This blog post is intended for all those students who started their studies of conference interpreting right after the outbreak of Covid-19. More than one year into the pandemic, many of them haven’t entered a physical booth or put their hands on a hard console yet.
In order to not leave them completely unprepared, I have assembled some very basic guidance. There are many different interpreting consoles out there, the ones you see here are just three random ones to give you an idea. Many thanks to Magdalena Lindner-Juhnke and Inés de Chavarría for helping with the pictures and to Tefik Cevikel from Schneider Konferenz Systeme for letting me take a video in their hub in Düsseldorf.
And here is a short video on how to find your relais:
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C), and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
Beim Dolmetschen gendern – das habe ich bislang eigentlich ganz munter „nach Gefühl“ gehandhabt. Klar, wenn die Rednerin oder der Redner der Ausgangssprache gendert, übernehme ich das in der Zielsprache – sofern die sprachlichen Mittel das hergeben. Aber wenn die Originalsprache etwa Englisch ist, ist die Lage häufig alles andere als klar. Viele Benennungen erfordern keine Differenzierung bzw. lassen diese auch nicht erkennen (participant, doctor, president, friend). Das lässt uns beim Dolmetschen mitunter nicht nur graue Haare wachsen, weil wir nur raten oder blitzschnell nachschlagen können, ob the commissioner nun Herr Kommissar oder Frau Kommissarin ist, sondern weil sich auch noch die vertrackte Frage stellt, ob bzw. wie wir in der Zielsprache – wenn diese zum Beispiel Deutsch oder Spanisch ist – gendern.
Zur Frage, ob ich gendere, ist die Antwort dolmetsch-typisch ganz klar: Es kommt auf den Kontext an. Wir dolmetschen für den Moment. Relevant ist, ob die redende Person gendern würde, wenn ihre Sprache die Mittel dafür hergäbe. Es stellt sich also jedes Mal die Frage: Wer redet? Was ist die Intention der vortragenden Person? In welchem Kreis befinden wir uns (Frauenausschuss, Monteurschulung, Fraktionssitzung der Grünen oder Bilanzpressekonferenz)?
Bleibt die Frage, wie ich gendere. Was mache ich zum Beispiel aus dem gender-neutralen englischen Dear participants? Beim Dolmetschen ins Deutsche habe ich hier durchaus die Qual der Wahl zwischen unterschiedlichen Spielarten der Gendersprache. Im Sinne einer schnellen Entscheidungsfindung, wie wir sie beim Simultandolmetschen brauchen, könnte man grob unterscheiden zwischen:
progressiver Gendersprache – Neuschöpfungen wie die gesprochene “Binnen-Lücke” mit Glottisschlag, verschriftlicht als TeilnehmerInnen/Teilnehmer_innen/Teilnehmer:innen/Teilnehmer*innen;
konservativer Gendersprache – Doppelnennung wie Teilnehmerinnen und Teilnehmer, Schülerinnen und Schüler, Kolleginnen und Kollegen, wie sie schon sehr lange üblich sind;
“vermeidender” Gendersprache – Umgehung des Genderns durch Substantivierung (die Zuhörerschaft, das Publikum), Gerundium (Studierende, Teilnehmende) oder alternative Ausdrücke (verfügt über eine Promotion in statt hat einen Doktor in, Personal/Belegschaft statt Mitarbeiter).
Interessanterweise ist die Auswahl im Spanischen durchaus ähnlich:
Was den Deutschsprachigen das progressive Gendersternchen bzw. die Binnenlücke, ist der spanischsprachigen Welt das neugeschöpfte so genannte dritte linguistische Genus – „el tercer género linguístico“: Statt todos y todas heißt es todes oder gleich todas, todas y todes, entsprechend (queridos, queridas y) querides participantes (im Schriftlichen auch wahlweise lxs participantes, l@s participantes, aber das ist für das Dolmetschen ja nicht relevant). Was beiden Phänomenen gemein ist: Sie sind neu, ungemein praktisch und nicht minder unumstritten. Für den persönlichen Umgang mit der deutschen und spanischen Sprache macht es das vielleicht kompliziert, aber im Dolmetschen kann man zumindest grob davon ausgehen, dass die Freund_innen und les amiges in ihrer Intention und Wirkung ähnlich sind.
Ansonsten gibt es auch hier die „konservative“ Doppelnennung (etwa queridas y queridos participantes oder compañeros, compañeras) und die unauffällige Umgehung durch alternative Substantive (estimada audiencia statt estimados auditores, la ciudadanía statt los ciudadanos) oder Adjektive (el desempleo juvenil statt desempleo entre los jóvenes), genderneutrale Pronomina (quienes quieran statt los/las que quieran, cualquiera statt todos/todas) oder Umschreibungen (personas que trabajan aqui statt trabajadores).
Für meine tägliche Arbeit hoffe ich, dass mir eine solche etwas strukturiertere Herangehensweise helfen wird, den richtigen Gender-Ton zu treffen. Danken möchte ich in dem Zusammenhang meinen Studierenden des MA Konferenzdolmetschen an der TH Köln für den angeregten Austausch! Über weitere gute Tipps und Ideen rund um das mehrsprachige Gendern freue ich mich natürlich 🙂
Über die Autorin:
Anja Rütten ist freiberufliche Konferenzdolmetscherin für Deutsch (A), Spanisch (B), Englisch (C) und Französisch (C) in Düsseldorf. Sie widmet sich seit Mitte der 1990er dem Wissensmanagement.
No more traveling, paper coffee cups and the like … instead it’s videoconference interpreting, paperless office, and paperless booth (or no booth at all, for that matter) … so could we be any more eco-friendly at all? We could indeed – after all, we are generating tons of digital waste in our „new normal“ everyday life. Huge amounts of data is stored in data centres and being sent back and forth from „the cloud“ to our personal devices every second, all of which requires computing power and drives energy consumption. Just writing and sending an email releases ten grams of CO2 – this is one of the things I learnt from Siegfried Behrendt, head of the „Resources, Economics & Resilience“ department at the Institute for Future Studies and Technology Assessment in Berlin, in this article by Thomas Röbke (link to the German version below). It is a really interesting read about how to reduce our computer- or cloud-related carbon footprint.
Here are some tips I found relevant for conference interpreters (and ordinary human beings):
Use climate-neutral email providers, search engines (like Ecosia or Gexsi), streaming platforms (Betterstream), and online shops.
When streaming videos, choose standard definition (SD) instead of high definition (HD) or ultra-high definition (UHD).
Switch of your camera in videoconferences if there is no need for you to be seen (which, on the other hand, makes meetings less communicative). Consider making phone calls instead of zooming from time to time. Consider using a chat instead of a parallel video connection to stay in touch with your remote boothmate.
Avoid sending unnecessary emails and saving them forever on your provider’s server. Empty your sent folder regularly. For example, when organising a large team of interpreters, avoid sending all documents in all languages to the whole team.
Don’t send pictures if you can send texts instead (e.g. a link instead of a screenshot of a webpage). Delete pictures you don’t need (Do you really need five versions of the same motive?).
Choose a cable or Wifi over a mobile data connection, which is the most energy-intensive option.
Don’t duplicate all your data by saving it permanently on your hard drive and in the cloud. However, this makes observing the backup rule of three more difficult. Alternatively, you can start by using external hard drives or USB sticks to backup data you don’t normally need access to (more data on your hard drive requires more computing power).
There are certainly many more things we can do to become greener digital conference interpreters, or citizens. Just drop me a line or leave a comment to share your thoughts!
Further reading on how to be a green conference interpreter:
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C), and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
One year into the pandemic, I thought it might be time to think about what our new normal work environment as conference interpreters will look like. Will new normal meetings and conferences return to the „real world“, or will most of them remain virtual?
I very much hope that our new reality brings the best of both worlds together and we can help conference hosts to make wise decisions as to when to meet in person or online. After many, many, many discussions I held and heard in the past year, I have tried to draw up an overview of the pros and cons of organising conferences with interpretation on-site or virtually, using interpreting hubs, or having interpreters work from their own offices. I hope you find it useful!
Did I miss anything? I will be happy to include further aspects, just drop me a line 🙂
On-site
Full remote/virtual
Hub
Participants and interpreters meet in person at a physical conference/meeting venue
Participants and interpreters all work from their own offices relying on their personal equipment and internet connections
Meeting can take place physically or virtually, interpreters work from „hubs“, i.e. in booths from a single location, RSI software permanently installed, professional technical support, secure and redundant internet connection
Host’s needs
Confidentiality
Full control over attendance
Good for open formats with no confidentiality issues
Protected server structures and connections – sensitive information is protected
Reliability
No connection issues
Risk of technical failure is accepted; participants use „standard“ equipment/connections too
Reliable, redundant connection for events where software/hardware/connection failures would be problematic or costly
Time
More time-consuming due to travel time
Good for short notice meetings, replacement straightforward (but sound checks etc. need to be factored in)
Time-saving if hub is located close to interpreters‘ offices
Logistics
More logistics required (travel, set-up of sound/interpreting system)
Short set-up time, flexible, no travel
Time and cost-saving if interpreters are closer to hub than to meeting venue
Technical equipment
Professional, state-of-the-art equipment and technical support
Reliance on interpreters‘ own equipment and expertise in using it
Professional, state-of-the-art interpreting equipment and technical support
Software
No RSI (Remote Simultaneous Interpreting) software required
RSI software to be booked/managed by organiser (or by a designated interpreter)
Professional RSI (Remote Simultaneous Interpreting) software support/hosting
Collaboration and personal contact
Personal contact, coffee break chats, lively exchanges, spontaneous encounters
Less personal contact, screen time more tiring – „Zoom fatigue“ (recommended for shorter meetings)
Personal contact possible if participants meet in person and interpreters work from hubs (but no direct contact with interpreters)
Bad sound may affect quality and hearing, USB microphones required for participants!
Bad sound may affect quality and hearing, USB microphones required for participants!
Work environment
On-site amenities: professional equipment, catering etc.
Comfortable „private“ environment
Amenities of professionally-equipped booth
Cognitive load
Cognitive load OK for full-day meetings
Cognitive load significantly higher, OK for 3-4 hours (or larger teams/work in shifts required)
Cognitive load significantly higher, OK for 3-4 hours (or larger teams/work in shifts required)
Technical equipment
Provided by organiser
Interpreter provides headset, ethernet cable, high-speed internet, back-up internet, second device, bigger screen etc.
Provided by the hub
Software
No RSI (Remote Simultaneous Interpreting) software required
RSI (Remote Simultaneous Interpreting) software to be booked/managed by organiser (or by a designated interpreter)
Professional RSI (Remote Simultaneous Interpreting) support
Collaboration and personal contact
Personal contact, teamwork, smooth handovers, mutual support (terminology, numbers, document management)
Teamwork, e.g. handovers and mutual support (terminology, numbers, document management) via chat or additional video connection
Teamwork as on-site: smooth handovers, mutual support (terminology, numbers, document management)
About the author
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C), and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
The good news is: If you want to watch all the panels and loads of useful video contributions around how technology can support you in the booth, setting up your own interpreting studio, sim-consec, digital notetaking, remote simultaneous interpreting, remote teaching any many more, it’s not too late! You can still buy the power pack (including access to all videos and lots of bonus material) until midnight on 3 March 2021 here.
This is my video contribution on How to be boothmates without sharing a booth. (which is in German with English subtitles by my dear colleague Leonie Wagener). It is about digitalising – instead of just digitising – collaboration between interpreters.
I also had the honour to moderate a panel on New Frontiers in Interpreting Technology. My four wonderful panellists were Bart Defrancq, Bianca Prandi, Jorn Rijckaert, and Oliver Pouliot. There was interpretation from spoken English into International Sign Language and vice versa provided by Helsa Borinstein and Romy O’Callaghan, and we even had live captions in English by Norma MacHaye. Even without the inspiring discussion, I could have just watched the sign language interpreting and live captioning for ages. But then the discussion as such wasn’t too bad either 🙂
Looking back on the last 25 years, it seems to me like around every five years some innovative technology comes about and changes our professional lives in a way for us to ask „how could we ever …?“
1995 – … write translations on a typewriter?
2000 – … do translations without Google/electronic dictionaries/translation memories?
2005 – … travel and run a business with no mobile internet/ phone?
2010 – … live without linguee?
2015 – … survive without your laptop/tablet in the booth?
2020 – … prepare technical conferences on your own? Live without Zoom?
So I asked my panellist colleagues what they thought the next big thing would be in 2025. For Bart, and also for Bianca, it is definitely ASR (Automatic Speech Recognition) that is going to help create a new kind of artificial boothmate, displaying difficult elements like numbers, acronyms, and named entities in real time. Bianca also thinks that the majority of interpreter colleagues will finally embrace computers as a valuable support in the booth. Oliver made me a bit envious when he said that as a sign language interpreter, for a very long time he just brought his physical self to the booth, with no technical support whatsoever (not even pen and paper I suppose). He and Jorn mentioned sign language avatars as a new technology in sign language interpreting. Jorn also explained how ASR could be a good way for deaf sign language interpreters to be able to interpret from spoken language into sign language with automatic live captions being their intermediate language.
We then discussed skills. Are there any skills, like knowing how to read a map or remembering phone numbers for our kids, that will become obsolete for conference interpreters? Won’t we memorise key terminology before each conference in the future?
There was general agreement that interpreters shouldn’t become „lazy“ and rely on a virtual boothmate to spit out any terminology needed in real-time. We should rather develop strategies as to best use CAI tools in the booth and in preparation, as Bianca put it. So predicting a „virtual boothmate’s“ errors might be a decisive skill in the future. After all, the strengths and weaknesses of humans and machines are quite different and should be used so that they complement each other, as Bart explained. Jorn gave us a very interesting account of how sign language interpreters due to COVID-19 started to do their own recordings and video editing at home instead of relying on a cameraman.
My final question was twofold: What do you wish had never been invented (like built-in laptop microphones), and which piece of hardware (e.g. a rollable 34-inch screen which I can bring to the booth) or software (for me: fully functional abstracting/automatic mind-mapping) is top on your wishlist?
Oliver explained how video auto-focus was a real nightmare for sign language interpreters, something I had never thought about before. It tends to never get the focus right, what with sign language interpreters constantly moving and gesturing. Just like Jorn, he saw perfect ASR as a real opportunity in sign language interpreting. Bart referred to the downsides of data sharing in the remote simultaneous interpreting industry. He saw speaker control as a promising feature of the future so that instead of waving at the speaker to slow down, the system will simply slow down the speech electronically as soon as certain threshold values are reached – very promising indeed! Bianca’s wishes were the nicest ones: computers serving as a „second brain“ in the booth, and – most importantly – being able to see our boothmates on RSI platforms. I couldn’t have thought of any better concluding remarks!
About the author
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C), and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C) and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
Together with Angelika Eberhardt and Peter Sand, I have compiled tips and tricks around remote simultaneous interpreting (be it from a hub or from home) that we have been collecting ourselves or that colleagues have shared with us. It is meant as an informal collection of personal experiences that work for some while others may find them completely pointless. The purpose of this document is not to discuss the pros and cons of remote vs. on-site interpreting, or recommend either of them.
This is a work-in-progress document that we will try to constantly update – so feel free to share your best practices, workarounds, and tips in the comments or via email! We will try to keep track of the credits as best we can.
„Natural Language Processing? Hey, that’s what I do for a living!“ That’s what I thought when I heard about the live talk „A Glimpse at the Future of NLP“ (big thank you to Julia Böhm for pointing this out to me). As I am always curious about what happens in AI and language processing, I registered right away. And I was not disappointed.
In this conference, Marco Turchi, Head of the Machine Translation group at Fondazione Bruno Kessler, presented recent developments in automatic speech translation. And just to make this clear: This was not about machine interpretation, but about spoken language translation (SLT): spoken language is translated into written language. This text can then be used, e.g., for subtitling. Theoretically, it could then also be passed through TTS (text to speech) in order to deliver spoken interpretation, although this is not the purpose of SLT.
The classic approach of SLT, which has been used in the past decades, is cascading. It consists of two phases: First, the source speech is converted into written text by means of automatic speech recognition (ASR). This text is then passed through a machine translation (MT) system. The downside of this approach is that once the spoken language has been converted into written text, the MT system is ignorant of, e.g., the tone of the voice, background sounds (i.e. context information), age or gender of the speaker.
Now another, rather recent approach relies on using a single neural network to directly translate the input audio signal in one language into text in a different language without first transcribing it, i.e. converting it into written text. This end-to-end SLT translates directly from the spoken source text, thus has more contextual information available than what a transcript provides. The source speech is neither „normalised“ while being converted into written text, nor divided into segments that are treated separately from each other. Despite being very new, the quality of end-to-end SLT this year has already reached parity with the 30-year-old cascade approach. But it also has its peculiarities:
As the text is not segmented automatically (or naturally by punctuation, like in written text), the system must learn how to organise the text into meaningful units (similar to, but not necessarily sentences). I was intrigued to hear that efforts are being made to find the right „ear-voice-span“ or décalage, as we human interpreters call it. While a computer does not have this human problem of limited working memory, it still has to decide when to start producing its output – a tradeoff between lagging and performance. This was the point when I decided I wanted to ask some more questions about this whole SLT subject, and had a video chat with Marco Turchi (thank you, Marco!), just to ask him some more questions that maybe only interpreters find interesting:
Question: Could an end-to-end NLP system learn from human interpreters what a good ear-voice-span is? Are there other strategies from conference interpreting that machine interpreting systems are taught to deal with difficult situations, like for example chunking, summarising, explaining/commenting, inferencing, changes of sentence order, or complete reshaping of longer passages? (and guessing, haha)? But then I guess a machine won’t necessarily struggle with the same problems humans have, like excessive speed …
Marco Turchi: Human interpreting data could indeed be very helpful as a training base. But you need to bear in mind that neural systems can’t be taught rules. You don’t just tell them „wait until there is a meaningful chunk of information you can process before you start speaking“ like you do with students of conference interpreting. Neural networks, similar to human brains, learn by pattern recognition. This means that they need to be fed with human interpreting data so that they can listen to the work of enough human interpreters in order to „intuitively“ figure out what the right ear-voice-span is. These patterns, or strategies, are only implicit and difficult to interpret. So neural networks need to observe a huge amount of examples in order to recognise a pattern, much more than the human brain needs to learn the same thing.
Question: If human training data was used, could you give me an idea of if or how the learning system would deal with all those human imperfections, like omissions, hesitations, and also mistakes?
Marco Turchi: Of course, human training data would include pauses, hesitations, and errors. But researchers are studying ways of weighing these „errors“ in a smart way, so it is a good way forward.
Question: And what happens if the machine is translating a conference on mechanical engineering and someone makes a side remark about yesterday’s football match?
Marco Turchi: Machine translation tends to be literal, not creative. It produces different options and the problem is to select from it. To a certain extent, machines can be forced to comply with rules: They can be fed preferred terminology or names of persons, or they can be told that a speech is about a certain subject matter, let’s say car engines. Automatic domain adaptation, however, is a topic still being worked on. So it might be a challenge for a computer to recognise an unforeseen change of subject. Although of course, a machine does not forget its knowledge about football just because it is translating a speech about mechanical engineering. However, it lacks the situational awareness of a human interpreter to distinguish between the purposes of different elements of a spoken contribution.
Question: One problem that was mentioned in your online talk: real-live, human training data is simply not available, mainly due to permission and confidentiality issues. How do you go about this problem at the moment?
Marco Turchi: The current approach is to create datasets automatically. For our MuSt-C corpus, we have TED talks transcribed and translated by humans. These translations with their spoken source texts are then fed into our neural network for it to learn from. There are other such initiatives, like Facebook’s CoVoSt or Europarl-ST.
Question: So when will computers outperform humans? What’s the way forward?
Marco Turchi: Bringing machine interpreting to the same level as humans is not a goal that is practically relevant. It is just not realistic. Machine learning has its limitations. There is a steep learning curve at the beginning, which then flattens at a certain level with increasing specificity. Dialects or accents, for example, will always be difficult to learn for a neural network, as it is difficult to feed it with enough of such data for the system to recognise it as something „worth learning“ and not just noise, i.e. irrelevant deviations of normal speech.
The idea of all this research is always to help humans where computers are better. Computers, unlike humans, have no creativity, which is an essential element of interpreting. But they can be better at many other things. The most obvious are recognising numbers and named entities or finding a missing word more quickly. But there will certainly be more tasks computers can fulfill to support interpreters, which we are still to discover while the technology improves.
Thank you very much, Marco!
After all, I think that I prefer being supported by a machine than the other way around. The other day, in the booth, I had to read out pre-translated questions and answers provided by the customer. It was only halfway through the first round of questions that my colleague and I realised that we were reading out machine translations that had not been post-edited. While some parts were definitely not recognisable as machine translations, others were complete nonsense content-wise (although they still sounded good). So what we did was a new kind of simultaneous on-the-fly post-editing … Well, at least we won’t get bored too soon!
Further reading and testing:
beta.matesub.com (generates subtitles)
http://voicedocs.com/transcriber (transcribes audio and video files)
https://elitr.eu/technologies (European live translator – a current project to provide a solution to transcribe audio input for hearing-impaired listeners in multiple languages)
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C) and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
Now THAT’S what I want: Virtual Reality for my ears!
Apparently, simultaneous interpreters are not the only ones suffering from Zoom fatigue, i.e. the confusion and inability to physically locate a speaker using our ears can lead to a condition that’s sometimes referred to as “Zoom Fatigue”. But it looks like there is still reason to hope that, acoustically, video conferences become more of a pleasure and less of an ordeal in years to come. At least that’s what current discussions around this topic make me hope … This (four year old!) video by BBC Click illustrates quite nicely what 3D sound for headphones is about:
Binaural recording is a method of recording sound with the intent to create an immersive 3D stereo sound sensation for the listener of actually being in the room with the performers. A dummy head, aka „Kunstkopf“, is used for recording, which has two dummy ears in the shape of human ears with microphones in them so as to simulate the perception of the human ear. Sound recorded via binaural recording is intended for replay using headphones. And the good thing is: What was originally made for the gaming and movie industry is now also bound to conquer the video conferencing market.
Mathias Johannson, the CEO of Dirac, is rather confident: In less than a decade, 3D audio over headsets with head-tracking capabilities will allow us to have remote meetings in which you can move about an actual room, having sidebar discussions with one colleague or another as you huddle close or step away. What is more, Johannson reckons that spatial audio could be made available to videoconference users early in 2021. Dirac wants to offer 3D audio technology to video chat platforms via an off-the-shelf software solution, so no expensive hardware would be required. Google, on the other hand, already advertises its Google Meet hardware for immersive sound. But from what we have learned six months into Covid-19, it is difficult even to persuade participants to wear a cabled headset (not to mention using an ethernet cable instead of a wifi connection), I am personally not too optimistic that expensive hardware is the way forward to high-quality remote simultaneous interpretation.
So, will such a software-based solution possibly not only provide a more immersive meeting experience but also be able to provide decent sound even without remote participants connected from their home offices having to use special equipment, i.e. headsets? I asked Prof. Jochen Steffens, who is a sound and video engineer, for his opinion. The answer was rather sobering regarding equipment: For 3D audio, a dry and clean recording is required, which at the moment is not possible using built-in microphones. Equipment made for binaural recording, however, would not really serve the purpose of simultaneous interpreting either, as the room sound would actually be more of a disturbance for interpreting. Binaural recording is rather made for recording the sound of real threedimensional sound impressions like in concert halls and the like. For video conferencing, rather than headsets, Steffens recommends using unidirectional microphones; he suggests, for example, an inexpensive cardioid large-diaphragm microphone, mounted on a table stand. And the good news: If you are too vain to wear a headset in video conferences, with decent sound input being delivered by a good microphone, any odd wireless in-ear earphones can be used for listening, or even the built-in speakers of your laptop as long as you turn them off while speaking.
But what about the spatial, immersive experience? And how will a spatial distribution of participants happen if, in fact, there is no real room to match the virtual distribution to? As Prof. Steffens explained to me, once you have a good quality sound input, people can indeed be mapped into a virtual space, e.g. around a table, rather easily. The next question would be if, in contrast to the conference participants, we as interpreters would really appreciate such a being-in-the-room experience. While this immersion could indeed allow for more situational awareness, we might prefer to always be acoustically positioned right in front of the person who is speaking instead of having a „round table“ experience. After all, speakers are best understood when they are placed in front of you and both ears get an equally strong input (the so-called cocktail party effect of selectively hearing only one voice works best with binaural input). And this would, by the way, nicely match a close front view of the person speaking.
And then, if ever video conferencing can offer us a useful immersive experience, couldn’t it even end up being more convenient than a „normal“ on-site simultaneous interpreting setting? More often than not, we are rather isolated in our booths with no more than a poor view of the meeting room from a faraway/high above/hidden-next-door position. So much so that I am starting to wonder if 3D audio (and video, for that matter) could also be used in on-site conference rooms. According to Prof. Steffens, this would be perfectly feasible by „simply“ using sound engineering software.
But then the next question arises: While simultaneous interpreters used to be „the voice in your ear“, they might now be assigned a position in the meeting space … the voice from above, from behind (like in chuchotage), or our voices could even come from where the speaker is sitting who is being interpreted at the moment. Although for this to happen, the speaker’s voice would have to be muted completely, which might not be what we want. Two voices coming from the same position would be hard to process for the brain. So the interpreter’s voice would need to find its own „place in space“ after all – suggestions are welcome!
About the author
Anja Rütten is a freelance conference interpreter for German (A), Spanish (B), English (C) and French (C) based in Düsseldorf, Germany. She has specialised in knowledge management since the mid-1990s.
