Inspirational stories have emerged over the last couple of years showing how companies (and individuals) have found new opportunities amid adversity. One such company is Jeenie, an interpreting startup that was founded to serve the US tourism industry. After the market was severely disrupted, Jeenie trained its eyes on the healthcare sector.
As an on-demand, healthcare interpreting platform, Jeenie was able to capitalize on the flexibility and opportunity-mindset of the post-Covid gig economy. Interpreters get higher rates on their platform (no middleman), customers pay by the minute, and Jeenie pays interpreters the same way.
As a result, recurring monthly revenue is now growing at 25%, with 90% of customers coming via doctors’ offices, clinics, and hospitals. Jeenie has even attracted some growth-equity funding in a series A that valued the interpreting platform at USD 34m.
This startup success story led us to poll our readers about what they see as the most promising, language-technology segment in which to launch a startup.
Synthetic Voices / Synthetic Dubbing was the favorite (27.6%), with Speech-to-Text (Transcription) as runner-up (21.8%). It was a draw for third place between MT and TMS (18.8%).
And bringing up the rear were Synthetic Text Generation (8.7%), Translation Marketplace (2.9%), and Other (1.4%).
Still on the topic of language tech — while over a fifth of the readers above acknowledged that startups offering speech-to-text (S2T) or automatic transcription showed potential, the technology had yet to gain traction among most respondents in another poll.
Asked if they currently use speech-to-text in their translation work, the majority said they never used it (60.7%) or, if so, rarely (16.4%). About 15% said they use S2T sometimes, while less than a tenth use the technology most of the time.
Delving deeper into the collab between human and machine, a project combines pen, touch, gesture, speech, keyboard, and mouse in a human-in-the-loop approach called MMPE.
That’s “multi-modal interface for post-editing machine translation,” which was the headliner of a SlatorPod episode featuring the duo of Nico Herbig and Josef van Genabith. Herbig is Research Engineer at deep-tech startup, Natif.ai; van Genabith is Scientific Director of MLT at DFKI.
Herbig pointed out that, each year, great tools are developed around NLP, “but what is often missing is the integration with humans. Often [...] all these tools are put somewhere in the submenu of an existing CAT tool.”
Hence, the pair decided to work on something that addresses that missing integration.
Herbig explained: “The idea was that when you switch to post-editing from normal translation, your interaction headlines change quite a lot. The mouse and keyboard were developed for producing text. So you start with an empty text box and you type your text — and, for that, mouse and keyboard are great tools [...] but in post-editing, the machine does the first draft and you edit it. The question is, are mouse and keyboard still good tools for that?”
According to van Genabith, when humans communicate with one another, they do not always use keyboard and mouse. "We speak, we gesture, we use vision, eye contact, we do lots of things. Part of the project was how we can best support all these multimodal ways of interacting with humans, or with a human and a machine, or human and content.”
Roughly half the readers we polled the week of that SlatorPod episode shared the duo’s enthusiasm, saying alternatives to the keyboard-mouse PE paradigm were either “Very promising” (25%) or “Definitely the future” (19%). Check out this new way to post-edit MT.
That is the addressable market for global language services and technology, according to Slator’s 2022 Market Report. After the challenges of 2020, the language industry made a full recovery in 2021, growing 11.75% to USD 26.6bn.
Even by conservative estimates, continued growth is expected in an industry that is relatively resistant to inflation and has been essentially future-proof for quite some time.
So high has been demand, notably in the media localization sphere, that the industry is currently experiencing a talent shortage — which has spurred stakeholders into action. Here’s what some of them are doing to address the challenge.
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Certain language denizens have even proven their skills to be so transferable that it will likely ensure steady employment no matter how pervasive task automation may be.
More than half the Slator readers we polled share the same optimism, expecting as strong a growth in 2022 as the year prior. About a quarter expect growth to still be healthy, albeit with a slight slowdown.
The rest expect growth to be either flat against 2021 (17%) or in slight decline (7.3%) — but no one expects a strong decline.