HUMAN-COMPUTER INTERACTION
SECOND EDITION
HUMAN-COMPUTER INTERACTION
SECOND EDITION
This leads us to the third process of memory: information retrieval. Here we need to distinguish between two types of information retrieval, recall and recognition. In recall the information is reproduced from memory. In recognition, the presentation
Interactive input devices can themselves be split into two broad categories: those that allow text entry, and those that allow pointing, selection of particular items on the screen, and movement. The first category consists of things such as keyboards and speech recognition systems, whilst the second category comprises devices like mice, joysticks and touchscreens. We will deal with each of these categories in turn.
Handwriting is a common and familiar activity, and is therefore attractive as a method of text entry. If we were able to write as we would when we use paper, but with the computer taking this form of input and converting it to text, we can see that it is an intuitive and simple way of interacting with the computer. However, there are a number of disadvantages with handwriting recognition. Current technology is still fairly inaccurate and so makes a significant number of mistakes in recognizing letters, but has improved rapidly. Moreover, individual differences in handwriting are enormous, and make the recognition process even more difficult. The most significant information in handwriting is not in the letter shape itself but in the stroke information -- the way in which the letter is drawn. This means that devices which support handwriting recognition must capture the stroke information, not just the final character shape. This means that on-line recognition is far easier than reading handwritten text on paper. Further complications arise because letters within words are shaped and often drawn very differently depending on the actual word; the context can help determine the letter's identity, but often is unable to provide enough information. Handwriting recognition is covered in more detail later in the book, in Chapter 15. More serious in many ways is the limitation on speed; it is difficult to write at more than 25 words a minute, which is no more than half the speed of a decent typist.
The different nature of handwriting means that we may find it more useful in situations where a keyboard-based approach would have its own problems. Such situations will invariably result in completely new systems being designed around the handwriting recognizer as the predominant mode of textual input, and may bear very little resemblance to the typical system. Pen-based systems that use handwriting recognition are actively marketed in the mobile computing market, especially for smaller pocket organizers. Such machines are typically used for taking notes, jotting down and sketching ideas, as well as acting as a diary, address book and organizer. Using handwriting recognition has many advantages over using a keyboard. A pen-based system can be small and yet still accurate and easy to use, whereas small keys become very tiring, or even impossible, to use accurately. Also the pen-based approach does not have to be altered when we move from jotting down text to sketching diagrams; pen-based input is highly appropriate for this also.
Some organizer designs have dispensed with a keyboard completely. With such systems one must consider all sorts of other ways to interact with the system that are not character based. For example, we may decide to use drawings to tell the system what to do rather than commands using gesture recognition, for example drawing a line through a word in order to delete it. The important point is that a different input device that was initially considered simply as an alternative to the keyboard opens up a whole host of alternative interface designs and different possibilities for interaction. Pen-based systems that use handwriting recognition often use a special pen-based operating system, which attempts to tackle some of the problems of using a pen-based approach to what is otherwise a standard keyboard and mouse-oriented system, in much the same way as we suggested above, although there are also pen-based versions of standard operating systems.
Handwriting recognition is difficult principally because of the great differences between different people's handwriting. These differences can be used to advantage in signature authentication where the purpose is to identify the user rather than read the signature. Again this is far easier when we have stroke information as people tend to produce signatures which look slightly different from one another in detail, but are formed in a similar fashion. Furthermore, a forger who has a copy of a person's signature may be able to copy the appearance of the signature, but will not be able to reproduce the pattern of strokes.
Speech recognition is a promising area of text entry, but it has been promising for a number of years without actually delivering usable systems! It is forecast that the market for a successful system runs into billions of pounds and therefore a lot of development work is being put into this area. Indeed, practical systems are beginning to be delivered commercially so a major growth in this area may occur in coming years. There is a natural enthusiasm for being able to talk to the machine and have it respond to commands, since this form of interaction is one with which we are very familiar. Successful recognition rates of over 97% have been reported, but since this represents a letter in error in approximately every 30, or one spelling mistake every six or so words, this is stoll unacceptible (sic)! Note also that this performance is usually quoted only for a restricted vocabulary of command words. Trying to extend such systems to the level of understanding natural language, with its inherent vagueness, imprecision and pauses, opens up many more problems that have not been satisfactorily solved even for keyboard-entered natural language. Moreover, since every person speaks differently, the system has to be trained and tuned to each new speaker, or its performance decreases. Strong accents, a cold or emotion can also cause recognition problems, as can background noise. This leads us on to the question of practicality within an office environment: not only may the background level of noise cause errors, but if everyone in an open-plan office were to talk to their machine, the level of noise would dramatically increase, with associated difficulties. Confidentiality would also be harder to maintain.
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