| --- |
| pretty_name: {{NAME}} |
| annotations_creators: |
| - crowdsourced |
| language_creators: |
| - crowdsourced |
| language_bcp47: |
| {{LANGUAGES}} |
| license: |
| - cc0-1.0 |
| multilinguality: |
| - multilingual |
| size_categories: |
| {{SIZES}} |
| source_datasets: |
| - extended|common_voice |
| task_categories: |
| - speech-processing |
| task_ids: |
| - automatic-speech-recognition |
| paperswithcode_id: common-voice |
| extra_gated_prompt: "By clicking on “Access repository” below, you also agree to not attempt to determine the identity of speakers in the Common Voice dataset." |
| --- |
| |
| # Dataset Card for {{NAME}} |
|
|
| ## Table of Contents |
| - [Dataset Description](#dataset-description) |
| - [Dataset Summary](#dataset-summary) |
| - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) |
| - [Languages](#languages) |
| - [Dataset Structure](#dataset-structure) |
| - [Data Instances](#data-instances) |
| - [Data Fields](#data-fields) |
| - [Data Splits](#data-splits) |
| - [Dataset Creation](#dataset-creation) |
| - [Curation Rationale](#curation-rationale) |
| - [Source Data](#source-data) |
| - [Annotations](#annotations) |
| - [Personal and Sensitive Information](#personal-and-sensitive-information) |
| - [Considerations for Using the Data](#considerations-for-using-the-data) |
| - [Social Impact of Dataset](#social-impact-of-dataset) |
| - [Discussion of Biases](#discussion-of-biases) |
| - [Other Known Limitations](#other-known-limitations) |
| - [Additional Information](#additional-information) |
| - [Dataset Curators](#dataset-curators) |
| - [Licensing Information](#licensing-information) |
| - [Citation Information](#citation-information) |
| - [Contributions](#contributions) |
|
|
| ## Dataset Description |
|
|
| - **Homepage:** https://commonvoice.mozilla.org/en/datasets |
| - **Repository:** https://github.com/common-voice/common-voice |
| - **Paper:** https://arxiv.org/abs/1912.06670 |
| - **Leaderboard:** https://paperswithcode.com/dataset/common-voice |
| - **Point of Contact:** [Anton Lozhkov](mailto:anton@huggingface.co) |
|
|
| ### Dataset Summary |
|
|
| The Common Voice dataset consists of a unique MP3 and corresponding text file. |
| Many of the {{TOTAL_HRS}} recorded hours in the dataset also include demographic metadata like age, sex, and accent |
| that can help improve the accuracy of speech recognition engines. |
| |
| The dataset currently consists of {{VAL_HRS}} validated hours in {{NUM_LANGS}} languages, but more voices and languages are always added. |
| Take a look at the [Languages](https://commonvoice.mozilla.org/en/languages) page to request a language or start contributing. |
| |
| ### Supported Tasks and Leaderboards |
| |
| The results for models trained on the Common Voice datasets are available via the |
| [🤗 Speech Bench](https://huggingface.co/spaces/huggingface/hf-speech-bench) |
| |
| ### Languages |
| |
| ``` |
| {{LANGUAGES_HUMAN}} |
| ``` |
| |
| ## Dataset Structure |
| |
| ### Data Instances |
| |
| A typical data point comprises the `path` to the audio file and its `sentence`. |
| Additional fields include `accent`, `age`, `client_id`, `up_votes`, `down_votes`, `gender`, `locale` and `segment`. |
| |
| ```python |
| { |
| 'client_id': 'd59478fbc1ee646a28a3c652a119379939123784d99131b865a89f8b21c81f69276c48bd574b81267d9d1a77b83b43e6d475a6cfc79c232ddbca946ae9c7afc5', |
| 'path': 'et/clips/common_voice_et_18318995.mp3', |
| 'audio': { |
| 'path': 'et/clips/common_voice_et_18318995.mp3', |
| 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32), |
| 'sampling_rate': 48000 |
| }, |
| 'sentence': 'Tasub kokku saada inimestega, keda tunned juba ammust ajast saati.', |
| 'up_votes': 2, |
| 'down_votes': 0, |
| 'age': 'twenties', |
| 'gender': 'male', |
| 'accent': '', |
| 'locale': 'et', |
| 'segment': '' |
| } |
| ``` |
| |
| ### Data Fields |
|
|
| `client_id` (`string`): An id for which client (voice) made the recording |
|
|
| `path` (`string`): The path to the audio file |
|
|
| `audio` (`dict`): A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`. |
|
|
| `sentence` (`string`): The sentence the user was prompted to speak |
|
|
| `up_votes` (`int64`): How many upvotes the audio file has received from reviewers |
|
|
| `down_votes` (`int64`): How many downvotes the audio file has received from reviewers |
|
|
| `age` (`string`): The age of the speaker (e.g. `teens`, `twenties`, `fifties`) |
|
|
| `gender` (`string`): The gender of the speaker |
|
|
| `accent` (`string`): Accent of the speaker |
|
|
| `locale` (`string`): The locale of the speaker |
|
|
| `segment` (`string`): Usually an empty field |
|
|
| ### Data Splits |
|
|
| The speech material has been subdivided into portions for dev, train, test, validated, invalidated, reported and other. |
|
|
| The validated data is data that has been validated with reviewers and received upvotes that the data is of high quality. |
|
|
| The invalidated data is data has been invalidated by reviewers |
| and received downvotes indicating that the data is of low quality. |
|
|
| The reported data is data that has been reported, for different reasons. |
|
|
| The other data is data that has not yet been reviewed. |
|
|
| The dev, test, train are all data that has been reviewed, deemed of high quality and split into dev, test and train. |
|
|
| ## Data Preprocessing Recommended by Hugging Face |
|
|
| The following are data preprocessing steps advised by the Hugging Face team. They are accompanied by an example code snippet that shows how to put them to practice. |
|
|
| Many examples in this dataset have trailing quotations marks, e.g _“the cat sat on the mat.“_. These trailing quotation marks do not change the actual meaning of the sentence, and it is near impossible to infer whether a sentence is a quotation or not a quotation from audio data alone. In these cases, it is advised to strip the quotation marks, leaving: _the cat sat on the mat_. |
|
|
| In addition, the majority of training sentences end in punctuation ( . or ? or ! ), whereas just a small proportion do not. In the dev set, **almost all** sentences end in punctuation. Thus, it is recommended to append a full-stop ( . ) to the end of the small number of training examples that do not end in punctuation. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("mozilla-foundation/{{DATASET_PATH}}", "en", use_auth_token=True) |
| |
| def prepare_dataset(batch): |
| """Function to preprocess the dataset with the .map method""" |
| transcription = batch["sentence"] |
| |
| if transcription.startswith('"') and transcription.endswith('"'): |
| # we can remove trailing quotation marks as they do not affect the transcription |
| transcription = transcription[1:-1] |
| |
| if transcription[-1] not in [".", "?", "!"]: |
| # append a full-stop to sentences that do not end in punctuation |
| transcription = transcription + "." |
| |
| batch["sentence"] = transcription |
| |
| return batch |
| |
| ds = ds.map(prepare_dataset, desc="preprocess dataset") |
| ``` |
|
|
| ## Dataset Creation |
|
|
| ### Curation Rationale |
|
|
| [Needs More Information] |
|
|
| ### Source Data |
|
|
| #### Initial Data Collection and Normalization |
|
|
| [Needs More Information] |
|
|
| #### Who are the source language producers? |
|
|
| [Needs More Information] |
|
|
| ### Annotations |
|
|
| #### Annotation process |
|
|
| [Needs More Information] |
|
|
| #### Who are the annotators? |
|
|
| [Needs More Information] |
|
|
| ### Personal and Sensitive Information |
|
|
| The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset. |
|
|
| ## Considerations for Using the Data |
|
|
| ### Social Impact of Dataset |
|
|
| The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in the Common Voice dataset. |
|
|
| ### Discussion of Biases |
|
|
| [More Information Needed] |
|
|
| ### Other Known Limitations |
|
|
| [More Information Needed] |
|
|
| ## Additional Information |
|
|
| ### Dataset Curators |
|
|
| [More Information Needed] |
|
|
| ### Licensing Information |
|
|
| Public Domain, [CC-0](https://creativecommons.org/share-your-work/public-domain/cc0/) |
|
|
| ### Citation Information |
|
|
| ``` |
| @inproceedings{commonvoice:2020, |
| author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.}, |
| title = {Common Voice: A Massively-Multilingual Speech Corpus}, |
| booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)}, |
| pages = {4211--4215}, |
| year = 2020 |
| } |
| ``` |
|
|
