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README.md ADDED
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+ ---
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+ license: cc-by-nc-4.0
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+ language:
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+ - zh
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+ language_bcp47:
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+ - zh-TW
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+ task_categories:
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+ - automatic-speech-recognition
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+ - text-to-speech
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+ - audio-classification
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+ pretty_name: TW Parliament
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+ tags:
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+ - Taiwan
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+ - Traditional Chinese
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+ - parliament
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+ - speech
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+ - ASR
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+ - TTS
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+ - Legislative Yuan
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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-*.parquet
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+ ---
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+
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+ # TW Parliament
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+
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+ TW Parliament is a filtered Traditional Chinese speech dataset derived from the
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+ `zh_tw` split of [disco-eth/WorldSpeech](https://huggingface.co/datasets/disco-eth/WorldSpeech).
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+ It contains audio clips and human transcripts from Taiwan Legislative Yuan IVOD
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+ parliamentary proceedings.
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+
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+ This release keeps only rows that passed the Taiwan-OmniData / FineWeb2-style
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+ text filtering pipeline. Audio is preserved from the upstream dataset and cast
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+ as a Hugging Face `Audio(sampling_rate=24000)` feature.
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+
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+ ## Dataset Summary
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+
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+ - Source dataset: `disco-eth/WorldSpeech`
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+ - Source config: `zh_tw`
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+ - Source split: `train`
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+ - Upstream source: Taiwan Legislative Yuan IVOD parliamentary proceedings
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+ - Audio: included, Opus/Ogg bytes, exposed as `datasets.Audio`
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+ - Text: human transcript
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+ - Rows after filtering: 308,521
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+ - Rows rejected by filtering: 24,762
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+ - Estimated text tokens after filtering: 11,464,559
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+ - License: CC BY-NC 4.0, following the upstream WorldSpeech dataset card
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+
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+ ## Fields
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+
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+ - `audio`: audio clip, Hugging Face `Audio(sampling_rate=24000)`
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+ - `text`: filtered human transcript
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+ - `human_transcript`: original human transcript from WorldSpeech
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+ - `asr_transcript`: upstream ASR transcript
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+ - `cer`: upstream character error rate signal
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+ - `snr`: upstream signal-to-noise estimate
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+ - `dnsmos_sig`, `dnsmos_bak`, `dnsmos_ovr`, `dnsmos_p808`: upstream DNSMOS quality signals
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+ - `duration`: clip duration in seconds
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+ - `source`: upstream source label
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+ - `source_url`: original IVOD media URL
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+ - `source_start_s`, `source_end_s`: segment offsets in the original media
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+ - `session_date`: parliamentary session date if available
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+ - `segment_id`: upstream segment id
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+ - `doc_id`: Taiwan-OmniData document id
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+ - `row_index`: row index in `disco-eth/WorldSpeech`, config `zh_tw`, split `train`
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+ - `estimated_tokens`: heuristic token estimate for the transcript
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+ - `quality_score`, `taiwan_relevance_score`, `zh_tw_naturalness_score`, `safety_score`, `pii_risk_score`: filtering/scoring signals
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+ - `filter_metadata`: compact provenance metadata for the filtering pass
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+
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+ ## Filtering
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+
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+ The source rows were processed through the Taiwan-OmniData filtering pipeline:
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+
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+ - text normalization and metadata preservation
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+ - Taiwan/Traditional Chinese locale tagging
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+ - FineWeb2-style repetition and boilerplate filters
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+ - safety and PII-risk scoring
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+ - train/eval separation metadata
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+
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+ Rejected rows are not included in this release. Top rejection reasons from the
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+ filtering run:
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+
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+ - `fineweb2_top_2gram_fraction`: 8,336
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+ - `fineweb2_top_4gram_fraction`: 5,966
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+ - `fineweb2_dup_5gram_fraction`: 5,467
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+ - `fineweb2_top_3gram_fraction`: 4,895
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+ - `fineweb2_dup_6gram_fraction`: 95
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+ - `fineweb2_max_avg_word_length`: 2
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+ - `fineweb2_dup_7gram_fraction`: 1
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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, Audio
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+
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+ ds = load_dataset("voidful/tw_parliament", split="train")
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+ ds = ds.cast_column("audio", Audio(sampling_rate=24000))
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+ sample = ds[0]
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+ print(sample["text"])
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+ print(sample["audio"]["sampling_rate"])
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+ ```
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+
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+ For metadata-only inspection without decoding audio:
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+
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+ ```python
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+ from datasets import load_dataset, Audio
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+
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+ ds = load_dataset("voidful/tw_parliament", split="train")
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+ ds = ds.cast_column("audio", Audio(sampling_rate=24000, decode=False))
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+ print(ds[0]["audio"].keys())
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+ ```
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+
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+ ## License And Attribution
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+
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+ This dataset follows the upstream WorldSpeech license declaration, CC BY-NC 4.0.
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+ Please also review the upstream WorldSpeech dataset card and the applicable
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+ terms for Taiwan Legislative Yuan IVOD content before commercial use.
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+
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+ If you use this dataset, please cite or link the upstream WorldSpeech dataset and
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+ this derived dataset.
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+
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+ ## Provenance
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+
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+ Generated by Taiwan-OmniData-R1 on 2026-06-06T14:28:07.476743+00:00. Audio was not re-encoded; the
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+ original WorldSpeech audio bytes were preserved and cast to the Hugging Face
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+ Audio feature.
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