Create README.md

README.md

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----
-license: cc
----
+---
+license: cc
+pretty_name: M-AILABS Speech Dataset (French)
+languages:
+ - fr
+task_categories:
+- speech-processing
+task_ids:
+- automatic-speech-recognition
+size_categories:
+  fr:
+  - 1K<n<10K
+---
+
+## Dataset Description
+- **Homepage:** https://www.caito.de/2019/01/the-m-ailabs-speech-dataset/
+
+### Dataset Summary
+
+The M-AILABS Speech Dataset is the first large dataset that we are providing free-of-charge, freely usable as training data for speech recognition and speech synthesis.
+
+Most of the data is based on LibriVox and Project Gutenberg. The training data consist of nearly thousand hours of audio and the text-files in prepared format.
+
+A transcription is provided for each clip. Clips vary in length from 1 to 20 seconds and have a total length of approximately shown in the list (and in the respective info.txt-files) below.
+
+
+The texts were published between 1884 and 1964, and are in the public domain. The audio was recorded by the LibriVox project and is also in the public domain – except for Ukrainian.
+
+Ukrainian audio was kindly provided either by Nash Format or Gwara Media for machine learning purposes only (please check the data info.txt files for details).
+
+
+### Languages
+
+French
+
+## Dataset Structure
+### Data Instances
+A typical data point comprises the path to the audio file, called audio and its sentence.
+
+
+### Data Fields
+
+- audio: 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: The sentence the user was prompted to speak
+
+### Data Splits
+The speech material has been subdivided into portions for train and test.
+The train split consists of [TODO] audio clips and the related sentences.
+The test split consists of [TODO] audio clips and the related sentences.
+
+
+### Contributions
+[@gigant](https://huggingface.co/gigant) added this dataset.