Datasets:

davanstrien
/

apollo-11-diarized

license: cc0-1.0
configs:
  - config_name: segments
    data_files:
      - split: train
        path: segments/train-*
  - config_name: tapes
    data_files:
      - split: train
        path: tapes/train-*
language:
  - en
tags:
  - uv-script
  - generated
  - audio
  - transcription
  - diarization
  - apollo-11
pretty_name: Apollo 11 Mission Audio — Diarized Transcripts

Apollo 11 Mission Audio — Diarized Transcripts

Machine-generated transcripts with speaker diarization and timestamps for 103 tapes (175 hours) of Apollo 11 mission audio from the Internet Archive's Apollo11Audio collection (NASA recordings, public domain).

Generated in a single Hugging Face Job with OpenMOSS-Team/MOSS-Transcribe-Diarize (0.9B, Apache 2.0) — joint transcription + speaker attribution + timestamps in one generation pass per clip.

Configs

segments (45355 rows): tape, part, start, end, speaker, text. Timestamps are seconds from tape start.
tapes (103 rows): per-tape duration, transcript coverage, parts, speaker sets.

Known limitations

ASR quality: this is scratchy 1969 radio audio; expect mishearings (e.g. "Apollo eleven" sometimes transcribed as "Follow eleven").
Degenerate output filtered: on long non-speech stretches (static, carrier hiss, Quindar tones — and some tapes in the source collection are entirely empty transfers) the model hallucination-loops. Segments that are empty, dots-only, malformed, internally repetitive (zlib compression-ratio > 2.4, the Whisper heuristic), or identical to >2 preceding segments were dropped; compare num_segments vs num_segments_raw in the tapes config. Raw unfiltered output is preserved in the generation bucket.
Speaker labels (S01, S02, ...) are anonymous and consistent only within a part: tapes longer than ~55 min are processed in clips and the labels reset between them (the part column). Labels are not linked across tapes either.
Coverage: the model occasionally stops early; the pipeline continues from the last timestamp, but per-tape coverage_s in the tapes config shows any remaining gaps (170/175 h covered overall).

Reproduction

Generated with the moss-transcribe-diarize-server.py recipe from uv-scripts. The recipe serves the model with sglang-omni inside the job and transcribes files concurrently (37.8x realtime aggregate on a100-large). Run it yourself:

hf jobs run --detach --flavor a100-large -s HF_TOKEN --timeout 8h \
    -v hf://buckets/user/audio-files:/input:ro \
    -v hf://buckets/user/transcripts:/output \
    lmsysorg/sglang:nightly-dev-cu13-20260709-074bb928 -- \
    bash -c "pip install -q uv; git clone --depth 1 https://github.com/sgl-project/sglang-omni.git && cd sglang-omni && uv venv .venv -p 3.12 && . .venv/bin/activate && uv pip install . && (sgl-omni serve --model-path OpenMOSS-Team/MOSS-Transcribe-Diarize --host 0.0.0.0 --port 8000 --max-running-requests 16 --mem-fraction-static 0.80 &) && uv run https://huggingface.co/datasets/uv-scripts/transcription/raw/main/moss-transcribe-diarize-server.py /input /output --concurrency 6 --emit-txt"