The lifetime of the computer has been marked by an ongoing struggle to communicate with the machine. When two human conversational participants come from different languages, true communication only occurs when one can learn to speak in the language of the other.
At the beginning of the history of computation, it was the human who had to use the language of the machine; early programmers expressed themselves in binary. But over time, we built better interfaces. Binary machine code was replaced by languages employing commands that took the form of words. Typed command-line interfaces gave way to graphical interfaces and abstractions of file systems that suggested physical space. Commands took the form of mouse or swipe gestures.
Through these technologies, we are being introduced to digital assistants and textual interfaces that empower us to help ourselves.
Designing these systems requires overcoming certain challenges, of course. Cognitive ergonomics is a design philosophy recognizing that just as an ergonomic keyboard might bend so that the user’s wrists do not have to, a system’s design should bend so that the user’s natural processes for accomplishing a task do not have to. More and more, users expect not to be forced to bend to communicate to a computer.
Revolution Slider Error: Slider with alias rev-single-post-18 not found. Maybe you mean: 'rev3' or 'rev1'
When the communication takes the form of natural language, people would prefer to be able to converse as if the dialogue partner were another human. A move away from “interactive responses” and toward “dialogue,” however, entails more than just a shift in thinking away from menus and keyword detection.
Designing systems for natural human communication is challenging; dialogue breaks the “rules.” For example, it is not news to anyone who communicates via any of the text-based channels that these environments have developed a dialect of their own. “Textspeak” often involves deliberate modifications to the spelling and grammatical standards of natural language, and this has spawned entire domains of linguistic research.
The phenomenon, however, is hardly new to human communication. Morse code operators, in the interest of economizing their keystrokes, also developed a shorthand that can still be observed today by listening in on the conversation between any two ham operators, such as:
NC1M DE AA1JD GA DR OM UR RST 5NN HR QTH TIMBUKTU OP IS MATT HW? NC1M DE AA1JD KN
Translation: To NC1M from AA1JD: Good afternoon dear old man (buddy). Your signal is very readable (5) and very strong (9), with very good tone (9)). I’m located in Timbuktu. The operator’s (my) name is Matt. How do you copy? To NC1M from AA1JD, listening for response from a specific station.
Multiple publications have claimed that roughly 15 percent of the words occurring in SMS and Twitter text are not found in the dictionary, which is a significant problem for automated NLP tools hoping to communicate with users via text.