Update README.md

README.md

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 SIL is a global, faith-based nonprofit that works with local communities around the world to develop language solutions that expand possibilities for a better life.  We are involved in approximately 1,350 active language projects in 104 countries. These projects impact more than 1.1 billion people within 1,600 local communities.
 
-We long to see people flourishing in community using the languages they value most. This includes flourishing in the digital sphere where AI and Natural Language Processing (NLP) is increasingly driving the features of products. We work to make sure that the benefits of AI and NLP extend to local language communities.
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-We are currently working on:
 
-- TRANSLATION QUALITY CHECKING - When translating important information (e.g., the Bible or COVID-19 health information), translation quality must be ensured. At the same time, those wishing to create translations have limited options to check quality. Harnessing the latest artificial intelligence (AI) techniques, SIL seeks to automatically and objectively assess multiple facets of translation quality and to validate the usability of those assessments with translation experts.
-- MULTILINGUAL SPEECH SYSTEMS - SIL is collaborating with Intel to develop and deploy patent pending, AI-driven audio technology that expands possibilities for contactless and multilingual applications in linguistically diverse contexts. With this technology, speech in input audio streams can be dynamically recognized, even in cases when multiple languages might be spoken.
-- LOCAL LANGUAGE CHAT - Organizations have increasingly turned to dialogue systems to help them engage with users. As these organizations move into linguistically diverse settings, supporting chat interactions becomes challenging. The SIL chat platform natively supports natural language understanding (NLU) and conversation design in 1600+ languages.
-- MULTIMODAL LANGUAGE MODELS - With widespread focus on text-only techniques, audio represents a largely untapped source of information. Based on this, SIL is exploring multimodal (i.e., text and audio) language models. Such pre-trained models could be combined with a universal phone recognizer to lower the data requirement for a variety of NLP tasks in low resources languages like machine translation, speech recognition, dialogue, etc.
-- HUMAN IN-THE-LOOP MT - Often people wonder why machine translation is not used for local language translation. Well, as it turns out, commercial machine translation technology only supports around 100 of the 7000+ living languages. SIL is leveraging and extending new research from the NLP community to demonstrate how machine translation technology can be applied (with a human-in-the-loop) to low resources language translations. 
-- LANGUAGE IDENTIFICATION - Most commercially available systems for text language identification support 50-100 languages. SIL has built a language identification system that currently supports more than 1300 languages! In addition, we are deploying custom spoken language and accent identification systems around the world.
+We long to see people flourishing in community using the languages they value most. This includes flourishing in the digital sphere where AI and Natural Language Processing (NLP) is increasingly driving the features of products. We work to make sure that the benefits of AI and NLP extend to local language communities.