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Model: jonatasgrosman/wav2vec2-large-xlsr-53-polish
Source: Original Platform

README.md

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+---
+language: pl
+license: apache-2.0
+datasets:
+- common_voice
+- mozilla-foundation/common_voice_6_0
+metrics:
+- wer
+- cer
+tags:
+- audio
+- automatic-speech-recognition
+- hf-asr-leaderboard
+- mozilla-foundation/common_voice_6_0
+- pl
+- robust-speech-event
+- speech
+- xlsr-fine-tuning-week
+model-index:
+- name: XLSR Wav2Vec2 Polish by Jonatas Grosman
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice pl
+      type: common_voice
+      args: pl
+    metrics:
+    - name: Test WER
+      type: wer
+      value: 14.21
+    - name: Test CER
+      type: cer
+      value: 3.49
+    - name: Test WER (+LM)
+      type: wer
+      value: 10.98
+    - name: Test CER (+LM)
+      type: cer
+      value: 2.93
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Robust Speech Event - Dev Data
+      type: speech-recognition-community-v2/dev_data
+      args: pl
+    metrics:
+    - name: Dev WER
+      type: wer
+      value: 33.18
+    - name: Dev CER
+      type: cer
+      value: 15.92
+    - name: Dev WER (+LM)
+      type: wer
+      value: 29.31
+    - name: Dev CER (+LM)
+      type: cer
+      value: 15.17
+---
+
+# Fine-tuned XLSR-53 large model for speech recognition in Polish
+
+Fine-tuned [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on Polish using the train and validation splits of [Common Voice 6.1](https://huggingface.co/datasets/common_voice).
+When using this model, make sure that your speech input is sampled at 16kHz.
+
+This model has been fine-tuned thanks to the GPU credits generously given by the [OVHcloud](https://www.ovhcloud.com/en/public-cloud/ai-training/) :)
+
+The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
+
+## Usage
+
+The model can be used directly (without a language model) as follows...
+
+Using the [HuggingSound](https://github.com/jonatasgrosman/huggingsound) library:
+
+```python
+from huggingsound import SpeechRecognitionModel
+
+model = SpeechRecognitionModel("jonatasgrosman/wav2vec2-large-xlsr-53-polish")
+audio_paths = ["/path/to/file.mp3", "/path/to/another_file.wav"]
+
+transcriptions = model.transcribe(audio_paths)
+```
+
+Writing your own inference script:
+
+```python
+import torch
+import librosa
+from datasets import load_dataset
+from transformers import Wav2Vec2ForCTC, Wav2Vec2Processor
+
+LANG_ID = "pl"
+MODEL_ID = "jonatasgrosman/wav2vec2-large-xlsr-53-polish"
+SAMPLES = 5
+
+test_dataset = load_dataset("common_voice", LANG_ID, split=f"test[:{SAMPLES}]")
+
+processor = Wav2Vec2Processor.from_pretrained(MODEL_ID)
+model = Wav2Vec2ForCTC.from_pretrained(MODEL_ID)
+
+# Preprocessing the datasets.
+# We need to read the audio files as arrays
+def speech_file_to_array_fn(batch):
+    speech_array, sampling_rate = librosa.load(batch["path"], sr=16_000)
+    batch["speech"] = speech_array
+    batch["sentence"] = batch["sentence"].upper()
+    return batch
+
+test_dataset = test_dataset.map(speech_file_to_array_fn)
+inputs = processor(test_dataset["speech"], sampling_rate=16_000, return_tensors="pt", padding=True)
+
+with torch.no_grad():
+    logits = model(inputs.input_values, attention_mask=inputs.attention_mask).logits
+
+predicted_ids = torch.argmax(logits, dim=-1)
+predicted_sentences = processor.batch_decode(predicted_ids)
+
+for i, predicted_sentence in enumerate(predicted_sentences):
+    print("-" * 100)
+    print("Reference:", test_dataset[i]["sentence"])
+    print("Prediction:", predicted_sentence)
+```
+
+| Reference  | Prediction |
+| ------------- | ------------- |
+| """CZY DRZWI BYŁY ZAMKNIĘTE?""" | PRZY DRZWI BYŁY ZAMKNIĘTE |
+| GDZIEŻ TU POWÓD DO WYRZUTÓW? | WGDZIEŻ TO POM DO WYRYDÓ |
+| """O TEM JEDNAK NIE BYŁO MOWY.""" | O TEM JEDNAK NIE BYŁO MOWY |
+| LUBIĘ GO. | LUBIĄ GO |
+| — TO MI NIE POMAGA. | TO MNIE NIE POMAGA |
+| WCIĄŻ LUDZIE WYSIADAJĄ PRZED ZAMKIEM, Z MIASTA, Z PRAGI. | WCIĄŻ LUDZIE WYSIADAJĄ PRZED ZAMKIEM Z MIASTA Z PRAGI |
+| ALE ON WCALE INACZEJ NIE MYŚLAŁ. | ONY MONITCENIE PONACZUŁA NA MASU |
+| A WY, CO TAK STOICIE? | A WY CO TAK STOICIE |
+| A TEN PRZYRZĄD DO CZEGO SŁUŻY? | A TEN PRZYRZĄD DO CZEGO SŁUŻY |
+| NA JUTRZEJSZYM KOLOKWIUM BĘDZIE PIĘĆ PYTAŃ OTWARTYCH I TEST WIELOKROTNEGO WYBORU. | NAJUTRZEJSZYM KOLOKWIUM BĘDZIE PIĘĆ PYTAŃ OTWARTYCH I TEST WIELOKROTNEGO WYBORU |
+
+## Evaluation
+
+1. To evaluate on `mozilla-foundation/common_voice_6_0` with split `test`
+
+```bash
+python eval.py --model_id jonatasgrosman/wav2vec2-large-xlsr-53-polish --dataset mozilla-foundation/common_voice_6_0 --config pl --split test
+```
+
+2. To evaluate on `speech-recognition-community-v2/dev_data`
+
+```bash
+python eval.py --model_id jonatasgrosman/wav2vec2-large-xlsr-53-polish --dataset speech-recognition-community-v2/dev_data --config pl --split validation --chunk_length_s 5.0 --stride_length_s 1.0
+```
+
+## Citation
+If you want to cite this model you can use this:
+
+```bibtex
+@misc{grosman2021xlsr53-large-polish,
+  title={Fine-tuned {XLSR}-53 large model for speech recognition in {P}olish},
+  author={Grosman, Jonatas},
+  howpublished={\url{https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-polish}},
+  year={2021}
+}
+```