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metadata
dataset_info:
  features:
    - name: user
      dtype: string
    - name: age
      dtype: int64
    - name: ethnicity
      dtype: string
    - name: gender
      dtype: string
    - name: phq1
      dtype: float64
    - name: phq2
      dtype: float64
    - name: phq3
      dtype: float64
    - name: phq4
      dtype: int64
    - name: phq5
      dtype: int64
    - name: phq6
      dtype: int64
    - name: phq7
      dtype: int64
    - name: phq8
      dtype: float64
    - name: phq9
      dtype: int64
    - name: phq
      dtype: float64
    - name: phq_2
      dtype: float64
    - name: gad1
      dtype: float64
    - name: gad2
      dtype: float64
    - name: gad3
      dtype: float64
    - name: gad4
      dtype: float64
    - name: gad5
      dtype: float64
    - name: gad6
      dtype: float64
    - name: gad7
      dtype: float64
    - name: gad
      dtype: float64
    - name: gad_2
      dtype: float64
    - name: duration
      dtype: float64
    - name: prompt_vad_cut_duration
      dtype: float64
    - name: prompt_vad_trimmed_duration
      dtype: float64
    - name: conversational_vad_cut_duration
      dtype: float64
    - name: conversational_vad_trimmed_duration
      dtype: float64
    - name: mos_pred
      dtype: float64
    - name: noi_pred
      dtype: float64
    - name: loud_pred
      dtype: float64
    - name: dis_pred
      dtype: float64
    - name: col_pred
      dtype: float64
    - name: bin_phq
      dtype: int64
    - name: bin_gad
      dtype: int64
    - name: split
      dtype: string
    - name: prompt
      dtype: string
    - name: state
      dtype: string
    - name: income
      dtype: string
    - name: english_preferred
      dtype: string
    - name: preferred_lang
      dtype: string
    - name: scores_anxiety
      dtype: float64
    - name: quantized_labels_anxiety
      dtype: int64
    - name: scores_depression
      dtype: float64
    - name: quantized_labels_depression
      dtype: int64
    - name: is_unbiased
      dtype: bool
  splits:
    - name: validation
      num_bytes: 4337865
      num_examples: 8113
    - name: test
      num_bytes: 3743545
      num_examples: 7034
  download_size: 1717911
  dataset_size: 8081410
configs:
  - config_name: default
    data_files:
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*
license: apache-2.0

Overview

This dataset includes audio-based model scores, clinical mental health labels, and demographic metadata for the validation and test sets used in the development of https://huggingface.co/KintsugiHealth/dam. Demographic statistics covering the training set as well are included in this model card.

The model was trained and evaluated on a large-scale speech dataset collected from approximately 35,000 individuals via phone, tablet, or web app, which corresponds to ~863 hours of speech data. The data was collected by asking each subject to speak for about 1 minute to various non-mental-health related prompts, e.g. talking about a favorite hobby or sport. Ground-truth labels were derived from both clinician-administered and self-reported PHQ-9 and GAD-7 questionnaires, ensuring strong alignment with established clinical assessment standards. The data consists predominantly of American English speech. However, a broad range of accents is represented, providing robustness across diverse speaking styles.

This data has been redacted for privacy purposes, so no personally identifiable information is included. In particular, the audio itself is excluded. In its place are model scores predicted by https://huggingface.co/KintsugiHealth/dam. Any audio streams containing less than the 30 seconds of speech needed to run this model have also been excluded from the dataset, but are included in the demographic statistics below.

While it is not possible to verify these scores by running the model directly, since the input audio is redacted, the authors hope the scores, accompanying labels, demographic data are useful for threshold tuning and independent research questions.

Demographics

Train Validation Test Total
Number of unique subjects 23,743 6,047 5,353 34,457
Total number of audio files 43,945 11,073 9,810 64,828
Audio duration, s - Average (SD) 56.4 (13.6) 56.8 (13.8) 56.1 (13.6) 56.4 (13.7)
Audio duration, s - Median 56.8 57.6 55.7 56.7
Audio duration, s - Mode 79.9 79.9 79.9 79.9
Audio duration, s - Range 30-229 31-231 31-176 30-231
Audio duration, hr - Total 688.5 174.7 152.9 863.2
Age, y - Range 18+ 18+ 18+ 18+
Age, y - Average (SD) 45.2 (16.8) 45.4 (16.8) 45.5 (16.7) 45.3 (16.8)
Age, y - Median 42 43 43 42
Age, y - Mode 30 30 41 30
Gender, % - Female 57.5 57.8 57.8 57.6
Gender, % - Male 41.1 41 40.7 41
Gender, % - Not specified 0.4 0.4 0.3 0.3
Gender, % - Other 0.8 0.7 0.8 0.8
Race/ethnicity, % - Asian or Pacific Islander 5.9 6 6 6
Race/ethnicity, % - Black or African American 12.6 12.5 11.8 12.5
Race/ethnicity, % - Hispanic or Latine 17 17.2 17.7 17.2
Race/ethnicity, % - Native American or American Indian 0.9 0.8 0.8 0.8
Race/ethnicity, % - Not specified 2.9 2.9 2.9 2.9
Race/ethnicity, % - Other or mixed race 4.4 4.4 4.4 4.4
Race/ethnicity, % - White 56.2 56.1 56.5 56.2
PHQ-9 score - Average (SD) 8.7 (6.7) 8.7 (6.8) 8.8 (6.8) 8.7 (6.7)
PHQ-9 score - Median 7 7 8 7
PHQ-9 score - Mode 0 0 0 0
PHQ-9 score - Range 0-27 0-27 0-27 0-27
GAD-7 score - Average (SD) 7.3 (6.1) 7.3 (6.2) 7.4 (6.2) 7.3 (6.2)
GAD-7 score - Median 6 6 6 6
GAD-7 score - Mode 0 0 0 0
GAD-7 score - Range 0-21 0-21 0-21 0-21

Threshold tuning

Illustrations of how to use this data to tune model thresholds are provided in the model card https://huggingface.co/KintsugiHealth/dam.