Datasets:

nur-dev
/

stress17k-counterfactual-pairs

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
seed: int64
checkpoint: string
adapter: struct<name: string, n_rows: int64, accuracy: double, accuracy_ci_lo: double, accuracy_ci_hi: double (... 478 chars omitted)
  child 0, name: string
  child 1, n_rows: int64
  child 2, accuracy: double
  child 3, accuracy_ci_lo: double
  child 4, accuracy_ci_hi: double
  child 5, signed_margin: double
  child 6, signed_margin_ci_lo: double
  child 7, signed_margin_ci_hi: double
  child 8, accuracy_neutral: double
  child 9, accuracy_neutral_ci_lo: double
  child 10, accuracy_neutral_ci_hi: double
  child 11, accuracy_explicit: double
  child 12, accuracy_explicit_ci_lo: double
  child 13, accuracy_explicit_ci_hi: double
  child 14, signed_margin_neutral: double
  child 15, signed_margin_neutral_ci_lo: double
  child 16, signed_margin_neutral_ci_hi: double
  child 17, signed_margin_explicit: double
  child 18, signed_margin_explicit_ci_lo: double
  child 19, signed_margin_explicit_ci_hi: double
K_T: struct<name: string, n_rows: int64, accuracy: double, accuracy_ci_lo: double, accuracy_ci_hi: double (... 478 chars omitted)
  child 0, name: string
  child 1, n_rows: int64
  child 2, accuracy: double
  child 3, accuracy_ci_lo: double
  child 4, accuracy_ci_hi: double
  child 5, signed_margin: double
  child 6, signed_margin_ci_lo: double
  child 7, signed_margin_ci_hi: double
  child 8, accuracy_neutral: double
  child 9, accuracy_neutral_ci_lo: double
  child 10, accuracy_neutral_ci_hi: double
  child 11, accuracy_explicit: double
  child 
...
gin_explicit_ci_lo: double
  child 19, signed_margin_explicit_ci_hi: double
oracle_reconfirm: struct<accuracy: double, accuracy_ci_lo: double, accuracy_ci_hi: double, signed_margin: double, sign (... 81 chars omitted)
  child 0, accuracy: double
  child 1, accuracy_ci_lo: double
  child 2, accuracy_ci_hi: double
  child 3, signed_margin: double
  child 4, signed_margin_ci_lo: double
  child 5, signed_margin_ci_hi: double
  child 6, n_correct: int64
  child 7, n: int64
probe_k: struct<linear: struct<fit_best_eval_acc: double, fit_final_eval_acc: double, eval_acc_full: double,  (... 322 chars omitted)
  child 0, linear: struct<fit_best_eval_acc: double, fit_final_eval_acc: double, eval_acc_full: double, eval_acc_within (... 99 chars omitted)
      child 0, fit_best_eval_acc: double
      child 1, fit_final_eval_acc: double
      child 2, eval_acc_full: double
      child 3, eval_acc_within: double
      child 4, sp_acc_full: double
      child 5, sp_acc_within: double
      child 6, robust_fp16: double
      child 7, robust_sigma_01: double
  child 1, mlp2: struct<fit_best_eval_acc: double, fit_final_eval_acc: double, eval_acc_full: double, eval_acc_within (... 99 chars omitted)
      child 0, fit_best_eval_acc: double
      child 1, fit_final_eval_acc: double
      child 2, eval_acc_full: double
      child 3, eval_acc_within: double
      child 4, sp_acc_full: double
      child 5, sp_acc_within: double
      child 6, robust_fp16: double
      child 7, robust_sigma_01: double
to
{'adapter': List({'item': Value('int64'), 'transcription_id': Value('string'), 'is_explicit': Value('bool'), 'p_idx': Value('int64'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')}), 'K_T': List({'item': Value('int64'), 'transcription_id': Value('string'), 'is_explicit': Value('bool'), 'p_idx': Value('int64'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')}), 'cascade_T': List({'item': Value('int64'), 'transcription_id': Value('string'), 'is_explicit': Value('bool'), 'p_idx': Value('int64'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')}), 'oracle_reconfirm': List({'item': Value('int64'), 'transcription_id': Value('string'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')})}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                         ^^^^^^^^^
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                         ^^^^^^^^^^^^^^^^^^^^^
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2690, in __iter__
                  for key, example in ex_iterable:
                                      ^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2227, in __iter__
                  for key, pa_table in self._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2251, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 494, in _iter_arrow
                  for key, pa_table in iterator:
                                       ^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 384, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                                       ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 295, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 128, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2321, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2249, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              seed: int64
              checkpoint: string
              adapter: struct<name: string, n_rows: int64, accuracy: double, accuracy_ci_lo: double, accuracy_ci_hi: double (... 478 chars omitted)
                child 0, name: string
                child 1, n_rows: int64
                child 2, accuracy: double
                child 3, accuracy_ci_lo: double
                child 4, accuracy_ci_hi: double
                child 5, signed_margin: double
                child 6, signed_margin_ci_lo: double
                child 7, signed_margin_ci_hi: double
                child 8, accuracy_neutral: double
                child 9, accuracy_neutral_ci_lo: double
                child 10, accuracy_neutral_ci_hi: double
                child 11, accuracy_explicit: double
                child 12, accuracy_explicit_ci_lo: double
                child 13, accuracy_explicit_ci_hi: double
                child 14, signed_margin_neutral: double
                child 15, signed_margin_neutral_ci_lo: double
                child 16, signed_margin_neutral_ci_hi: double
                child 17, signed_margin_explicit: double
                child 18, signed_margin_explicit_ci_lo: double
                child 19, signed_margin_explicit_ci_hi: double
              K_T: struct<name: string, n_rows: int64, accuracy: double, accuracy_ci_lo: double, accuracy_ci_hi: double (... 478 chars omitted)
                child 0, name: string
                child 1, n_rows: int64
                child 2, accuracy: double
                child 3, accuracy_ci_lo: double
                child 4, accuracy_ci_hi: double
                child 5, signed_margin: double
                child 6, signed_margin_ci_lo: double
                child 7, signed_margin_ci_hi: double
                child 8, accuracy_neutral: double
                child 9, accuracy_neutral_ci_lo: double
                child 10, accuracy_neutral_ci_hi: double
                child 11, accuracy_explicit: double
                child 
              ...
              gin_explicit_ci_lo: double
                child 19, signed_margin_explicit_ci_hi: double
              oracle_reconfirm: struct<accuracy: double, accuracy_ci_lo: double, accuracy_ci_hi: double, signed_margin: double, sign (... 81 chars omitted)
                child 0, accuracy: double
                child 1, accuracy_ci_lo: double
                child 2, accuracy_ci_hi: double
                child 3, signed_margin: double
                child 4, signed_margin_ci_lo: double
                child 5, signed_margin_ci_hi: double
                child 6, n_correct: int64
                child 7, n: int64
              probe_k: struct<linear: struct<fit_best_eval_acc: double, fit_final_eval_acc: double, eval_acc_full: double,  (... 322 chars omitted)
                child 0, linear: struct<fit_best_eval_acc: double, fit_final_eval_acc: double, eval_acc_full: double, eval_acc_within (... 99 chars omitted)
                    child 0, fit_best_eval_acc: double
                    child 1, fit_final_eval_acc: double
                    child 2, eval_acc_full: double
                    child 3, eval_acc_within: double
                    child 4, sp_acc_full: double
                    child 5, sp_acc_within: double
                    child 6, robust_fp16: double
                    child 7, robust_sigma_01: double
                child 1, mlp2: struct<fit_best_eval_acc: double, fit_final_eval_acc: double, eval_acc_full: double, eval_acc_within (... 99 chars omitted)
                    child 0, fit_best_eval_acc: double
                    child 1, fit_final_eval_acc: double
                    child 2, eval_acc_full: double
                    child 3, eval_acc_within: double
                    child 4, sp_acc_full: double
                    child 5, sp_acc_within: double
                    child 6, robust_fp16: double
                    child 7, robust_sigma_01: double
              to
              {'adapter': List({'item': Value('int64'), 'transcription_id': Value('string'), 'is_explicit': Value('bool'), 'p_idx': Value('int64'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')}), 'K_T': List({'item': Value('int64'), 'transcription_id': Value('string'), 'is_explicit': Value('bool'), 'p_idx': Value('int64'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')}), 'cascade_T': List({'item': Value('int64'), 'transcription_id': Value('string'), 'is_explicit': Value('bool'), 'p_idx': Value('int64'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')}), 'oracle_reconfirm': List({'item': Value('int64'), 'transcription_id': Value('string'), 'label': Value('int64'), 'pred': Value('int64'), 'correct': Value('int64'), 'score_A': Value('float64'), 'score_B': Value('float64'), 'signed_margin': Value('float64')})}
              because column names don't match

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Beyond Transcript Alignment — derived data

Derived data + per-seed evaluation results for the Beyond Transcript Alignment research project (frozen-frozen speech-to-LLM adapters under counterfactual training on the StressTest benchmark).

Code: https://github.com/Nurgali-Kadyrbek/frozen-speech-llm-stress

cf_pairs/cf_pairs_train.jsonl — 3666 same-transcript counterfactual pairs from Stress-17K-raw probe-train (transcript IDs + stress indices; no raw audio).
cf_pairs/cf_pairs_artifact.jsonl — 6846 artifact-matched negatives (same Φ, different surface features).
cf_pairs/cf_pairs_train_shuffled.jsonl — Stage 4 Control B: 3666 pairs with audio decorrelated from (transcript, Φ) labels.
proj_P/proj_P.pt — Stage 4 Control A: 4096→1024 lstsq-fit linear projection (train MSE 0.090, train cos-sim 0.999) used to construct the text-only adapter baseline.
desc_only_baseline.json — pinned cross-domain absolute Probe-K floor (0.361).
eval_results/stage{2,3p8,4,6,6_r4,7}_eval/ — per-seed summary.json
- rows.json files for every cohort and pilot in the project.

Audio access

No raw audio is included. Audio for the four datasets used in this project is accessed via HuggingFace Hub:

slprl/StressPresso (CC-BY-NC-4.0) — n=202 test items
slprl/Stress-17K-raw (CC-BY-NC-4.0) — cf-pairs derive from this
ylacombe/expresso (CC-BY-NC-4.0) — artifact-matched negatives
openslr/librispeech_asr config clean (CC-BY-4.0) — domain mix

The cf-pairs JSONL files contain transcription_id + stress_index + speaker_id + style references; users instantiate audio at load time from the upstream HuggingFace datasets.

Reproducibility

from huggingface_hub import snapshot_download
import json

# Download
local = snapshot_download("nur-dev/stress17k-counterfactual-pairs", repo_type="dataset")

# Reproduce R1.8 cohort Probe-G_neutral (= 0.5122 ± 0.0039 across 5 seeds)
import numpy as np
seeds = [1234, 1235, 1236, 1237, 1238]
vals = [json.load(open(f"{local}/eval_results/stage3p8_eval/seed{s}/summary.json"))
            ["adapter"]["accuracy_neutral"] for s in seeds]
print(f"R1.8 Probe-G_neutral cohort: {np.mean(vals):.4f} ± {np.std(vals):.4f}")

License

CC-BY-NC-4.0 (inherited from Stress-17K-raw upstream). Permitted for academic research, ablation studies, reproducibility checks, pedagogy. Commercial use is not permitted under upstream dataset licenses.

Citation

@software{kadyrbek_frozen_stress_llm,
  author  = {Kadyrbek, Nurgali},
  title   = {frozen-speech-llm-stress: research code for frozen-frozen speech-to-{LLM} adapters under counterfactual training},
  year    = {2026},
  url     = {https://github.com/Nurgali-Kadyrbek/frozen-speech-llm-stress}
}

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Total file size:

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Collection including nur-dev/stress17k-counterfactual-pairs

Beyond Transcript Alignment

Collection

Frozen-frozen speech-LLM adapters + counterfactual training. Code: github.com/Nurgali-Kadyrbek/frozen-speech-llm-stress • 8 items • Updated May 3