README.md

metadata

license: unknown
language:
  - zh
pretty_name: CDC Press Conferences
extra_gated_prompt: Access requires agreeing to non-commercial research use only.
extra_gated_fields:
  Name: text
  Affiliation: text
  Intended use: text
  I agree to use this dataset only for non-commercial research purposes: checkbox
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*.parquet
dataset_info:
  features:
    - name: id
      dtype: string
    - name: audio
      dtype: audio
    - name: text
      dtype: string

CDC Press Conferences

Utterance-level clips from Taiwan CDC (疾病管制署) press-conference YouTube livestreams (largely COVID-19 era, 2020-2023). This corpus is Mandarin, not Taiwanese -- it is one of the few non-Taiwanese-language corpora kept in this project's source bucket, included here for reference/comparison purposes only.

Dataset Description

• Use case: ASR (Automatic Speech Recognition)
• Language: Mandarin Chinese (not Taiwanese)
• Source: Taiwan CDC press-conference YouTube livestreams, 728 episodes across 5 years (2020-2023). Utterance-level audio/text pairs were produced by the team's own prior pipeline (cdc_press/utils/cdc_preprocess.ipynb in the source bucket): parse each episode's auto-generated .srt, merge consecutive caption entries separated by <100ms gaps (a heuristic fix for captions that get cut mid-word -- see caveat below), then a second merge pass targeting 3.5-22.5 second spans, then crop the corresponding 16kHz WAV per final caption group. This repo reshapes the team's already-built cdc_ds.zip (a datasets.DatasetDict.save_to_disk export covering all 5 source years) into HF-viewer-friendly Parquet shards; no re-processing of the original video/subtitles was done here.
• Known caveat -- residual mid-word/mid-sentence cuts: even after the 100ms-gap merge heuristic, some captions may still be cut mid-word or mid-sentence, since the merge is a heuristic, not a real transcript re-alignment. Concrete example from a source .srt: one caption ends "...那今天我們指揮", the next begins "中心出席的...", splitting the compound word 指揮中心 ("Central Epidemic Command Center") right through the middle with a 0ms gap between them. Treat text as generally reliable but not perfectly clean.
• Not included: whole-episode raw audio (16k/48k WAV) and raw .srt subtitle files also exist in the source bucket but are not part of this repo -- only the pre-cropped utterance-level version from cdc_ds.zip is included here.
• Audio format: 16kHz, mono, 16-bit PCM WAV
• Split: this dataset is train only (the 5 source years are not modeling splits -- they're just how the raw data happened to be organized during scraping; each row's source episode/date is embedded in id -- see Dataset Structure below -- so filter on that if you need a per-year subset).

Dataset Structure

• id: {episode_id}_{index:04}, e.g. 2020-10-14-14_00_7ibcEttw4-g_0001 -- the part before the trailing _NNNN utterance index is the source YouTube episode identifier (date + title fragment + video ID). There is no separate episode/origin column since it's always exactly this prefix of id.
• audio: audio clip (16kHz, mono, 16-bit PCM WAV).
• text: Mandarin transcript for the clip (originally zh in the source dataset; same language as the audio, per this project's field-naming convention).

Statistics

split	lang_name	hours	n_utts	n_chars_in_utts	secs/utt	chars/sec	n_sents	n_chars_in_sents
train	Mandarin	404.0792	238003	7176515	6.11	4.93	0	0
Total	-	404.0792	238003	7176515	6.11	4.93	0	0