757 GB
48 files
Updated 11 days ago
README.md

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.

cat audio_tars/*.tar | tar -xf -    # or extract each shard individually
Total size
757 GB
Files
48
Last updated
Sep 8
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