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One thing i think about is what where would NLP and linguistics research gone if another language (other than english) was the predominant language. Granted the

One thing i think about is what where would NLP and linguistics research gone if another language (other than english) was the predominant language. Granted there is quite of bit interesting fundamental research in other countries and languages. But it seems many of problems and approaches developed in language understanding and NLP target specific idiosyncracies of the English language. If NLP researched with say German (which has a deep and overly explicit vocabulary) or Hindi or Mandarian, would the fundamental NLP approaches and problem areas be different and potentially better?

TomMarius 6y ago
I recommend you to check out NLP research regarding the Czech language. It has high quality researchers keen on making use of the language's features (it's a highly regular and expressive grammar). Sadly not much research is done, but what is done is interesting.
YeGoblynQueenne 6y ago
Agreed. The way I see it, current research directions have focused on approaches that work best with large datasets because such datasets exist for English, and because English just happens to be a language that is possible to represent well by training on large datasets. It helps of course that English is the de facto lingua franca of most of the technologically developed world (if not the rest of the world also). If another language was the lingua franca, current approaches would not work so well. The article makes a point about how we assume that pre-trained embeddings encode all relevant information about a language when this may not be the case for arbitrary languages. The article also makes a point about the morphological simplicity of English which is of course a great asset for a lingua franca, and also simplifies the language modelling task. Imagine if the lingua franca was, e.g. ancient Greek (as it was, in ancient times, all around the Mediterrannean) or something with similar morphological intricacies (and Greek is still an Indo-European language; I just don't know much about, e.g. Finno-Ugric to give an example about them).

TomMarius 6y ago

I recommend you to check out NLP research regarding the Czech language. It has high quality researchers keen on making use of the language's features (it's a highly regular and expressive grammar). Sadly not much research is done, but what is done is interesting.

YeGoblynQueenne 6y ago

Agreed. The way I see it, current research directions have focused on approaches that work best with large datasets because such datasets exist for English, and because English just happens to be a language that is possible to represent well by training on large datasets. It helps of course that English is the de facto lingua franca of most of the technologically developed world (if not the rest of the world also). If another language was the lingua franca, current approaches would not work so well. The article makes a point about how we assume that pre-trained embeddings encode all relevant information about a language when this may not be the case for arbitrary languages. The article also makes a point about the morphological simplicity of English which is of course a great asset for a lingua franca, and also simplifies the language modelling task. Imagine if the lingua franca was, e.g. ancient Greek (as it was, in ancient times, all around the Mediterrannean) or something with similar morphological intricacies (and Greek is still an Indo-European language; I just don't know much about, e.g. Finno-Ugric to give an example about them).