Idea #15: Find primordial language by using an emotional database


Premise:

For decades–or maybe even centuries–scholars and enthusiasts have been fascinated by the pursuit of an ancestral language that all humans trace their native tongues back to. There are several theories and methods concerning how exactly to find roots common to all words. However, current methods all seem a bit homogeneous. From my understanding, they tend to use brute force to analyze words across several languages, viewing the vowels and consonants until some semblance of a pattern emerges from the jumble. So far, it’s worked to some extent, with experts having constructed a vocabulary of over 500 words in a language they call “Nostratic.” It is the oldest vocabulary we’ve been able to find.

Nostratic was spoken about 20,000 years ago. A Proto-Human Language, on the other hand, may be up to 180,000 years older. That leaves quite a few years that we know nothing about, language-wise. However, I believe that a new method may be able to narrow this gap significantly.

The Concept:

Darwin was one of the first to establish the idea that emotions–more specifically, the facial expressions associated with them–are universal among humans. This has recently been proven true by researchers such as David Matsumoto. It’s arguable that because these expressions shape the face when they are made, they can influence the sounds people make when speaking while they express an emotion, in terms of both vowel pitch and actual consonants. If this is valid, then we can use  the “emotional value” of each word in several languages to see which ones match. Back when human brains were first developing Broca’s Areas, which are responsible for speech, humans had probably already been able to feel emotion. Assuming that our ancestors did what was most convenient to them, it’s possible that they assigned easy-to-make  sounds to objects with emotional associations. If, say, a fire made Uggabugga (by the way, how was he named?) happy, he may have started referring to it with sounds that are convenient to make while smiling.

The approach requires the construction of a place for several people to find words in several languages. They can look at a word, then classify it emotionally. Is it a happy word? An angry word? An icky word? And so on. Using this will help to create a list of words  strongly associated with certain emotions. Additionally, participants can create a list of words that come to mind when a certain phrase is read. This will build a thesaurus of sorts.

Once enough data has been gathered on a word, researchers can use its emotional classification to determine whether it fits with the idea of convenience. If “fire” is actually a term people associate with happiness, then combining this fact with research on happy sounds can be used to divine what Uggabugga used to call a flame.

The thesaurus can be used to see if words have a common root in the past, even if they sound different and are used in the same language.

The Pros:

  • All that’s required to collect the data is a set of dictionaries and a wiki-like website in which users find and evaluate words.
  • This approach crowdsources much of the “grunt work” of rating words, so quite a bit of the research more or less does itself.
  • Creating the “thesaurus” I mentioned can be done by several means such as web games, meaning that the data is more likely to be pure than it would be if participants were focused on finding an ancient language with their input.

The Cons:

  • This will likely have to be Internet-based, so it’s likely that researchers will run into trolls.
  • It’s possible that emotional reactions to objects have changed over the ages, so researchers may be working with improper data in some cases.
  • This will only provide the framework for a very old language. Unless outside methodology were to be implemented after conclusions have been made, we would still not know the language’s grammar system or how exactly it evolved into dialects.
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