regben2ipa-mt5-base / README.md
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metadata
license: apache-2.0
language:
  - bn
metrics:
  - wer
  - cer
tags:
  - seq2seq
  - ipa
  - bengali
  - byt5
widget:
  - text: <Narail> আমি সে বাবুর মামু বাড়ি গিছিলাম।
    example_title: Narail Text
  - text: <Rangpur> এখন এই কুলো তার শেষ অই কুলো তার শেষ।
    example_title: Rangpur Text
  - text: <Chittagong> খয়দে সিআরের এইল্লা কি অবস্থা!
    example_title: Chittagong Text
  - text: <Kishoreganj> আটাইশ করছিলাম দের কানি ক্ষেত, ইবার মাইর কাইছি।
    example_title: Kishoreganj Text
  - text: <Narsingdi> তারা তো ওই খারাপ খেইলাই আসে না।
    example_title: Narsingdi Text
  - text: <Tangail> আর সব থেকে ফানি কথা হইতেছে দেখ?
    example_title: Tangail Text

Regional bengali text to IPA transcription - umt5-base

This is a fine-tuned version of the google/umt5-base for the task of generating IPA transcriptions from regional bengali text. This was done on the dataset of the competition “ভাষামূল: মুখের ভাষার খোঁজে“ by Bengali.AI.

Scores achieved till now (test scores):

  • Word error rate (wer): 0.27792885899543700
  • Char error rate (cer): 0.05638457089662550

Supported district tokens:

  • Kishoreganj
  • Narail
  • Narsingdi
  • Chittagong
  • Rangpur
  • Tangail

Loading & using the model

# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("teamapocalypseml/ben2ipa-mt5base")
model = AutoModelForSeq2SeqLM.from_pretrained("teamapocalypseml/ben2ipa-mt5base")
"""
  The format of the input text MUST BE: <district> <bengali_text>
"""
text = "<district> bengali_text_here"
text_ids = tokenizer(text, return_tensors='pt').input_ids
model(text_ids)

Using the pipeline

# Use a pipeline as a high-level helper
from transformers import pipeline
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipeline("text2text-generation", model="teamapocalypseml/ben2ipa-mt5base", device=device)
"""
  `texts` must be in the format of: <district> <contents>
"""
outputs = pipe(texts, max_length=512, batch_size=batch_size)

Credits

Done by S M Jishanul Islam, Sadia Ahmmed, Sahid Hossain Mustakim