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+ # Dataset Card
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+
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+ ---
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+ license: cc-by-4.0
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+ language:
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+ - en
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+ tags:
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+ - streaming-cot
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+ - chain-of-thought
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+ - sft
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+ - audio
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+ size_categories:
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+ - 1K<n<10K
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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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+ - split: eval
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+ path: data/eval.parquet
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+ - config_name: high_quality
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+ data_files:
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+ - split: train
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+ path: data/high_quality_train.parquet
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+ - split: eval
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+ path: data/high_quality_eval.parquet
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+ ---
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+
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+ # LifeAudioMultiTurnStreamingCoT
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+
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+ **Version:** vFinal
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+
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+ A multi-turn audio dataset with streaming chain-of-thought reasoning for SFT. 13349 active training rows with audio references.
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+
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+ ## Schema
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+
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+ Top-level fields: `id, split, modality, turn_type, dialogue, audio, input, streaming, target, taxonomy, quality, source, metadata`
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+
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+ - dialogue (list of turns with role/text)
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+ - audio (path, reference, duration_sec, loadability)
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+ - input (instruction, length_bucket)
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+ - target (reasoning, answer, response)
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+ - streaming (checkpoints with streaming_reasoning)
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+ - taxonomy (category, subcategory, difficulty, intent_type)
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+
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+ ### Target Format
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+ ```json
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+ {
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+ "reasoning": "Natural language reasoning about the task/input...",
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+ "answer": "The actual task output...",
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+ "response": "Reasoning: ...\n\nAnswer: ..."
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+ }
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+ ```
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+
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+ Use `target.response` for SFT training. It includes both reasoning and final answer.
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+
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+ ## Quality
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+
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+ | Metric | Value |
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+ |--------|-------|
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+ | Active rows | 13,349 |
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+ | Train | 10,679 |
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+ | Eval | 2,670 |
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+ | High quality | 13,349 |
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+ | SFT-ready | 100.0% |
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+ | Target grounded | 100.0% |
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+
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+ ## High-Quality Configuration
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+
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+ The `high_quality` config contains a filtered subset of default rows where `quality.sft_ready = true` and `quality.is_high_quality = true`. It is not additional unique data.
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+
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+ ## Limitations
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+
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+ - Audio is external reference only (HF URLs). No bundled audio bytes.
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+ -
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+ - Natural-language reasoning is template-generated, not LLM-written.
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+ - Row counts reflect quality-filtered active splits suitable for direct SFT usage.
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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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+ # Load default config
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+ ds = load_dataset("skyzhou06/LifeAudioMultiTurnStreamingCoT")
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+
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+ # Load high-quality subset
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+ ds_hq = load_dataset("skyzhou06/LifeAudioMultiTurnStreamingCoT", "high_quality")
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+ ```