--- tags: - speech - speech-transcription - romanian language: - ro license: mit task_categories: - automatic-speech-recognition - audio-classification - text-to-speech - text-to-audio pretty_name: RO_CV20 size_categories: - 10K Common Voices is an open-source dataset of speech recordings created by Mozilla to improve speech recognition technologies. It consists of crowdsourced voice samples in multiple languages, contributed by volunteers worldwide.
Challenges: The raw dataset included numerous recordings with incorrect transcriptions or those requiring adjustments, such as sampling rate modifications, conversion to .wav format, and other refinements essential for optimal use in developing and fine-tuning various models.
Processing: Our team, led by project manager Ionuț Vișan, carefully reviewed and manually corrected the transcriptions of all audio segments, ensuring their conversion into the required format for modern models (16k Hz sampling rate, mono channel, .wav format).
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Dataset Summary

common_voices20_audio.zip: The archive containing all processed audio segments.
Total number of audio segments: 41,431.
Total duration of all audio segments combined: approximately 47 hours.
common_voices20.csv: Contains metadata for all segments from the common_voices20_audio.
The file contains 41,431 rows and 2 columns:
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Split

To split the dataset (common_voices20.csv), we performed an 80-20 split into training and test sets using a seed value of 42, resulting in:
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How to use

If you want to download all the files from the dataset, use the following code:
Click to expand the code ```python from huggingface_hub import hf_hub_download import zipfile import os # Repo and files Dataset = "TransferRapid/CommonVoices20_ro" filenames = [ "common_voices20.csv", "test_common_voices20.csv", "train_common_voices20.csv", "common_voices20_audio.zip" ] # Download files for filename in filenames: print(f"Downloading {filename}...") file_path = hf_hub_download(repo_id=Dataset, filename=filename, repo_type="dataset", local_dir="./") print(f"Downloaded {filename} to: {file_path}") # Extract ZIP files if filename.endswith('.zip'): extracted_dir = filename.replace('.zip', '') with zipfile.ZipFile(file_path, 'r') as zip_ref: zip_ref.extractall(extracted_dir) print(f"Extracted files to: {extracted_dir}") print(os.listdir(extracted_dir)) else: print(f"{filename} is available.") ```
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Usage

The dataset can be used for:
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Communication

For any questions regarding this dataset or to explore collaborations on ambitious AI/ML projects, please feel free to contact us at: