As part of Mission Bhashini, we are working on two major Machine Translation projects: ISHAAN and VIDYAAPATI. These projects focus on creating high-quality parallel corpora and robust bi-directional Neural Machine Translation (NMT) models for various Indian languages, enabling seamless translation between English, Hindi, and regional languages.
- ISHAAN focuses on developing translation models for translation between English, Hindi, and North-East Indian languages.
- VIDYAAPATI addresses translation needs for Hindi and several Indo-Aryan languages.
- Datasets: Parallel corpora generated in these projects cover multiple languages and domains, offering a robust foundation for developing and fine-tuning Machine Translation (MT) models.
- Pre-trained Machine Translation Models: The models are designed to handle diverse translation tasks and can be used directly or fine-tuned for specific applications.
The ISHAAN project covers the following language pairs:
| Language Pair |
|---|
| English-Assamese |
| English-Bodo |
| English-Manipuri |
| English-Nepali |
| Hindi-Manipuri |
| Assamese-Bodo |
The VIDYAAPATI project covers the following language pairs:
| Language Pair |
|---|
| Hindi-Bengali |
| Hindi-Konkani |
| Hindi-Maithili |
| Hindi-Marathi |
The following prestigious institutes are collaborating on these projects:
- IIT Bombay
- Gauhati University
- IIIT Manipur
- NIT Silchar
- North Bengal University
- IIT Bombay
- IIT Patna
- Goa University
- Jadavpur University
- Jawaharlal Nehru University (JNU)
- Indian Statistical Institute (ISI), Kolkata
pip3 install ctranslate2 mosestokenizer indic-nlp-library codecs subword-nmt
We provide two example inference scripts that use different tokenization schemes.
- Hindi to Konkani: This script uses bpe tokenizer.
- English to Manipuri: This script uses spm tokenizer.
The resources in this repository are released under the Creative Commons Attribution 4.0 International License (CC-BY 4.0). This license allows for sharing and adaptation of the material, provided appropriate credit is given.
Shield:
This work is licensed under a Creative Commons Attribution 4.0 International License.
We welcome contributions to this repository. Feel free to raise issues or submit pull requests.
For any inquiries, reach out to our team at nltmbhashini@gmail.com.