Buckets:
| pretty_name: StreamAudio-2M | |
| license: cc-by-4.0 | |
| language: | |
| - en | |
| - zh | |
| task_categories: | |
| - audio-classification | |
| - automatic-speech-recognition | |
| - translation | |
| - audio-to-audio | |
| tags: | |
| - audio | |
| - streaming | |
| - audio-understanding | |
| - asr | |
| - speech-translation | |
| - voice-chat | |
| configs: | |
| - config_name: Stream_Audio_Understanding | |
| data_files: | |
| - split: train | |
| path: Stream_Audio_Understanding.jsonl | |
| - config_name: Real_time_ASR | |
| data_files: | |
| - split: train | |
| path: Real_time_ASR.jsonl | |
| - config_name: Stream_translation | |
| data_files: | |
| - split: train | |
| path: Stream_translation.jsonl | |
| - config_name: Voice_chatting | |
| data_files: | |
| - split: train | |
| path: Voice_chatting.jsonl | |
| - config_name: Proactive_respond | |
| data_files: | |
| - split: train | |
| path: Proactive_respond.jsonl | |
| - config_name: Environment_awared_audio_agent | |
| data_files: | |
| - split: train | |
| path: Environment_awared_audio_agent.jsonl | |
| # StreamAudio-2M | |
| Large-scale streaming-audio dataset for audio-LLM / audio-agent training. Each row is a | |
| **stream**: a sequence of audio turns sharing one unified schema. ~2.28M unique audio clips | |
| are organised into six task subsets. | |
| ## Subsets | |
| | Subset | Rows | Description | | |
| |---|---|---| | |
| | `Stream_Audio_Understanding` | 90,738 | Montages of audio-understanding clips (AudioSet / FMA): captions, choice & open QA | | |
| | `Real_time_ASR` | 28,109 | Streams of ASR clips (CommonVoice / GigaSpeech / LibriSpeech / VoxPopuli); `assistant` = transcript | | |
| | `Stream_translation` | 11,712 | Streams of EN→ZH speech-translation clips (CoVoST2); `assistant` = Chinese translation | | |
| | `Voice_chatting` | 196,064 | Multi-round spoken dialogues; each turn has spoken `user` + `assistant` | | |
| | `Proactive_respond` | 4,519 | Indoor/outdoor proactive-response streams (ElevenLabs / AudioX) | | |
| | `Environment_awared_audio_agent` | 50,035 | Same-scene audio montages (90–180 s) | | |
| ## Schema | |
| Top level: | |
| `id`, `stream_scene_type`, `stream_audio_category`, `num_turns`, `total_duration_s`, `turns` | |
| `stream_scene_type` / `stream_audio_category` hold the common value when all turns agree, else `"mixed"`. | |
| Each item of `turns`: | |
| `user`, `assistant`, `emotion`, `keywords`, `scene_type`, `audio_category`, `topic_type`, | |
| `audio_path`, `source`, `audio_stats` | |
| `audio_stats` = `{duration_s, sample_rate, channels, mean, std, abs_mean, rms_db, peak_db, crest_factor, dynamic_range_db, zero_crossing_rate}`. | |
| `scene_type` ∈ {Driving, Traffic, Home Smart, Cooking, Fitness, Travel, Office, others}. | |
| ## Audio | |
| Audio is shipped as uncompressed tar shards under `audio_tars/`. Download all shards and | |
| extract them into the dataset root to recreate the `audio/` tree; the `audio_path` field in | |
| every row is the relative path inside that tree, e.g. `audio/asr/0012/asr_0012345.wav`. | |
| ```bash | |
| cat audio_tars/*.tar | tar -xf - # or extract each shard individually | |
| ``` | |
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