Use audio feature in ASR task template (#4006)

* use audio feature in ASR task template

* update datasets

* update tests

* typo

* update dataset_infos.json

Commit from https://github.com/huggingface/datasets/commit/32e0e79aa57b36a269b6f2ee38449a043a393e50

arabic_speech_corpus.py

@@ -93,7 +93,7 @@ class ArabicSpeechCorpus(datasets.GeneratorBasedBuilder):
             supervised_keys=("file", "text"),
             homepage=_URL,
             citation=_CITATION,
-            task_templates=[AutomaticSpeechRecognition(audio_file_path_column="file", transcription_column="text")],
+            task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="text")],
         )
 
     def _split_generators(self, dl_manager):

dataset_infos.json

@@ -1 +1 @@
-{"clean": {"description": "This Speech corpus has been developed as part of PhD work carried out by Nawar Halabi at the University of Southampton.\nThe corpus was recorded in south Levantine Arabic\n(Damascian accent) using a professional studio. Synthesized speech as an output using this corpus has produced a high quality, natural voice.\nNote that in order to limit the required storage for preparing this dataset, the audio\nis stored in the .flac format and is not converted to a float32 array. To convert, the audio\nfile to a float32 array, please make use of the `.map()` function as follows:\n\n\n```python\nimport soundfile as sf\n\ndef map_to_array(batch):\n    speech_array, _ = sf.read(batch[\"file\"])\n    batch[\"speech\"] = speech_array\n    return batch\n\ndataset = dataset.map(map_to_array, remove_columns=[\"file\"])\n```\n", "citation": "@phdthesis{halabi2016modern,\n  title={Modern standard Arabic phonetics for speech synthesis},\n  author={Halabi, Nawar},\n  year={2016},\n  school={University of Southampton}\n}\n", "homepage": "http://en.arabicspeechcorpus.com/arabic-speech-corpus.zip", "license": "", "features": {"file": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "phonetic": {"dtype": "string", "id": null, "_type": "Value"}, "orthographic": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "file", "output": "text"}, "task_templates": [{"task": "automatic-speech-recognition", "audio_file_path_column": "file", "transcription_column": "text"}], "builder_name": "arabic_speech_corpus", "config_name": "clean", "version": {"version_str": "2.1.0", "description": "", "major": 2, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1002365, "num_examples": 1813, "dataset_name": "arabic_speech_corpus"}, "test": {"name": "test", "num_bytes": 65784, "num_examples": 100, "dataset_name": "arabic_speech_corpus"}}, "download_checksums": {"http://en.arabicspeechcorpus.com/arabic-speech-corpus.zip": {"num_bytes": 1192302846, "checksum": "1df85219370fb1ebe8bfc46aa886265586411d04e7c1caa5a5b9847b3ad5f9de"}}, "download_size": 1192302846, "post_processing_size": null, "dataset_size": 1068149, "size_in_bytes": 1193370995}}
+{"clean": {"description": "This Speech corpus has been developed as part of PhD work carried out by Nawar Halabi at the University of Southampton.\nThe corpus was recorded in south Levantine Arabic\n(Damascian accent) using a professional studio. Synthesized speech as an output using this corpus has produced a high quality, natural voice.\nNote that in order to limit the required storage for preparing this dataset, the audio\nis stored in the .flac format and is not converted to a float32 array. To convert, the audio\nfile to a float32 array, please make use of the `.map()` function as follows:\n\n\n```python\nimport soundfile as sf\n\ndef map_to_array(batch):\n    speech_array, _ = sf.read(batch[\"file\"])\n    batch[\"speech\"] = speech_array\n    return batch\n\ndataset = dataset.map(map_to_array, remove_columns=[\"file\"])\n```\n", "citation": "@phdthesis{halabi2016modern,\n  title={Modern standard Arabic phonetics for speech synthesis},\n  author={Halabi, Nawar},\n  year={2016},\n  school={University of Southampton}\n}\n", "homepage": "http://en.arabicspeechcorpus.com/arabic-speech-corpus.zip", "license": "", "features": {"file": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "audio": {"sampling_rate": 48000, "mono": true, "decode": true, "id": null, "_type": "Audio"}, "phonetic": {"dtype": "string", "id": null, "_type": "Value"}, "orthographic": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "file", "output": "text"}, "task_templates": [{"task": "automatic-speech-recognition", "audio_column": "audio", "transcription_column": "text"}], "builder_name": "arabic_speech_corpus", "config_name": "clean", "version": {"version_str": "2.1.0", "description": "", "major": 2, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 1002365, "num_examples": 1813, "dataset_name": "arabic_speech_corpus"}, "test": {"name": "test", "num_bytes": 65784, "num_examples": 100, "dataset_name": "arabic_speech_corpus"}}, "download_checksums": {"http://en.arabicspeechcorpus.com/arabic-speech-corpus.zip": {"num_bytes": 1192302846, "checksum": "1df85219370fb1ebe8bfc46aa886265586411d04e7c1caa5a5b9847b3ad5f9de"}}, "download_size": 1192302846, "post_processing_size": null, "dataset_size": 1068149, "size_in_bytes": 1193370995}}