Lengoo 20M Series Cold Ewey Tech Crunch
Despite all the hype around AI, there are still many challenges in leveraging machine learning for translation. One of the biggest challenges is the lack of a feedback loop between the translation process and the AI tool. This article discusses what companies can do to overcome this challenge and make the translation process easier and Lengoo 20m Seriescoldeweytechcrunch.
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Workflow between companies and translators
Managing a translation workflow can be difficult, particularly when you’re dealing with content in many different languages. But the good news is that there are some simple tools that can help you make sure that your workflow is efficient.
One tool you might consider is Trello, which is a Kanban system that allows you to track and manage projects and tasks. Trello can be particularly useful if you have a small team of people working on a single project. But Trello can become unwieldy if you have too many projects to manage.
Another great tool for managing translation workflow is machine learning. Machine learning is a technology that uses artificial intelligence to analyze and improve the way that humans perform certain tasks. For example, it might be able to improve a translation by a factor of ten. This doesn’t mean that it will completely replace human translators. But it could make a key feature of your product easier to implement.
AI tool works well to translate the meaning of a product in a creative manner
Whether you are releasing a new product or are trying to break communication gaps, Lengoo can help. With their augmented translation tool, you can get a real sense of what a word means in a different language. Their AI tool also helps you translate content creatively.
The company plans to create their own neural machine translation framework. They train the model with feedback from the translation process and with customer documents. Then, they customize the model to fit the needs of a specific client. This is done by building a model based on the client’s website and data.
The machine translation has a built-in quality check. If a human reviewer finds any discrepancies, they can correct the machine’s output. This frees the human translator to focus on more important sentences. The fewer corrections, the faster the translation.
The Lengoo AI tool can also translate words from a different language. The company also offers apps for easy consumer use. They can translate content in up to 25 languages.
Limited translator-AI feedback loop
Despite the best efforts of a small army of savvy machine learning experts, the MT system is a work in progress. That’s a pity, since translators are keen to get their hands on the latest linguistic technology, and want to see a return on their investment. But alas, the MT system is no panacea, and requires constant human intervention, as any seasoned localizer knows all too well.
There are a few MT solutions on the market, but none of them come close to integrating human collaboration into the machine. One example is ModernMT, which uses AI to generate corrective feedback in real-time. This is especially useful for those tasked with interpreting a high-volume document or series of documents in a single day. The system is also tightly integrated into foundational CAT tools, making it easier to deploy across your enterprise. It also enlightens translators with the latest in machine translation technology. MT is also about more than a computer, and is a key component in the success of today’s translation businesses.
Investment in machine learning
Several business angels participated in Lengoo’s Series A round, including Creathor Ventures, Redalpine, and Piton Capital. The round also included Target Global, Project A Ventures, and Draper Esprit. This funding round will allow Lengoo to expand its technology stack, improve its product, and build a global presence for its global active clients.
Lengoo uses machine learning to translate content and match businesses with freelance linguists. Using its own proprietary technology, Lengoo claims to reduce translation costs by half. Lengoo’s neural machine translation framework integrates multiple pipelines and processes. In turn, it improves speed and consistency in translations. Lengoo trains the model using customer language data and feedback from its translation process. Its feedback loop depends on the model’s use and on the context of the text.
The company has also benefited from European Union funding to support its training approach. Lengoo trains its models on customer language data, and uses feedback from the translation process to create a customized model for each client.
