There are a number of ways for translators to invoice their clients. We can either invoice by the number of source or target words, the number of source or target characters, or by the amount of hours that we spend on a certain task. Each method has its advantages and disadvantages, but each method also has room for improvement. Look for tips for counting words and characters in the "Upgrade Your Tools" section, and read on right here for a couple of hints on how to make it easier to clock the amount of time you spend.
The most common way to log the time that we spend on an individual task is probably in an Excel spreadsheet. A few things that have made it easier for me to keep track of my time are two keyboard shortcuts:
- CTRL+; to enter the current date and
- CTRL+SHIFT+: to enter the current time.
A preconfigured spreadsheet with rows of fields for client, date, start time, end time, and rate requires the entry of relatively little information. If you then add fields such as total time (formula: =SUM(
While it is possible to record your time in this manner, there are little programs out there that make this a lot easier. Time Stamp (see http://www.syntap.com) is a free program (supported by optional donations) which allows you to track the start and end time for projects you are currently working on with a click on a button in your task bar. It is even possible to have several instances of the program running simultaneously so you can switch back and forth between different projects that you may be working on. Once you are completely done, all the time that is spent on each project is summed up and can either be printed out or saved as a text file. This is a nifty little program that requires neither a lot of computer resources nor a lot of time to learn.
Machine translation and human translation: in competition or in complementation
By John Hutchins
. Introduction
Ever since the idea of using computers to translate natural languages was first proposed in the 1940s and since the first investigations were begun in the 1950s, translators have watched developments either in scorn or in trepidation. Either they have dismissed the very notion that anyone could even believe that translation could be mechanized, or (at the other extreme) they have feared that their profession would be taken over entirely by machines.
The first of these attitudes found expression as early as 1951 in a report for Unesco by J.E.Holmström. He believed that from a machine translation (MT) system, “the resulting literary style would be atrocious and fuller of ‘howlers’ and false values than the worst that any human translator produces”. The reason was that “translation is an art; something which at every step involves personal choice between uncodifiable alternatives; not merely direct substitutions of equated sets of symbols but choices of values dependent for their soundness on the whole antecedent education and personality of the translator” (Holmström 1951). His comments preceded by three years the first tentative demonstration of a small prototype system, and were based on pure speculation. Nevertheless, such comments have been repeated again and again by translators for nearly fifty years, and no doubt they shall be heard again in the next fifty.
The second attitude has also persisted to the present day. However, there is now no doubt that computer-based translation systems are not rivals to human translators, but
they are aids to enable them to increase productivity in technical translation or they provide means of translating material which no human translator has ever attempted. In this context we must distinguish (1) machine translation (MT), which aims to undertake the whole translation process, but whose output must invariably be revised; (2) computer aids for translators (translation tools), which support the professional translator; and (3) translation systems for the ‘occasional’ non-translator user, which produce only rough versions to aid comprehension. These differences were not recognised until the late 1980s. The previous assumption had been that MT systems, whether running on a mainframe or a microcomputer, could serve all these functions with greater or lesser success. In part, this failure to identify different needs and to design systems specifically to meet them has contributed to misconceptions about translation technology and its impact for the professional translator.
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