<p>Huggingface has a <strong><a href="https://huggingface.co/Helsinki-NLP/opus-mt-ka-en" rel="nofollow noreferrer"><code>Helsinki-NLP/opus-mt-ka-en</code></a></strong> repository with a Georgian (Ka) to English (en) model. A <code>tokenizer_config.json</code> is available</p>

CC BY-SA 4.0
2021-05-26T17:42:34.493Z
i want to build my own translation system. i think it is already trained model for translation, i need tokenizer not whole model. Also i want english to georgian, not vice versa
dato nefaridze
CC BY-SA 4.0
2021-05-26T07:52:57.493Z
2021-05-26T07:52:57.493Z
Saurav Maheshkar
<p>I want to build a machine translation system from English to Georgian. Georgian is a language similar (and simpler) to the Russian language. its syntax looks like <strong>base</strong> + <strong>suffix</strong>, only <strong>suffix</strong> changes, most of the time <strong>base</strong> is frozen, to describe the time the only suffix is changed. Unfortunately, I couldn't find a morphological analyser for the Georgian language, so could you link or provide useful resources to help me to build one? or can you give me some suggestions?</p>

CC BY-SA 4.0
2021-05-26T08:12:32.447Z
Do you mean a tokeniser or a morphological analyser?
Oliver Mason
CC BY-SA 4.0
2021-05-26T17:47:59.180Z
i mean tokenizer, i have text( georgian, i will mention english for everybody to understand), "i am dato nefaridze, and living in Georgia", i think it should split these text into words ['i', 'am' 'dato', 'nefaridze' 'and' 'live' 'ing' 'in' 'Georgia']. it should put apart living word
dato nefaridze
CC BY-SA 4.0
2021-05-27T08:46:53.873Z
That's not a tokeniser. A tokeniser is mostly language-agnostic and only splits a stream of characters into words and non-words. You're looking for a morphological analyser, which can identify component parts of words, and therefore relies on knowledge about the structure of the language.
Oliver Mason
<natural-language-processing>
How to build a custom morphological analyser for translation system
dato nefaridze
# How to build a custom morphological analyser for translation system

(Asked by: username_0 on 2021-05-25)

I want to build a machine translation system from English to Georgian. Georgian is a language similar (and simpler) to the Russian language. its syntax looks like **base** + **suffix**, only **suffix** changes, most of the time **base** is frozen, to describe the time the only suffix is changed. Unfortunately, I couldn't find a morphological analyser for the Georgian language, so could you link or provide useful resources to help me to build one? or can you give me some suggestions?

**Tags:** natural-language-processing

> **Comments:**
> **username_1**: Do you mean a tokeniser or a morphological analyser?  
> **username_0**: i mean tokenizer, i have text( georgian, i will mention english for everybody to understand), "i am username_0, and living in Georgia", i think it should split these text into words ['i', 'am' 'dato', 'nefaridze' 'and' 'live' 'ing' 'in' 'Georgia']. it should put apart living word  
> **username_1**: That's not a tokeniser. A tokeniser is mostly language-agnostic and only splits a stream of characters into words and non-words. You're looking for a morphological analyser, which can identify component parts of words, and therefore relies on knowledge about the structure of the language.  

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## 1 answers

### Answer by username_2 on 2021-05-26. Score: 1

Huggingface has a **[`Helsinki-NLP/opus-mt-ka-en`](https://huggingface.co/Helsinki-NLP/opus-mt-ka-en)** repository with a Georgian (Ka) to English (en) model. A `tokenizer_config.json` is available

> **Comments:**
> **username_0**: i want to build my own translation system. i think it is already trained model for translation, i need tokenizer not whole model. Also i want english to georgian, not vice versa  

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