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Setting Freelance Translation Rates in a Technologically Changing Market. Andrew D. Levine, C.T. Overview. A changing market Rethinking freelancer rates: Quotes vs. income Technologies that can put power back in freelancers’ hands: Dragon NaturallySpeaking SDL AutoSuggest
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Setting Freelance Translation Rates in a Technologically Changing Market Andrew D. Levine, C.T.
Overview • A changing market • Rethinking freelancer rates: Quotes vs. income • Technologies that can put power back in freelancers’ hands: • Dragon NaturallySpeaking • SDL AutoSuggest • Freelancer-implemented PEMT • Business cases, real and possible • Audience feedback • Personal experiences • Q&A
Freelancer rates falling • Average translation rate for Top 30 online languages: • 2008: USD 0.229 • 2010: USD 0.205 • 2012: USD 0.134 • A majority of freelancers surveyed were worried about the downward spiral of prices • Volumes increasing in most language pairs, but technology is helping to drive down costs Source: Common Sense Advisory, Inc. 2012
Correcting a power imbalance • Most translation tech development over the past quarter-century has helped the bottom line of agencies/LSCs rather than freelancers • CAT tools adopted en masse by agencies first • The famous “Trados Discount Grid” • Lots and lots of features for “agency versions” and less functionality for “freelance versions” • Requiring freelancers to use an agency’s preferred CAT tool
Correcting a power imbalance The result of decades of imbalanced translation software development: Freelancer skepticism about adoption of new technologies and of anything that claims to “increase productivity” but looks like an excuse to slash rates
How do you set your rates? • Common practice for freelancers (1990s-2000s): • “I’ll raise my rates each year… My clients need me!” • Raising rates equating with raising income (for a long time, this worked for lots of freelancers) • In recent years, translation volumes have been expanding (source: CSA) but hourly productivity has risen too • Every language pair and specialization is a different market; some are exceptional (but not forever)
How do you set your rates? • Your income is not your per-word rate • Most freelancers quote per word • Preferred approach in this presentation: Quote per word, but think in terms of time (hourly, weekly, monthly income targets)
Time vs. Money • On the margins of your freelance translation business, saving time is better than earning more $/€ per word than your “standard quote” earns you • Time more fungible as a business resource • Need for breaks undervalued during heavy work periods • Unlike $/€, the time you save is available to you immediately
Hourly output • Your hourly output varies based on: • File type (Word or scanned doc, spreadsheet/DB) • Presence of acronyms, character strings, software code, product codes • Need to research individual terms • Ability to use your own preferred software • Body factors (relaxation, strain, wakefulness)
Assessing time savings/costs • Any assessment begins by figuring out how much time a given type of project takes, on average, and how that differs from all your other types of projects. • For each client you have, examine the sort of texts they give you and look for patterns that affect how long the translation takes. • Figure out what sort of practices make you take longer and what helps you “fly”…
Productivity tools for freelancers • Alternative text input: Dictation • Works in any CAT tool, MS Word • Word completion: Auto-Suggest • Feature in SDL Trados Studio 2009-14 • Populating the target text: MT + post-editing • Feature in current versions of most CAT tools • Currently sketchy re: confidentiality, but that will change
Benefits common to these tools • Relief from repetitive strain (less typing) • Saves time when text includes lots of lengthy words (8-20 letters), repeated often • Customizability: Can be used in combination or not, or on certain types of projects only • (A common issue: All memory-intensive. Time for a new computer?)
What is dictation? • Dictating words into a computer with a microphone instead of (or in addition to) using a keyboard • To be useful to translators, it must work in different text entry environments (e.g. your favorite CAT tool, or Word) • “Speaker-dependent” S2T is needed for accuracy
Dragon (software for dictation) • Dragon NaturallySpeaking 12 (Windows); Dragon Dictate 3 (Mac) from Nuance • Available for English, French, Spanish, German, Dutch, Italian (Windows), English, French, German, Italian (Mac) • Dragon 12 Premium: $150
Dictation • Where it excels: • If you generally think faster than you type • Long, grammatically coherent sentences • Frequently reused technical jargon • Long words – highly accurate & fast • Where it stumbles: • Very short sentences/segments (1-3 words) • Only 1-3 words between pauses in speech • Need to research lots of terms • Full of acronyms, unusual proper names
Tips for using Dragon • Dump the headset that comes with the packaged version (get a real one, $30-50) • After set-up and initial training (15-30 minutes), several hours of use & patient correction over a period of days or weeks • Enunciate clearly • Dictate 50 minutes, type 10 minutes • Very good support community at www.knowbrainer.com
SDL Trados Studio AutoSuggest • “Subsegment matching” that analyzes large TMs (25,000 segments or more) and picks out words and phrases in source/target that match • Created files are called “dictionaries” • Start typing a few characters in target text and a menu of possible words or phrases pop up; select best option (4-6 keystrokes to type an 8-20 character word or phrase) • Full instructions to enable AutoSuggest and load dictionaries are at SDL website
Using AutoSuggest • Usable feature in SDL Trados Studio 2009/11/14: All versions • AutoSuggest Creator only available as an add-on for Freelance edition ($250 add-on); included with Pro edition • Even without add-on, Freelance edition can use AutoSuggest dictionaries created elsewhere: Free downloads for 19 language pairs at http://www.translationzone.com/products/sdl-trados-studio/sdl-autosuggest-tab2.html#tabs
Post-Editing Machine Translation • Many current versions of CAT tools offer MT modules to translate individual segments • Current MT modules (WordFast, MemoQ) send source-text data “to the cloud” – not target-text data – which is a problem for many clients • Given the problems of cloud MT solutions, there is a greater need for desktop solutions
Productivity effects of PEMT • The rosy scenario (Plitt & Masselot 2010): • 31% less pauses with PEMT than translation • Input speed 70% faster with PEMT than translation • MT engine trained in client-specific corpora • The dismal scenario: • Mental strain: Three different texts to process • Complex sentences that need restructuring • MT engine “flying blind” • Lots of false friends/uncommon uses of familiar words
MT for Wordfast • Google Translate API • Pay-to-use as of 2011 • $20 per 1M characters (~400,000 source words or ~$0.01 per 20 words) • Recommended for quality • Microsoft Translate API • 2M characters per month free (~800,000 source words) • Quality approaching that of Google (depends on language pair) • WorldLingo API • Free to use • Quality spottier in at least some language pairs
The cloud problem Despite attempts at allaying concerns, this will still not be enough to reassure most clients
Help is on the way! • Various “non-evil” adaptive MT projects in the works • One promising example: MATECAT • Italian-led project funded by the EU • Fully Open Source; built atop open MT engines (Moses, MyMemory) • CAT tool implementing “user-adaptive MT” • http://www.matecat.com/matecat/the-project/
Business Case: A Square Deal • Two years ago: • Patents for AXIPROM: 35% less time thanks to Dragon • Other texts from the same agency: 10-30% less time • Post-Dragon implementation, my hourly income averaged 80% higher for AXIPROM patents than the average hourly income for all other texts from that agency
Business Case: A Square Deal • Based on assessments of my hourly output for different types of texts using Dragon, I offered the following rate adjustments to the agency: • USD 0.0075 LESS per word for AXIPROM patents (~1/3 of work) • USD 0.0025 MORE per word for all other Word documents (~1/2 of work) • USD 0.0050 MORE per word for all PowerPoint and Excel files (~1/6 of work) • Result: Happy client + I earned more where I needed it more. I was less inclined to turn down their non-AXIPROM projects in favor of better-paying work elsewhere.
Hypothetical business cases • Client is an agency that offers some work in a field you know perfectly (no Termbase) and some in a field where you need to use Termbase. Negotiate a rate increase for the more time-intensive work. Be willing to accept a discount on the other work. • Harder field: 20% more time; +20%/-10% on rates • Client is a law firm that only sends scanned PDFs: Tell them you will quote a lower rate only on properly formatted Word files. You can potentially get more work from them AND earn a higher hourly average: • Word docs: 50% less time; rate 30% less; PDF rate steady
Recap of Steps to Take • Set an hourly, weekly, and/or monthly income target • Look for things that are slowing you down and keeping you from hitting your targets • Find ways to do more work in same time without sacrificing quality • Negotiate with clients to achieve goals
The point of all this? • Better balance between clients • Saving time and spending it wisely • Trial and error rather getting stuck in a rut or not evolving with the times • Consistency in hitting your income targets • More flexible in your business
Thank You! Twitter: @andrewlevine E-mail: andrew@levinetranslator.com
Audience Feedback • Part 1: Sharing Personal Experiences • Finding factors that were slowing you down/speeding you up • Software changes that made a difference to productivity over time • Successful rate negotiations that weren’t simply raising a base rate • Part 2: Questions