|
{ |
|
"train": { |
|
"description": "ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set.\n", |
|
"citation": "@inproceedings{lovenia2021ascend,\n title = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},\n author = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others},\n booktitle = {Proceedings of the International Conference on Language Resources and Evaluation, {LREC} 2022, 20-25 June 2022, Lu Palais du Pharo, France},\n publisher = {European Language Resources Association},\n year = {2022},\n pages = {}\n}\n", |
|
"homepage": "https://huggingface.co/datasets/CAiRE/ASCEND", |
|
"license": "", |
|
"features": { |
|
"id": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"path": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"audio": { |
|
"sampling_rate": 16000, |
|
"mono": true, |
|
"decode": true, |
|
"id": null, |
|
"_type": "Audio" |
|
}, |
|
"transcription": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"duration": { |
|
"dtype": "float32", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"language": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"original_speaker_id": { |
|
"dtype": "int64", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"session_id": { |
|
"dtype": "int64", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"topic": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
} |
|
}, |
|
"post_processed": null, |
|
"supervised_keys": null, |
|
"task_templates": [ |
|
{ |
|
"task": "automatic-speech-recognition", |
|
"audio_column": "audio", |
|
"transcription_column": "transcription" |
|
} |
|
], |
|
"builder_name": "ascend", |
|
"config_name": "train", |
|
"version": { |
|
"version_str": "1.0.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 0, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 4316724, |
|
"num_examples": 9869, |
|
"dataset_name": "ascend" |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 559170, |
|
"num_examples": 1315, |
|
"dataset_name": "ascend" |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 489562, |
|
"num_examples": 1130, |
|
"dataset_name": "ascend" |
|
} |
|
}, |
|
"download_checksums": { |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/train_metadata.csv": { |
|
"num_bytes": 1081181, |
|
"checksum": "4cbdf90fe9bf53640bfc285e2539b468a6e412daeb17c36a1b5da478cd9f5b29" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/test_metadata.csv": { |
|
"num_bytes": 127658, |
|
"checksum": "15689bc1c1a0bc29b250f63221576392b627da9cc1d80e51bb1a422118b9732c" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/validation_metadata.csv": { |
|
"num_bytes": 118552, |
|
"checksum": "6e53e362991b23ffa49ed991c6062a51d8f286747f341e566c897c02bee72459" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/resolve/main/waves.tar.bz2": { |
|
"num_bytes": 929707032, |
|
"checksum": "b35cc295f1310535a8e250d534aee0adeb90bccbc027a442cdbef81146894529" |
|
} |
|
}, |
|
"download_size": 931034423, |
|
"post_processing_size": null, |
|
"dataset_size": 5365456, |
|
"size_in_bytes": 936399879 |
|
}, |
|
"validation": { |
|
"description": "ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set.\n", |
|
"citation": "@inproceedings{lovenia2021ascend,\n title = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},\n author = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others},\n booktitle = {Proceedings of the International Conference on Language Resources and Evaluation, {LREC} 2022, 20-25 June 2022, Lu Palais du Pharo, France},\n publisher = {European Language Resources Association},\n year = {2022},\n pages = {}\n}\n", |
|
"homepage": "https://huggingface.co/datasets/CAiRE/ASCEND", |
|
"license": "", |
|
"features": { |
|
"id": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"path": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"audio": { |
|
"sampling_rate": 16000, |
|
"mono": true, |
|
"decode": true, |
|
"id": null, |
|
"_type": "Audio" |
|
}, |
|
"transcription": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"duration": { |
|
"dtype": "float32", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"language": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"original_speaker_id": { |
|
"dtype": "int64", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"session_id": { |
|
"dtype": "int64", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"topic": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
} |
|
}, |
|
"post_processed": null, |
|
"supervised_keys": null, |
|
"task_templates": [ |
|
{ |
|
"task": "automatic-speech-recognition", |
|
"audio_column": "audio", |
|
"transcription_column": "transcription" |
|
} |
|
], |
|
"builder_name": "ascend", |
|
"config_name": "validation", |
|
"version": { |
|
"version_str": "1.0.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 0, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 4316724, |
|
"num_examples": 9869, |
|
"dataset_name": "ascend" |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 559170, |
|
"num_examples": 1315, |
|
"dataset_name": "ascend" |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 489562, |
|
"num_examples": 1130, |
|
"dataset_name": "ascend" |
|
} |
|
}, |
|
"download_checksums": { |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/train_metadata.csv": { |
|
"num_bytes": 1081181, |
|
"checksum": "4cbdf90fe9bf53640bfc285e2539b468a6e412daeb17c36a1b5da478cd9f5b29" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/test_metadata.csv": { |
|
"num_bytes": 127658, |
|
"checksum": "15689bc1c1a0bc29b250f63221576392b627da9cc1d80e51bb1a422118b9732c" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/validation_metadata.csv": { |
|
"num_bytes": 118552, |
|
"checksum": "6e53e362991b23ffa49ed991c6062a51d8f286747f341e566c897c02bee72459" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/resolve/main/waves.tar.bz2": { |
|
"num_bytes": 929707032, |
|
"checksum": "b35cc295f1310535a8e250d534aee0adeb90bccbc027a442cdbef81146894529" |
|
} |
|
}, |
|
"download_size": 931034423, |
|
"post_processing_size": null, |
|
"dataset_size": 5365456, |
|
"size_in_bytes": 936399879 |
|
}, |
|
"test": { |
|
"description": "ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set.\n", |
|
"citation": "@inproceedings{lovenia2021ascend,\n title = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},\n author = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others},\n booktitle = {Proceedings of the International Conference on Language Resources and Evaluation, {LREC} 2022, 20-25 June 2022, Lu Palais du Pharo, France},\n publisher = {European Language Resources Association},\n year = {2022},\n pages = {}\n}\n", |
|
"homepage": "https://huggingface.co/datasets/CAiRE/ASCEND", |
|
"license": "", |
|
"features": { |
|
"id": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"path": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"audio": { |
|
"sampling_rate": 16000, |
|
"mono": true, |
|
"decode": true, |
|
"id": null, |
|
"_type": "Audio" |
|
}, |
|
"transcription": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"duration": { |
|
"dtype": "float32", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"language": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"original_speaker_id": { |
|
"dtype": "int64", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"session_id": { |
|
"dtype": "int64", |
|
"id": null, |
|
"_type": "Value" |
|
}, |
|
"topic": { |
|
"dtype": "string", |
|
"id": null, |
|
"_type": "Value" |
|
} |
|
}, |
|
"post_processed": null, |
|
"supervised_keys": null, |
|
"task_templates": [ |
|
{ |
|
"task": "automatic-speech-recognition", |
|
"audio_column": "audio", |
|
"transcription_column": "transcription" |
|
} |
|
], |
|
"builder_name": "ascend", |
|
"config_name": "test", |
|
"version": { |
|
"version_str": "1.0.0", |
|
"description": "", |
|
"major": 1, |
|
"minor": 0, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 4316724, |
|
"num_examples": 9869, |
|
"dataset_name": "ascend" |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 559170, |
|
"num_examples": 1315, |
|
"dataset_name": "ascend" |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 489562, |
|
"num_examples": 1130, |
|
"dataset_name": "ascend" |
|
} |
|
}, |
|
"download_checksums": { |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/train_metadata.csv": { |
|
"num_bytes": 1081181, |
|
"checksum": "4cbdf90fe9bf53640bfc285e2539b468a6e412daeb17c36a1b5da478cd9f5b29" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/test_metadata.csv": { |
|
"num_bytes": 127658, |
|
"checksum": "15689bc1c1a0bc29b250f63221576392b627da9cc1d80e51bb1a422118b9732c" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/raw/main/validation_metadata.csv": { |
|
"num_bytes": 118552, |
|
"checksum": "6e53e362991b23ffa49ed991c6062a51d8f286747f341e566c897c02bee72459" |
|
}, |
|
"https://huggingface.co/datasets/CAiRE/ASCEND/resolve/main/waves.tar.bz2": { |
|
"num_bytes": 929707032, |
|
"checksum": "b35cc295f1310535a8e250d534aee0adeb90bccbc027a442cdbef81146894529" |
|
} |
|
}, |
|
"download_size": 931034423, |
|
"post_processing_size": null, |
|
"dataset_size": 5365456, |
|
"size_in_bytes": 936399879 |
|
}, |
|
"main": { |
|
"description": "ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: training, validation, and test with a ratio of 8:1:1 while maintaining a balanced gender proportion on each set.\n", |
|
"citation": "@inproceedings{lovenia2021ascend,\n title = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},\n author = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Barezi, Elham J and others},\n booktitle = {Proceedings of the International Conference on Language Resources and Evaluation, {LREC} 2022, 20-25 June 2022, Lu Palais du Pharo, France},\n publisher = {European Language Resources Association},\n year = {2022},\n pages = {}\n}\n", |
|
"homepage": "https://huggingface.co/datasets/CAiRE/ASCEND", |
|
"license": "", |
|
"features": { |
|
"id": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"path": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"audio": { |
|
"sampling_rate": 16000, |
|
"_type": "Audio" |
|
}, |
|
"transcription": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"duration": { |
|
"dtype": "float32", |
|
"_type": "Value" |
|
}, |
|
"language": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
}, |
|
"original_speaker_id": { |
|
"dtype": "int64", |
|
"_type": "Value" |
|
}, |
|
"session_id": { |
|
"dtype": "int64", |
|
"_type": "Value" |
|
}, |
|
"topic": { |
|
"dtype": "string", |
|
"_type": "Value" |
|
} |
|
}, |
|
"task_templates": [ |
|
{ |
|
"task": "automatic-speech-recognition" |
|
} |
|
], |
|
"builder_name": "parquet", |
|
"dataset_name": "ascend", |
|
"config_name": "main", |
|
"version": { |
|
"version_str": "1.0.0", |
|
"major": 1, |
|
"minor": 0, |
|
"patch": 0 |
|
}, |
|
"splits": { |
|
"train": { |
|
"name": "train", |
|
"num_bytes": 1014573740.14, |
|
"num_examples": 9869, |
|
"dataset_name": null |
|
}, |
|
"test": { |
|
"name": "test", |
|
"num_bytes": 106171230.135, |
|
"num_examples": 1315, |
|
"dataset_name": null |
|
}, |
|
"validation": { |
|
"name": "validation", |
|
"num_bytes": 106772517.43, |
|
"num_examples": 1130, |
|
"dataset_name": null |
|
} |
|
}, |
|
"download_size": 1223536062, |
|
"dataset_size": 1227517487.7050002, |
|
"size_in_bytes": 2451053549.705 |
|
} |
|
} |
