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import glob |
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import json |
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import os |
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from functools import partial |
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from pathlib import Path |
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import datasets |
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VERSION = datasets.Version("0.0.1") |
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SAMPLE_RATE = 16000 |
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URLS = {'introduction_psychology': 'data/introduction_psychology.zip', |
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'a_descriptive_statistics': 'data/a_descriptive_statistics.zip', |
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'inherited_how_does_the_internet_work': 'data/inherited_how_does_the_internet_work.zip', |
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'data_structures': 'data/data_structures.zip', |
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'computational_thinking': 'data/computational_thinking.zip', |
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'physics_intro': 'data/physics_intro.zip', |
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'data_intro': 'data/data_intro.zip', |
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'introduction_to_the_philosophy_of_education': 'data/introduction_to_the_philosophy_of_education.zip', |
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'yad_vashem': 'data/yad_vashem.zip', |
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'algorithms': 'data/algorithms.zip', |
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'blue-and-white_tv': 'data/blue-and-white_tv.zip', |
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'covid_mindfulness': 'data/covid_mindfulness.zip', |
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'preparation_for_a_job_interview-_ways_to_success': 'data/preparation_for_a_job_interview-_ways_to_success.zip', |
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'what_is_the_world_introduction_to_general_chemistry': 'data/what_is_the_world_introduction_to_general_chemistry.zip', |
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'networking_create_a_network_of_professional_progress': 'data/networking_create_a_network_of_professional_progress.zip', |
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'how_to_learn': 'data/how_to_learn.zip', |
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'post_modern_education': 'data/post_modern_education.zip', |
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'introduction_to_renewable_energy': 'data/introduction_to_renewable_energy.zip', |
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'science_communication': 'data/science_communication.zip', |
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'introduction_to_physics_-_mechanics': 'data/introduction_to_physics_-_mechanics.zip', |
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'negotiations_different_cultures_and_what_between_them': 'data/negotiations_different_cultures_and_what_between_them.zip', |
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'computation_models': 'data/computation_models.zip', |
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'object_oriented_programming': 'data/object_oriented_programming.zip', |
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'from_another_angle_math': 'data/from_another_angle_math.zip'} |
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class CampusHebrewSpeech(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="campus_hebrew_speech", |
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version=VERSION, |
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description=f"Campus Hebrew Speech Recognition dataset") |
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] |
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def _info(self): |
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return datasets.DatasetInfo( |
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description="Hebrew speech datasets", |
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features=datasets.Features( |
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{ |
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"uid": datasets.Value("string"), |
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"file_id": datasets.Value("string"), |
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"audio": datasets.Audio(sampling_rate=SAMPLE_RATE), |
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"sentence": datasets.Value("string"), |
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"n_segment": datasets.Value("int32"), |
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"duration_ms": datasets.Value("float32"), |
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"language": datasets.Value("string"), |
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"sample_rate": datasets.Value("int32"), |
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"course": datasets.Value("string"), |
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"sentence_length": datasets.Value("int32"), |
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"n_tokens": datasets.Value("int32"), |
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} |
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), |
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supervised_keys=("audio", "sentence"), |
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homepage="https://huggingface.co/datasets/imvladikon/hebrew_speech_campus", |
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citation="TODO", |
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) |
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def _split_generators(self, dl_manager): |
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course_links = { |
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'from_another_angle-_mathematics_teaching_practices': 'data/from_another_angle-_mathematics_teaching_practices', |
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'introduction_to_renewable_energy': 'data/introduction_to_renewable_energy', |
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'negotiations_different_cultures_and_what_between_them': 'data/negotiations_different_cultures_and_what_between_them', |
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'introduction_to_physics_-_mechanics': 'data/introduction_to_physics_-_mechanics', |
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'networking-_create_a_network_of_professional_progress': 'data/networking-_create_a_network_of_professional_progress', |
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'post_modern_education': 'data/post_modern_education', |
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'physics_intro': 'data/physics_intro', |
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'algorithms': 'data/algorithms', |
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'blue-and-white_tv': 'data/blue-and-white_tv', |
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'what_is_the_world-_introduction_to_general_chemistry': 'data/what_is_the_world-_introduction_to_general_chemistry', |
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'computational_thinking': 'data/computational_thinking', |
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'preparation_for_a_job_interview-_ways_to_success': 'data/preparation_for_a_job_interview-_ways_to_success', |
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'a_descriptive_statistics': 'data/a_descriptive_statistics', |
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'yad_vashem': 'data/yad_vashem', |
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'introduction_to_the_philosophy_of_education': 'data/introduction_to_the_philosophy_of_education', |
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'covid_mindfulness': 'data/covid_mindfulness', |
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'data_structures': 'data/data_structures', |
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'computation_models': 'data/computation_models', |
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'introduction_psychology': 'data/introduction_psychology', |
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'how_to_learn': 'data/how_to_learn', |
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'inherited_-_how_does_the_internet_work': 'data/inherited_-_how_does_the_internet_work', |
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'object_oriented_programming': 'data/object_oriented_programming', |
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'science_communication': 'data/science_communication', |
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'data_intro': 'data/data_intro'} |
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return [ |
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datasets.SplitGenerator( |
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name=datasets.Split.TRAIN, |
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gen_kwargs={ |
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"course_links": course_links, |
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"split": "train"}, |
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) |
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] |
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def _generate_examples(self, course_links, split): |
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idx = 0 |
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for course, root_path in course_links.items(): |
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root_path = "/content/hebrew_speech_campus/" + root_path |
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for metadata_file in Path(root_path).glob("*.json"): |
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audio_file = Path(metadata_file).stem + ".wav" |
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metadata = json.load(open(metadata_file, encoding="utf-8")) |
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yield idx, { |
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"uid": metadata["file"].split("_")[0], |
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"file_id": Path(metadata["file"]).stem, |
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"audio": os.path.join(root_path, audio_file), |
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"sentence": metadata["text"], |
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"n_segment": metadata["n_segment"], |
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"duration_ms": 1000 * metadata["duration"], |
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"language": metadata["language"], |
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"sample_rate": SAMPLE_RATE, |
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"course": course, |
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"sentence_length": len(metadata["text"]), |
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"n_tokens": metadata["text"].count(" ") + 1, |
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} |
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idx += 1 |
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