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  1. README.md +85 -31
  2. info.csv +62 -0
README.md CHANGED
@@ -1,31 +1,85 @@
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- ---
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- dataset_info:
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- features:
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- - name: audio
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- dtype: audio
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- - name: transcription
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- dtype: string
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- - name: Speaker ID
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- dtype: string
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- splits:
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- - name: train
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- num_bytes: 58513440.578
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- num_examples: 2858
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- - name: validation
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- num_bytes: 56714850.712
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- num_examples: 2912
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- - name: test
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- num_bytes: 70051704.606
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- num_examples: 3437
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- download_size: 183555285
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- dataset_size: 185279995.896
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- configs:
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- - config_name: default
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- data_files:
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- - split: train
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- path: data/train-*
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- - split: validation
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- path: data/validation-*
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- - split: test
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- path: data/test-*
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-4.0
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+ task_categories:
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+ - automatic-speech-recognition
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+ - text-to-speech
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+ language:
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+ - vi
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+ pretty_name: VietMed labeled set
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+ size_categories:
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+ - 1K<n<10K
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+ dataset_info:
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+ features:
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+ - name: audio
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+ dtype: audio
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+ - name: transcription
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+ dtype: string
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+ - name: Speaker ID
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+ dtype: string
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+ splits:
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+ - name: train
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+ num_bytes: 58513440.578
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+ num_examples: 2858
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+ - name: validation
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+ num_bytes: 56714850.712
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+ num_examples: 2912
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+ - name: test
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+ num_bytes: 70051704.606
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+ num_examples: 3437
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+ download_size: 183555285
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+ dataset_size: 185279995.896
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: validation
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+ path: data/validation-*
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+ - split: test
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+ path: data/test-*
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+ ---
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+
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+ # unofficial mirror of VietMed (Vietnamese speech data in medical domain) labeled set
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+
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+ official announcement: https://arxiv.org/abs/2404.05659
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+
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+ official download: https://huggingface.co/datasets/leduckhai/VietMed
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+
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+ this repo contains the labeled set: 9.2k samples
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+
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+ i also gather the metadata: see [info.csv](info.csv)
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+
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+ my extraction code: https://github.com/phineas-pta/fine-tune-whisper-vi/blob/main/misc/vietmed-labeled.py
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+
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+ need to do: check misspelling, restore foreign words phonetised to vietnamese
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+
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+ usage with HuggingFace:
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+ ```python
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+ # pip install -q "datasets[audio]"
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+ from datasets import load_dataset
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+ from huggingface_hub import hf_hub_download
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+ from pandas import read_csv
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+
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+ repo_id = "doof-ferb/VietMed_labeled"
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+ dataset = load_dataset(repo_id, split="train", streaming=True)
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+ info_file = hf_hub_download(repo_id=repo_id, filename="info.csv", repo_type="dataset")
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+ info_dict = read_csv(info_file, index_col=0).to_dict("index")
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+
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+ def merge_info(batch):
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+ meta = info_dict.get(batch["Speaker ID"], "")
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+ if meta != "":
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+ batch["Recording Condition"] = meta["Recording Condition"]
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+ batch["ICD-10 Code"] = meta["ICD-10 Code"]
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+ batch["Role"] = meta["Role"]
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+ batch["Gender"] = meta["Gender"]
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+ batch["Accent"] = meta["Accent"]
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+ else:
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+ batch["Recording Condition"] = ""
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+ batch["ICD-10 Code"] = ""
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+ batch["Role"] = ""
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+ batch["Gender"] = ""
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+ batch["Accent"] = ""
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+ return batch
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+ dataset = dataset.map(merge_info)
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+ ```
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+
info.csv ADDED
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+ "Speaker ID","split","Recording Condition","ICD-10 Code","Role","Gender","Accent"
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+ "VietMed_001_a","Dev","Telephone","J00-J99","Doctor","Male","North"
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+ "VietMed_001_b","Dev","Telephone","J00-J99","Doctor","Male","North"
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+ "VietMed_002","Test","Lectures","N00-N99","Lecturer","Female","South Central Coast"
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+ "VietMed_003_a","Dev","Telephone","A00-B99","Host","Male","South East"
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+ "VietMed_003_b","Dev","Telephone","A00-B99","Doctor","Male","South West"
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+ "VietMed_004","Test","Consultation","M00-M99","Doctor","Male","South Central Coast"
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+ "VietMed_005","Dev","Consultation","I00-I99","Doctor","Male","Central Highland"
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+ "VietMed_006_a","Dev","Consultation","R00-R99","Doctor","Female","South East"
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+ "VietMed_006_b","Dev","Consultation","R00-R99","Host","Female","South East"
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+ "VietMed_007_a","Train","Consultation","I00-I99","Doctor","Male","Central Highland"
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+ "VietMed_007_b","Train","Consultation","I00-I99","Doctor","Male","South East"
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+ "VietMed_008_a","Train","Telephone","G00-G99","Host","Male","South East"
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+ "VietMed_008_b","Train","Telephone","G00-G99","Doctor","Male","South East"
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+ "VietMed_008_c","Train","Telephone","G00-G99","Doctor","Male","South East"
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+ "VietMed_009_a","Train","Consultation","E00-E89","Host","Male","South East"
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+ "VietMed_009_b","Train","Consultation","E00-E89","Doctor","Female","South East"
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+ "VietMed_009_c","Train","Consultation","E00-E89","Doctor","Male","South East"
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+ "VietMed_010_a","Train","Consultation","C00-D49","Host","Female","North"
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+ "VietMed_010_b","Train","Consultation","C00-D49","Doctor","Female","North"
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+ "VietMed_011_a","Train","Telephone","M00-M99","Host","Female","North"
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+ "VietMed_011_b","Train","Telephone","M00-M99","Doctor","Male","North"
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+ "VietMed_011_c","Train","Telephone","M00-M99","Patient","Male","North"
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+ "VietMed_012_a","Dev","Telephone","Z00-Z99","Host","Male","South East"
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+ "VietMed_012_b","Dev","Telephone","Z00-Z99","Doctor","Male","North"
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+ "VietMed_012_c","Dev","Telephone","Z00-Z99","Patient","Male","South West"
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+ "VietMed_012_d","Dev","Telephone","Z00-Z99","Patient","Female","North"
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+ "VietMed_013_a","Dev","Telephone","I00-I99","Host","Male","South East"
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+ "VietMed_013_b","Dev","Telephone","I00-I99","Doctor","Female","North"
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+ "VietMed_013_c","Dev","Telephone","I00-I99","Patient","Male","South East"
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+ "VietMed_013_d","Dev","Telephone","I00-I99","Patient","Female","North"
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+ "VietMed_014_a","Test","Telephone","K00-K95","Host","Female","North"
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+ "VietMed_014_b","Test","Telephone","K00-K95","Doctor","Male","North"
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+ "VietMed_015_a","Test","Telephone","O00-O9A","Host","Female","North"
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+ "VietMed_015_b","Test","Telephone","O00-O9A","Doctor","Female","North"
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+ "VietMed_015_c","Test","Telephone","O00-O9A","Patient","Female","North"
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+ "VietMed_017_a","Test","Talkshow","U00-U85","Doctor","Female","South West"
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+ "VietMed_017_b","Test","Talkshow","U00-U85","Doctor","Male","North"
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+ "VietMed_018_a","Test","Talkshow","K00-K95","Host","Female","South West"
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+ "VietMed_018_b","Test","Talkshow","K00-K95","Doctor","Male","South West"
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+ "VietMed_018_c","Test","Talkshow","K00-K95","Doctor","Female","South West"
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+ "VietMed_018_d","Test","Talkshow","K00-K95","Patient","Female","South West"
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+ "VietMed_018_e","Test","Talkshow","K00-K95","Patient","Male","South West"
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+ "VietMed_018_f","Test","Talkshow","K00-K95","Doctor","Male","South West"
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+ "VietMed_019_a","Test","Talkshow","L00-L99","Host","Female","South West"
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+ "VietMed_019_b","Test","Talkshow","L00-L99","Doctor","Female","South West"
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+ "VietMed_019_c","Dev","Talkshow","L00-L99","Doctor","Male","South West"
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+ "VietMed_019_d","Dev","Talkshow","L00-L99","Patient","Female","South West"
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+ "VietMed_020_a","Dev","Telephone","Z00-Z99","Host","Female","South West"
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+ "VietMed_020_b","Dev","Telephone","Z00-Z99","Doctor","Female","South West"
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+ "VietMed_021","Dev","Book","D50-D89","Narrator","Male","North"
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+ "VietMed_022","Dev","Book","F01-F99","Narrator","Male","South East"
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+ "VietMed_023","Test","Podcast","P00-P96","Podcaster","Female","South West"
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+ "VietMed_024","Test","Podcast","O00_O99","Podcaster","Female","South East"
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+ "VietMed_025_a","Test","Diagnosis","H60-H95","Host","Female","South West"
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+ "VietMed_025_b","Test","Diagnosis","H60-H95","Doctor","Male","South East"
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+ "VietMed_026","Test","Lectures","A00-B99","Lecturer","Male","North Central Coast"
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+ "VietMed_027_a","Test","News","S00-T88","Host","Female","South West"
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+ "VietMed_027_b","Test","News","S00-T88","Broadcaster","Male","South East"
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+ "VietMed_028_a","Test","News","V00-Y99","Host","Female","South East"
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+ "VietMed_028_b","Test","News","V00-Y99","Broadcaster","Male","South East"
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+ "VietMed_029","Test","News","V00-Y99","Broadcaster","Female","South East"