--- license: cc-by-nc-4.0 language: - ar pipeline_tag: token-classification datasets: - guymorlan/levanti --- # Levanti Transliterator This model converts diacritics in Palestinian colloquial Arabic to their estimated pronunciation via Hebrew vowels. It can be used to transliterate diacritized Palestinian Arabic text into Hebrew or English. The model is trained on a special subset of the Levanti dataset (to be released later). The model is fine-tuned from Google's [CANINE-s](https://huggingface.co/google/canine-s) character level LM with a token classification head. Each token (letter) of the input is classified into either of 7 classes: 'O' if not a diacritic, or one of 6 Hebrew vowels (see `model.config.id2label`). # Diacritizer This model can be used in conjunction with [Levanti Diacritizer](https://huggingface.co/guymorlan/levanti_arabic2diacritics), which add diacritics to raw Palestinian Arabic text. # Example Usage ```python from transformers import CanineForTokenClassification, AutoTokenizer import torch model = CanineForTokenClassification.from_pretrained("guymorlan/levanti_diacritics2translit") tokenizer = AutoTokenizer.from_pretrained("guymorlan/levanti_diacritics2translit") def diacritics2hebrew_vowels(text, model, tokenizer): tokens = tokenizer(text, return_tensors="pt") with torch.no_grad(): pred = model(**tokens) pred = pred.logits.argmax(-1).tolist() pred = pred[0][1:-1] # remove CLS and SEP output = [] for p, c in zip(pred, text): if p != model.config.label2id["O"]: output.append(model.config.id2label[p]) else: output.append(c) output = "".join(output) return output # to convert arabic diacritics to Hebrew diacritics (Tsere, Holam, Patah, Shva, Kubutz, Hiriq) text = "لَازِم نِعْطِي رَشَّات وِقَائِيِّة لِلشَّجَر " heb_vowels = diacritics2hebrew_vowels(text, model, tokenizer) heb_vowels ``` ``` Out[1]: 'لַازֵم نִعְطִي رַشַّات وִقַائִيֵّة لִلشַّجַر ' ``` ```python arabic_to_hebrew = { # regular letters "ا": "א", "أ": "א", "إ": "א", "ء": "א", "ئ": "א", "ؤ": "א", "آ": "אא", "ى": "א", "ب": "ב", "ت": "ת", "ث": "ת'", "ج": "ג'", "ح": "ח", "خ": "ח'", "د": "ד", "ذ": "ד'", "ر": "ר", "ز": "ז", "س": "ס", "ش": "ש", "ص": "צ", "ض": "צ'", "ط": "ט", "ظ": "ט'", "ع": "ע", "غ": "ע'", "ف": "פ", "ق": "ק", "ك": "כ", "ل": "ל", "م": "מ", "ن": "נ", "ه": "ה", "و": "ו", "ي": "י", "ة": "ה", # special characters "،": ",", "َ": "ַ", "ُ": "ֻ", "ِ": "ִ", } final_letters = { "ن": "ן", "م": "ם", "ص": "ץ", "ض": "ץ'", "ف": "ף", } def to_taatik(arabic): taatik = [] for index, letter in enumerate(arabic): if ( (index == len(arabic) - 1 or arabic[index + 1] in {" ", ".", "،"}) and letter in final_letters ): taatik.append(final_letters[letter]) elif letter not in arabic_to_hebrew: taatik.append(letter) else: taatik.append(arabic_to_hebrew[letter]) return "".join(taatik) # to convert consonants and create full hebrew transliteration (Taatik) to_taatik(heb_vowels) ``` ``` Out[2]: "לַאזֵם נִעְטִי רַשַّאת וִקַאאִיֵّה לִלשַّג'ַר " ``` ```python arabic_to_english = { "ا": "a", "أ": "a", "إ": "a", "ء": "a", "ئ": "a", "ؤ": "a", "آ": "aa", "ى": "a", "ب": "b", "ت": "t", "ث": "th", "ج": "j", "ح": "h", "خ": "kh", "د": "d", "ذ": "dh", "ر": "r", "ز": "z", "س": "s", "ش": "sh", "ص": "s", "ض": "d", "ط": "t", "ظ": "z", "ع": "a", "غ": "gh", "ف": "f", "ق": "q", "ك": "k", "ل": "l", "م": "m", "ن": "n", "ه": "h", "و": "w", "ي": "y", "ة": "h", "َ": "a", "ُ": "u", "ِ": "i", "،": ",", "ֹ": "o", # holam "ַ": "a", # patah "ִ": "i", # hiriq "ְ": "", # shva "ֻ": "u", # kubutz 'ֵ': "e", "ّ": "SHADDA" # shadda } vowels = ["،", ",", "َ", "ַ", "ُ", "ֻ", "ِ", "ִ", 'ֵ'] def to_translit(arabic): translit = [] for letter in arabic: if letter not in arabic_to_english: translit.append([letter, letter]) else: if arabic_to_english[letter] == "SHADDA": if translit[-1][0] in vowels: translit[-2][1] = translit[-2][1].upper() else: translit[-1][1] = translit[-1][1].upper() else: translit.append([letter, arabic_to_english[letter]]) return "".join([x[1] for x in translit]) # to convert letters to latin representation (English transliteration) to_translit(heb_vowels) ``` ``` Out[3]: 'laazem niatiy raSHaat wiqaaaiYeh lilSHajar ' ``` # Attribution Created by Guy Mor-Lan.
Contact: guy.mor AT mail.huji.ac.il