| # Data dictionary: `data/main_study/` |
| |
| Anonymized data from the main paired-preference study: 94 analyzed |
| participants (48 text, 46 audio) rating 100 PRISM prompt pairs, 20 per |
| participant. ParticipantIDs are remapped from Firebase anonymous UIDs to |
| `P001..P094`. No Prolific IDs, timestamps, or session metadata that could |
| re-identify a participant are included, and every justification was |
| manually reviewed before release. |
| |
| ## Human ratings |
| |
| ### `participant_table_clean.csv` |
| One row per analyzed participant (n = 94). |
| |
| | column | type | description | |
| |---|---|---| |
| | ParticipantID | str | `P001`..`P094` | |
| | Modality | str | `text` or `audio` | |
| | SurveyCompleted | bool | reached the post-survey form | |
| | assignedTrialIDs | str | comma-separated PromptIDs assigned (20 per participant) | |
| | postSurveyDifficulty | int | self-reported difficulty, 1–5 | |
| | Age | int | years | |
| | Gender, Race, Ethnicity | str | self-reported | |
| | EnglishProficiency | str | Native speaker / Fluent / Conversational | |
| | Country | str | always `United States` in this sample | |
| | Education | str | self-reported, six levels | |
| | TotalSessionDuration | float | total session, ms | |
| | PassedAttention | bool | always True (failed participants are excluded) | |
| | AvgTrialDuration | float | mean trial duration, ms | |
| |
| ### `recruitment_summary.csv` |
| Counts per condition before exclusions: `Recruited`, `Completed`, and |
| `PassedAttention` (text 53/49/48, audio 53/51/46). Used for Table 5. |
|
|
| ### `long_audio_table_normalized.csv` / `long_text_table_normalized.csv` |
| One row per (participant × rated response). The main analysis inputs. |
|
|
| | column | type | description | |
| |---|---|---| |
| | PromptID | str | `<conv_id>_<turn_no>`, matches `prompt_stim_table` | |
| | ParticipantID | str | `P001`..`P094` | |
| | AudioClip | str | filename of the rated response (`.mp3`; also the response key in the text table) | |
| | TrialNumber | int | 0 = attention check, 1–20 = real trials | |
| | IsAttentionCheck | bool | | |
| | PresentedFirst | bool | this response was shown first on the trial | |
| | Rating | int | 1–100 response-quality rating | |
| | qualityRating | int | audio only: 1–100 audio-quality rating | |
| | overallPreference | str | the participant's A / Tie / B choice for the pair | |
| | revisedAfterBothRated | bool | a rating was edited after both were set | |
| | L | float | shrunk logit of Rating, `log(p / (1 − p))` with `p = (Rating + 0.5) / 101` | |
| | L_adjusted | float | L with the condition's mean position bias (second-shown minus first-shown) removed from second-shown responses | |
| | user_mean, user_sd | float | participant's mean and SD of L_adjusted | |
| | L_centered | float | L_adjusted − user_mean | |
| | z | float | L_centered / user_sd | |
| | Pref_Num | float | 1 = this response preferred, 0.5 = tie, 0 = the other response | |
| | Pref_Nom | int | the pair's choice: 1 = A, 2 = Tie, 3 = B | |
| | z_binned | int | decile of z, used in descriptive plots | |
|
|
| ### `long_audio_table_clean.csv` / `long_text_table_clean.csv` |
| The same rows without the participant-normalization columns. |
|
|
| ### `audio_data_table_clean.csv` / `text_data_table_clean.csv` |
| One row per (participant × trial), with responses A and B side by side: |
| both ratings and quality ratings, preference, justification, task |
| duration, relisten counts (audio), and rating-change counts. |
|
|
| ### `justifications_by_prompt_participant.csv` |
| Free-text justifications with `prompt`, `participantID`, `modality`. |
| |
| ### `justifications_by_prompt_respondent.csv` |
| The same justifications without participant or prompt keys |
| (`PreferenceJustificationText`, `Modality`), as used by the TF-IDF |
| analysis. |
|
|
| ## Stimulus tables |
|
|
| ### `prompt_stim_table.csv` |
| One row per prompt pair: the user query, prior conversation history, and |
| the two audio clip names. |
|
|
| ### `survey_long_format.csv` |
| One row per (PromptID × response): `AudioClip`, `AudioLength`, |
| `TextResponse`, `TextLength`, and `PrismRating`, the original PRISM |
| respondent's own rating. PrismRating is a human baseline, not an AI |
| rating. |
|
|
| ### `stimulus_topic_codes.csv`, `stimulus_topic_codes_raw.csv`, `stimulus_topics.json` |
| Inductive topic coding of the 100 prompts (Table 19). |
| - `stimulus_topics.json` is the induced topic list (11 topics), with the |
| generation counts and merges that produced it. |
| - `stimulus_topic_codes_raw.csv` has one row per (prompt × coder), with |
| the supporting quote and a `context_dependent` flag. |
| - `stimulus_topic_codes.csv` is the adjudicated code per prompt, joined |
| with that prompt's cross-modal gap, winner flip, and modality-slope |
| BLUP. |
|
|
| The coders are two LLMs (Gemini 3.6 Flash and GPT-4o), so every field |
| is model-generated. |
|
|
| ## Synthetic (AI) ratings |
|
|
| ### `synth_long_audio_table.csv` / `synth_long_text_table.csv` |
| GPT-4o ratings of the same stimuli, in the same long schema as the human |
| tables. Text: `gpt-4o-2024-11-20`; audio: `gpt-4o-audio-preview-2024-12-17`. |
| These are the ratings used in the paper's Tables 3–4. |
| `synth_long_*_table_gpt4o.csv` holds the same rows under the per-model |
| name, plus a `model` column. |
|
|
| ### `synth_long_{audio,text}_table_<model>.csv` |
| The same procedure with two more rater families (Tables 6–8): |
|
|
| | suffix | text model | audio model (audio-native) | |
| |---|---|---| |
| | `_gemini_36_flash` | `gemini-3.6-flash` | `gemini-3.6-flash` | |
| | `_qwen35_omni_flash` | `qwen3.5-flash` | `qwen3.5-omni-flash` | |
|
|
| Each adds a `model` column. Every rater makes 10 independent |
| generations per pair (`synthNo` 1–10), with presentation order |
| counterbalanced 5/5. `PresentedFirst` records the order actually shown, |
| and `Rating` is mapped back to the original A/B assignment. Audio models |
| take the waveform directly, with no speech-to-text step. |
|
|
| `qualityRating` in the audio tables is exploratory. Raters agree poorly |
| on it (panel ICC(2,k) = 0.32, against 0.83 for the response rating), and |
| each rater's quality score tracks its own content rating more than |
| objective DistillMOS. |
|
|
| ### `synthetic_ratings_10x.csv` / `synthetic_ratings_10x_<model>.csv` |
| The raw wide model output behind the `synth_long_*` tables (converted by |
| `analysis/01_data_prep/03_synth_to_long_csv_multi.py`). One row per |
| prompt with: |
| - the PRISM conversation fields (`user_id`, `conv_id`, `turn_no`, |
| `query`, both responses and lengths, audio filenames and durations); |
| - ten rating blocks per modality: `text_rating_{a,b}_<i>`, |
| `text_justification_<i>`, `text_order_a_first_<i>`, and the audio |
| equivalents, including `audio_quality_rating_{a,b}_<i>`; |
| - `mos_rating_{a,b}` from DistillMOS. |
|
|
| `user_id` and `conv_id` are PRISM's own published identifiers, not |
| study participants. The `*_justification_*` columns are model-generated |
| text. |
|
|
| ### `synthetic_ratings_fullcorpus_gemini_36_flash.csv` |
| Gemini 3.6 Flash ratings of the **full** unguided PRISM corpus (10,800 |
| prompt pairs), not just the 100 study pairs, in both modalities. It uses |
| the same model, prompts, settings, and output schema as the study's |
| Gemini ratings, but makes **one** generation per pair instead of ten, and |
| it has no DistillMOS columns. Audio is the full-corpus Kokoro TTS |
| (`stimuli/main_study/audio_full_zips/`); `audio_file_{1,2}` join to |
| `full_audio_index.csv` on `audio_file`. |
|
|
| One row per pair with: |
| - the PRISM conversation fields as above, plus `unsum_hist` / `sum_hist` |
| (unsummarized and summarized conversation history) and `prev_hist` |
| (the history given to the model; empty for first turns); |
| - one rating block per modality, in the same layout as the 10x files |
| with `<i>` = 1: `text_rating_{a,b}_1`, `text_justification_1`, |
| `text_order_a_first_1`, `response_rating_{a,b}_1`, |
| `audio_quality_rating_{a,b}_1`, `justification_1`, |
| `audio_order_a_first_1`. Ratings are 1–100 and mapped back to the |
| original A/B assignment; |
| - `rater_model` (`gemini_36_flash`) and `row_id` (0–10,799, the pair's |
| position in the corpus). |
|
|
| Presentation order was drawn per pair and modality (seed 0) and is |
| balanced (A first in 49.7% of text and 50.0% of audio pairs). These |
| ratings are not used in the paper's analyses. |
|
|
| ## Provenance |
|
|
| The human tables were generated by |
| `analysis/01_data_prep/02_convert_main_json_to_csv.py` from a Firestore |
| export of the live study, then anonymized. The stimulus tables come from |
| `analysis/01_data_prep/01_build_stim_tables.py`. Analysis outputs are in |
| `results/`, not here. |
|
|
