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Datasets:
laubonghaudoi
/
legco-speech

Tasks:
Automatic Speech Recognition
Audio-to-Audio
Audio Classification
Modalities:
Audio
Text
Formats:
parquet
Languages:
Yue Chinese
Size:
1M - 10M
Tags:
cantonese
speech
hong-kong
legco
legislative-council
Libraries:
Datasets
Dask
Polars
License:
Dataset card Data Studio Files
xet
 Community
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laubonghaudoi commited on
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Super squash: clean up history after removing duplicate folders

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  2. README.md +112 -0
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+ ---
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+ language:
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+ - yue
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+ license: cc0-1.0
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+ task_categories:
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+ - automatic-speech-recognition
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+ - audio-to-audio
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+ - audio-classification
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+ - text-generation
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+ tags:
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+ - cantonese
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+ - speech
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+ - hong-kong
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+ - legco
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+ - legislative-council
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+ size_categories:
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+ - 1M<n<10M
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+ configs:
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+ - config_name: raw
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+ data_files:
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+ - split: train
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+ path: raw/train-*.parquet
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+ - config_name: segmented
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+ data_files:
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+ - split: train
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+ path: segmented/train-*.parquet
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+ default: true
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+ ---
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+
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+ # 香港立法會會議語音數據集
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+
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+ ## Dataset Description
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+
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+ - **License:** [CC0 1.0 Universal](https://creativecommons.org/publicdomain/zero/1.0/)
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+ - **Language:** Cantonese
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+ - **Audio Format:** 16kHz OPUS
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+ - **Total Duration (Raw):** 22,195.55 hours
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+ - **Total Duration (Segmented):** 20,71.21 hours
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+ - **Average Meeting Duration:** 5692.79 seconds (1.58 hours)
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+ - **Average Segment Duration:** 7.71 seconds
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+ - **Median Meeting Duration:** 6153.00 seconds (1.71 hours)
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+ - **Median Segment Duration:** 8.17 seconds
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+ - **Total number of characters:** 377,722,545
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+ - **Average characters per segment:** 39.52
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+ - **Median characters per segment:** 40
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+
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+ 本數據集係由[香港立法會會議](https://www.youtube.com/legcogovhk)製成嘅大規模語音數據集。原始錄音總時長 22,196 個鐘，切分語音後總時長 20,471 個鐘。數據集分兩個子集，`raw`同`segmented`，分別為原始錄音同VAD識別切分後嘅語音。
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+
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+ ## 數據集製作流程
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+
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+ 1. 先去[香港特別行政區立法會 YouTube](https://www.youtube.com/legcogovhk)下載所有會議紀錄並轉為 16kHz 採樣率嘅 OPUS音頻
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+ 1. 用 [fsmn-vad](https://huggingface.co/funasr/fsmn-vad) 切分所有語音，並用 [Qwen3-ASR-1.7B](https://huggingface.co/Qwen/Qwen3-ASR-1.7B) 轉寫成粵文 srt 字幕
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+ 1. 轉寫後用正則表達式修正字幕中常見轉寫錯誤
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+ 1. 將數據集分成 `raw`、 `segmented` 兩個子集傳到HF
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+
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+ | 子集 subset | `raw` |`segment`|
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+ |---|---|---|
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+ | 總行數 Row number | 14,036 | 9,557,109 |
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+ | 總時長 Total duration | 22,195.55 hr (79,903,980.00 s) | 20471.21 hr (73,696,365.27 s)|
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+ | 平均時長 Average duration | 1.58 hr (5692.79 s) | 7.71 s|
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+ | 中位時長 Median duration | 1.71 hr (6153.00 s) | 8.17 s |
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+ | 平均字數 Average subtitle characters | 26,910.98 | 39.52|
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+ | 中位字數 Median subtitle characters | 29,219.00 |40.00|
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+
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+ ## 數據列
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+
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+ ### `segment`
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+
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+ | 名稱 | 類型 | 描述 |
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+ |---|---|---|
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+ | `video_id` | string | 源 YouTube 影片 ID |
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+ | `segment_id` | int | 字幕 SRT 文件中嘅片段 ID |
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+ | `audio` | Audio | 音頻 |
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+ | `text` | string | 粵文轉寫文本 |
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+ | `start_time` | float | 該片段開始時間點 |
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+ | `end_time` | float | 該片段結束時間點 |
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+ | `duration` | float | 該片段時長 |
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+
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+ ### `raw`
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+
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+ | 名稱 | 類型 | 描述 |
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+ |---|---|---|
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+ | `id` | string | YouTube 影片 ID|
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+ | `audio` | Audio | 會議音頻 |
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+ | `transcription` | string | 粵文轉寫字幕 SRT |
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+ | `title` | string | YouTube 影片標題 |
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+ | `description` | string | YouTube 影片描述 |
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+ | `publish_date` | string | YouTube 影片發佈日期 |
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+ | `duration` | string | 總時長（HH:MM:SS 格式）|
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+ | `duration_seconds` | int | 總時長（秒數） |
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+
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+ 原始 SRT文件都放喺`raw/transcriptions/`
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+
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+ ## Usage
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+
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+ ```python
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+ from datasets import load_dataset
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+
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+ # Sentence-level segments (default, recommended for training)
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+ ds = load_dataset("<user>/legco-speech", "segmented", split="train", streaming=True)
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+ sample = next(iter(ds))
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+ print(sample["text"])
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+ # 香港嘅社會同城市結構已經跨越咗壯年嘅階段。
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+ print(sample["start_time"], sample["end_time"], sample["duration"])
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+ # 0.42 9.08 8.66
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+
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+ # Full meeting recordings
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+ ds_raw = load_dataset("<user>/legco-speech", "raw", split="train", streaming=True)
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+ sample = next(iter(ds_raw))
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+ print(sample["title"])
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+ # 房屋事務委員會特別會議 (2026/02/23)
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+ ```
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