metadata

language: tr
datasets:
  - common_voice
metrics:
  - wer
tags:
  - audio
  - automatic-speech-recognition
  - speech
license: apache-2.0
model-index:
  - name: XLSR Wav2Vec2 Turkish by Davut Emre TASAR
    results:
      - task:
          name: Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice tr
          type: common_voice
          args: tr
        metrics:
          - name: Test WER
            type: wer

wav2vec-tr-lite-AG

Usage

The model can be used directly (without a language model) as follows:

import torch
import torchaudio
from datasets import load_dataset
from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor

test_dataset = load_dataset("common_voice", "tr", split="test[:2%]") 

processor = Wav2Vec2Processor.from_pretrained("emre/wav2vec-tr-lite-AG")
model = Wav2Vec2ForCTC.from_pretrained("emre/wav2vec-tr-lite-AG")

resampler = torchaudio.transforms.Resample(48_000, 16_000)

**Test Result**: 27.30 %


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