jimregan/clarinpl_studio

The size of the audio portion of the corpus amounts to around 56 hours, with transcriptions containing 356674 words from a vocabulary of size 46361. Note that in order to limit the required storage for preparing this dataset, the audio is stored in the .wav format and is not converted to a float32 array.

To convert the audio file to a float32 array, please make use of the `.map()` function as follows: ```python import soundfile as sf def map_to_array(batch): speech_array, _ = sf.read(batch["file"]) batch["speech"] = speech_array return batch dataset = dataset.map(map_to_array, remove_columns=["file"]) ```