference through a tilting or movement gesture. SHRIMP (Small Handheld Rapid Input with Motion and Prediction) runs on camera phones equipped with a standard 12-key keypad. SHRIMP maintains the speed advantage of DBD driven predictive text input while enabling the user to overcome DBD collision and OOV problems seamlessly without even a mode switch. An initial empirical study demonstrates that SHRIMP can be learned very quickly, performed immediately faster than MultiTap and handled OOV words more efficiently than DBD

Multi-touch For General-purpose Computing An Examination Of Text Entry

In recent years, multi-touch has been heralded as a revolution in humancomputer interaction. Multi-touch provides features such as gestural interaction, tangible interfaces, pen-based computing, and interface customization – features embraced by an increasingly tech-savvy public. However, multi-touch platforms have not been adopted as everyday computer interaction devices; that is, multi-touch has not been applied to general-purpose computing. The questions this thesis seeks to address are: Will the general public adopt these systems as their chief interaction paradigm? Can multi-touch provide such a compelling platform that it displaces the desktop mouse and keyboard? Is multi-touch truly the next revolution in human-computer interaction? As a first step toward answering these questions, we observe that generalpurpose computing relies on text input, and ask: Can multi-touch, without a text entry peripheral, provide a platform for efficient text entry? And, by extension, is such a platform viable for general-purpose computing? We investigate these questions through four user studies that collected objective and subjective data for text entry and word processing tasks. The first of these studies establishes a benchmark for text entry performance on a multi-touch platform, across a variety of input modes. The second study attempts to improve this performance by iv examining an alternate input technique. The third and fourth studies include mousestyle interaction for formatting rich-text on a multi-touch platform, in the context of a word processing task. These studies establish a foundation for future efforts in general-purpose computing on a multi-touch platform. Furthermore, this work details deficiencies in tactile feedback with modern multi-touch platforms, and describes an exploration of audible feedback. Finally, the thesis conveys a vision for a general-purpose multi-touch platform, its design and rationale

Investigation of Tilt Gesture Interaction to Manipulate Text Property in Mobile Device

The objective of this study is to design and evaluate tilt gesture interaction to manipulate text property in mobile device through experiment. The function of changing the font size is added to the mobile phone information input, it can change the font size of the sent text to enhance the emotional effect of the message. The experiment evaluated performance and usability of four methods prototypes, including three new interactive methods (Shake, Leaning, and Accel) and a traditional button method. The experiment explored whether the new interaction method is comparable to the traditional button method by evaluating the workload and subjective usability of these methods. The results showed that in terms of task completion time, accuracy and subjective work, the Shake and Leaning methods can be equivalent to the button method. However, the Accel method is lower than other prototypes in these aspects. Subjective comments indicated that these new interactive methods are useful. After a period of practice and adaptation, these methods can replace traditional methods, add more functions to mobile phones and improve user efficiency. At the same time, participants expressed that changing the font size can help them express their emotions in the message to a certain extent. Even though the three new interactive methods are not superior to the button method in changing the font size of the message, these methods can still be added into the functions of mobile phone to provide users with convenience and higher practicability.MSHuman-Centered Design and Engineering, College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/169162/1/Xuesen Liu Final Thesis.pd

Optimizing Human Performance in Mobile Text Entry

Although text entry on mobile phones is abundant, research strives to achieve desktop typing performance "on the go". But how can researchers evaluate new and existing mobile text entry techniques? How can they ensure that evaluations are conducted in a consistent manner that facilitates comparison? What forms of input are possible on a mobile device? Do the audio and haptic feedback options with most touchscreen keyboards affect performance? What influences users' preference for one feedback or another? Can rearranging the characters and keys of a keyboard improve performance? This dissertation answers these questions and more. The developed TEMA software allows researchers to evaluate mobile text entry methods in an easy, detailed, and consistent manner. Many in academia and industry have adopted it. TEMA was used to evaluate a typical QWERTY keyboard with multiple options for audio and haptic feedback. Though feedback did not have a significant effect on performance, a survey revealed that users' choice of feedback is influenced by social and technical factors. Another study using TEMA showed that novice users entered text faster using a tapping technique than with a gesture or handwriting technique. This motivated rearranging the keys and characters to create a new keyboard, MIME, that would provide better performance for expert users. Data on character frequency and key selection times were gathered and used to design MIME. A longitudinal user study using TEMA revealed an entry speed of 17 wpm and a total error rate of 1.7% for MIME, compared to 23 wpm and 5.2% for QWERTY. Although MIME's entry speed did not surpass QWERTY's during the study, it is projected to do so after twelve hours of practice. MIME's error rate was consistently low and significantly lower than QWERTY's. In addition, participants found MIME more comfortable to use, with some reporting hand soreness after using QWERTY for extended periods

FEW phone file system

Trabalho apresentado no âmbito do Mestrado em Engenharia Informática, como requisito parcial para obtenção do grau de Mestre em Engenharia InformáticaThe evolution of mobile phones has made these devices more than just simple mobile communication devices. Current mobile phones include such features as built-in digital cameras, the ability to play and record multimedia contents and also the possibility of playing games. Most of these devices have support for Java developed applications, as well as multiple wireless technologies (e.g. GSM/GPRS, UMTS, Bluetooth, and Wi-Fi). All these features have been made possible due to technological evolution that led to the improvement of computational power, storage capacity, and communication capabilities of these devices. This thesis presents a distributed data management system, based on optimistic replication,named FEW Phone File System. This system takes advantage of the storage capacity and wireless communication capabilities of current mobile phones, by allowing users to carry their personal data “in” their mobile phones, and to access it in any workstation, as if they were files in the local file system. The FEW Phone File System is based on a hybrid architecture that merges the client/server model with peer-to-peer replication, that relies on periodic reconciliation to maintain consistency between replicas. The system’s server side runs on the mobile phone, and the client on a workstation. The communication between the client and the server can be supported by one of multiple network technologies, allowing the FEW Phone File System to dynamically adapt to the available network connectivity. The presented system addresses the mobile phone’s storage and power limitations by allowing multimedia contents to be adapted to the device’s specifications, thus reducing the volume of data transferred to the mobile phone, allowing for more user’s data to be stored. The FEW Phone File System also integrates mechanisms that maintain information about the existence of other copies of the stored files (e.g. WWW), avoiding the transfer of those files from the mobile device whenever accessing those copies is advantageous. Due to the increasing number of on-line storage resources (e.g. CVS/SVN, Picasa), this approach allows for those resources to be used by the FEW Phone File System to obtain the stored copies of the user’s files

INFERENCE-BASED FORENSICS FOR EXTRACTING INFORMATION FROM DIVERSE SOURCES

Digital forensics is tasked with the examination and extraction of evidence from a diverse set of devices and information sources. While digital forensics has long been synonymous with file recovery, this label no longer adequately describes the science’s role in modern investigations. Spurred by evolving technologies and online crime, law enforcement is shifting the focus of digital forensics from its traditional role in the final stages of an investigation to assisting investigators in the earliest phases — often before a suspect has been identified and a warrant served. Investigators need new forensic techniques to investigate online crimes, such as child pornography trafficking on peer-to-peer networks (p2p), and to extract evidence from new information sources, such as mobile phones. The traditional approach of developing tools tailored specifically to each source is no longer tenable given the diversity, volume of storage, and introduction rate of new devices and network applications. Instead, we propose the adoption of flexible, inference-based techniques to extract evidence from any format. Such techniques can be readily applied to a wide variety of different evidence sources without requiring significant manual work on the investigator’s part. The primary contribution of my dissertation is a set of novel forensic techniques for extracting information from diverse data sources. We frame the evaluation using two different, but increasingly important, forensic scenarios: mobile phone triage and network-based investigations. Via probabilistic descriptions of typical data structures, and using a classic dynamic programming algorithm, our phone triage techniques are able to identify user information in phones across varied models and manufacturers. We also show how to incorporate feedback from the investigator to improve the usability of extracted information. For network-based investigations, we quantify and characterize the extent of contraband trafficking on peer-to-peer networks. We suggest various techniques for prioritizing law enforcement’s limited resources. We finally investigate techniques that use system logs to generate and then analyze a finite state model of a protocol’s implementation. The objective is to infer behavior that an investigator can leverage to further law enforcement objectives. We evaluate all of our techniques using the real-world legal constraints and restrictions of investigators

Predicting and Reducing the Impact of Errors in Character-Based Text Entry

This dissertation focuses on the effect of errors in character-based text entry techniques. The effect of errors is targeted from theoretical, behavioral, and practical standpoints. This document starts with a review of the existing literature. It then presents results of a user study that investigated the effect of different error correction conditions on popular text entry performance metrics. Results showed that the way errors are handled has a significant effect on all frequently used error metrics. The outcomes also provided an understanding of how users notice and correct errors. Building on this, the dissertation then presents a new high-level and method-agnostic model for predicting the cost of error correction with a given text entry technique. Unlike the existing models, it accounts for both human and system factors and is general enough to be used with most character-based techniques. A user study verified the model through measuring the effects of a faulty keyboard on text entry performance. Subsequently, the work then explores the potential user adaptation to a gesture recognizer’s misrecognitions in two user studies. Results revealed that users gradually adapt to misrecognition errors by replacing the erroneous gestures with alternative ones, if available. Also, users adapt to a frequently misrecognized gesture faster if it occurs more frequently than the other error-prone gestures. Finally, this work presents a new hybrid approach to simulate pressure detection on standard touchscreens. The new approach combines the existing touch-point- and time-based methods. Results of two user studies showed that it can simulate pressure detection more reliably for at least two pressure levels: regular (~1 N) and extra (~3 N). Then, a new pressure-based text entry technique is presented that does not require tapping outside the virtual keyboard to reject an incorrect or unwanted prediction. Instead, the technique requires users to apply extra pressure for the tap on the next target key. The performance of the new technique was compared with the conventional technique in a user study. Results showed that for inputting short English phrases with 10% non-dictionary words, the new technique increases entry speed by 9% and decreases error rates by 25%. Also, most users (83%) favor the new technique over the conventional one. Together, the research presented in this dissertation gives more insight into on how errors affect text entry and also presents improved text entry methods