"This is Houston. Say again, please". The Behavox system for the\n Apollo-11 Fearless Steps Challenge (phase II)
Bibliographic record
Abstract
We describe the speech activity detection (SAD), speaker diarization (SD),\nand automatic speech recognition (ASR) experiments conducted by the Behavox\nteam for the Interspeech 2020 Fearless Steps Challenge (FSC-2). A relatively\nsmall amount of labeled data, a large variety of speakers and channel\ndistortions, specific lexicon and speaking style resulted in high error rates\non the systems which involved this data. In addition to approximately 36 hours\nof annotated NASA mission recordings, the organizers provided a much larger but\nunlabeled 19k hour Apollo-11 corpus that we also explore for semi-supervised\ntraining of ASR acoustic and language models, observing more than 17% relative\nword error rate improvement compared to training on the FSC-2 data only. We\nalso compare several SAD and SD systems to approach the most difficult tracks\nof the challenge (track 1 for diarization and ASR), where long 30-minute audio\nrecordings are provided for evaluation without segmentation or speaker\ninformation. For all systems, we report substantial performance improvements\ncompared to the FSC-2 baseline systems, and achieved a first-place ranking for\nSD and ASR and fourth-place for SAD in the challenge.\n
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".