wav2vec2 large xlsr 53 breton EU AI Act Compliance Profile

wav2vec2-large-xlsr-53-breton

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

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

processor = Wav2Vec2Processor.from_pretrained("Marxav/wav2vec2-large-xlsr-53-breton") 
model = Wav2Vec2ForCTC.from_pretrained("Marxav/wav2vec2-large-xlsr-53-breton")

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

chars_to_ignore_regex = '[\\,\,\?\.\!\;\:\"\“\%\”\�\(\)\/\«\»\½\…]'

# Preprocessing the datasets.
# We need to read the audio files as arrays
def speech_file_to_array_fn(batch):
   speech_array, sampling_rate = torchaudio.load(batch["path"])
   batch["speech"] = resampler(speech_array).squeeze().numpy()
   batch["sentence"] = re.sub(chars_to_ignore_regex, '', batch["sentence"]).lower() + " "
   batch["sentence"] = re.sub("ʼ", "'", batch["sentence"])
   batch["sentence"] = re.sub("’", "'", batch["sentence"])
   batch["sentence"] = re.sub('‘', "'", batch["sentence"])
   return batch

nb_samples = 2
test_dataset = test_dataset.map(speech_file_to_array_fn)

inputs = processor(test_dataset["speech"][:nb_samples], 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)

print("Prediction:", processor.batch_decode(predicted_ids))
print("Reference:", test_dataset["sentence"][:nb_samples])

The above code leads to the following prediction for the first two samples:

• Prediction: ["neller ket dont a-benn eus netra la vez ser merc'hed evel sich", 'an eil hag egile']
• Reference: ["N'haller ket dont a-benn eus netra pa vezer nec'het evel-se.", 'An eil hag egile.']

The model can be evaluated as follows on the {language} test data of Common Voice.

import re
import torch
import

Your obligations as a wav2vec2 large xlsr 53 breton deployer

Track your progress

Sign up to track obligations, receive deadline reminders, and generate audit packages.

Tags

Languages

Library