# Load audio data You can load an audio dataset using the [`Audio`] feature that automatically decodes and resamples the audio files when you access the examples. Audio decoding is based on the [`soundfile`](https://github.com/bastibe/python-soundfile) python package, which uses the [`libsndfile`](https://github.com/libsndfile/libsndfile) C library under the hood. ## Installation To work with audio datasets, you need to have the `audio` dependencies installed. Check out the [installation](./installation#audio) guide to learn how to install it. ## Local files You can load your own dataset using the paths to your audio files. Use the [`~Dataset.cast_column`] function to take a column of audio file paths, and cast it to the [`Audio`] feature: ```py >>> audio_dataset = Dataset.from_dict({"audio": ["path/to/audio_1", "path/to/audio_2", ..., "path/to/audio_n"]}).cast_column("audio", Audio()) >>> audio_dataset[0]["audio"] {'array': array([ 0. , 0.00024414, -0.00024414, ..., -0.00024414, 0. , 0. ], dtype=float32), 'path': 'path/to/audio_1', 'sampling_rate': 16000} ``` ## AudioFolder You can also load a dataset with an `AudioFolder` dataset builder. It does not require writing a custom dataloader, making it useful for quickly creating and loading audio datasets with several thousand audio files. ## AudioFolder with metadata To link your audio files with metadata information, make sure your dataset has a `metadata.csv` file. Your dataset structure might look like: ``` folder/train/metadata.csv folder/train/first_audio_file.mp3 folder/train/second_audio_file.mp3 folder/train/third_audio_file.mp3 ``` Your `metadata.csv` file must have a `file_name` column which links audio files with their metadata. An example `metadata.csv` file might look like: ```text file_name,transcription first_audio_file.mp3,znowu się duch z ciałem zrośnie w młodocianej wstaniesz wiosnie i możesz skutkiem tych leków umierać wstawać wiek wieków dalej tam były przestrogi jak siekać głowę jak nogi second_audio_file.mp3,już u źwierzyńca podwojów król zasiada przy nim książęta i panowie rada a gdzie wzniosły krążył ganek rycerze obok kochanek król skinął palcem zaczęto igrzysko third_audio_file.mp3,pewnie kędyś w obłędzie ubite minęły szlaki zaczekajmy dzień jaki poślemy szukać wszędzie dziś jutro pewnie będzie posłali wszędzie sługi czekali dzień i drugi gdy nic nie doczekali z płaczem chcą jechać dali ``` `AudioFolder` will load audio data and create a `transcription` column containing texts from `metadata.csv`: ```py >>> from datasets import load_dataset >>> dataset = load_dataset("audiofolder", data_dir="/path/to/folder") >>> # OR by specifying the list of files >>> dataset = load_dataset("audiofolder", data_files=["path/to/audio_1", "path/to/audio_2", ..., "path/to/audio_n"]) ``` You can load remote datasets from their URLs with the data_files parameter: ```py >>> dataset = load_dataset("audiofolder", data_files=["https://foo.bar/audio_1", "https://foo.bar/audio_2", ..., "https://foo.bar/audio_n"] >>> # for example, pass SpeechCommands archive: >>> dataset = load_dataset("audiofolder", data_files="https://s3.amazonaws.com/datasets.huggingface.co/SpeechCommands/v0.01/v0.01_test.tar.gz") ``` Metadata can also be specified as JSON Lines, in which case use `metadata.jsonl` as the name of the metadata file. This format is helpful in scenarios when one of the columns is complex, e.g. a list of floats, to avoid parsing errors or reading the complex values as strings. To ignore the information in the metadata file, set `drop_metadata=True` in [`load_dataset`]: ```py >>> from datasets import load_dataset >>> dataset = load_dataset("audiofolder", data_dir="/path/to/folder", drop_metadata=True) ``` If you don't have a metadata file, `AudioFolder` automatically infers the label name from the directory name. If you want to drop automatically created labels, set `drop_labels=True`. In this case, your dataset will only contain an audio column: ```py >>> from datasets import load_dataset >>> dataset = load_dataset("audiofolder", data_dir="/path/to/folder_without_metadata", drop_labels=True) ``` For more information about creating your own `AudioFolder` dataset, take a look at the [Create an audio dataset](./audio_dataset) guide. For a guide on how to load any type of dataset, take a look at the general loading guide.