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ai4bharat/indic-conformer-600m-multilingual

🤗 Hugging Face 来源automatic-speech-recognitionmit2.6 GBother✓ 296 个校验和今天更新
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IndicConformer

AI4Bharat's IndicConformers is a suite of ASR models built to deliver accurate speech-to-text conversion in all 22 official Indian languages. By leveraging cutting-edge deep learning techniques, these models provide precise transcriptions. As the country's first open-source ASR system covering such a vast array of languages, AI4Bharat Indic Conformer is a transformative tool for making technology more inclusive and accessible to all. IndicConformer is released under the MIT license.

Model Details

Model Usage

This model can be used to transcribe speech in various Indian languages. It supports two decoding strategies:

  • CTC (Connectionist Temporal Classification)
  • RNNT (Recurrent Neural Network Transducer)

Installation

Ensure that you have transformers and torchaudio installed:

pip install transformers torchaudio "onnxruntime==1.20.1" "onnx==1.20.1" "onnxruntime-gpu==1.20.1"

Inference Example

from transformers import AutoModel
import torch, torchaudio

# Load the model
model = AutoModel.from_pretrained("ai4bharat/indic-conformer-600m-multilingual", trust_remote_code=True)

# Load an audio file
wav, sr = torchaudio.load("audio.flac")
wav = torch.mean(wav, dim=0, keepdim=True)

target_sample_rate = 16000  # Expected sample rate
if sr != target_sample_rate:
    resampler = torchaudio.transforms.Resample(orig_freq=sr, new_freq=target_sample_rate)
    wav = resampler(wav)

# Perform ASR with CTC decoding
transcription_ctc = model(wav, "hi", "ctc")
print("CTC Transcription:", transcription_ctc)

# Perform ASR with RNNT decoding
transcription_rnnt = model(wav, "hi", "rnnt")
print("RNNT Transcription:", transcription_rnnt)

Supported Languages

IndicConformer-600M-Multi is trained for 22 officially recognized languages of India, including:

  • Assamese(as)
  • Bengali(bn)
  • Bodo(brx)
  • Dogri(doi)
  • Gujarati(gu)
  • Hindi(hi)
  • Kannada(kn)
  • Konkani(kok)
  • Kashmiri(ks)
  • Maithili(mai)
  • Malayalam(ml)
  • Manipuri(mni)
  • Marathi(mr)
  • Nepali(ne)
  • Odia(or)
  • Punjabi(pa)
  • Sanskrit(sa)
  • Santali(sat)
  • Sindhi(sd)
  • Tamil(ta)
  • Telugu(te)
  • Urdu(ur)

The tokenizers used for these languages can be found here

Contact

For any questions or feedback, please contact: