Datasets

WER

Com fer-lo servir / Usage

importtorchimporttorchaudiofromdatasetsimportload_datasetfromtransformersimportWav2Vec2ForCTC,Wav2Vec2Processortest_dataset=load_dataset("common_voice","ca",split="test[:2%]")processor=Wav2Vec2Processor.from_pretrained("ccoreilly/wav2vec2-large-100k-voxpopuli-catala")model=Wav2Vec2ForCTC.from_pretrained("ccoreilly/wav2vec2-large-100k-voxpopuli-catala")resampler=torchaudio.transforms.Resample(48_000,16_000)# Preprocessing the datasets.# We need to read the audio files as arraysdefspeech_file_to_array_fn(batch):speech_array,sampling_rate=torchaudio.load(batch["path"])batch["speech"]=resampler(speech_array).squeeze().numpy()returnbatchtest_dataset=test_dataset.map(speech_file_to_array_fn)inputs=processor(test_dataset["speech"][:2],sampling_rate=16_000,return_tensors="pt",padding=True)withtorch.no_grad():logits=model(inputs.input_values,attention_mask=inputs.attention_mask).logitspredicted_ids=torch.argmax(logits,dim=-1)print("Prediction:",processor.batch_decode(predicted_ids))print("Reference:",test_dataset["sentence"][:2])