Huzayfah-Patel/mindbridge-phq9-hindi-audio-fixtures

MindBridge Hindi PHQ-9/GAD-7 — Audio Fixtures (30 clips)

Hindi audio fixtures for OIWER (Orthographically-Informed Word Error Rate, AI4Bharat metric) audio-quality benchmarking on Gemma 4 E2B's native USM conformer audio encoder. Used to verify post-fine-tune audio quality has NOT regressed vs base E2B (audio modules explicitly frozen via requires_grad=False during training to preserve the native USM encoder).

Recording setup

• —30 clips spanning PHQ-9 Sections A-D + GAD-7 + Item-9
• —Recorded via SuperWhisper Scribe on macOS — native output is 16 kHz mono Int16 WAV, exact OIWER spec target (no ffmpeg resample needed)
• —Single speaker: builder's father (native Hindi reader/writer, Bihar/UP regional accent, ~60-year-old male). Named with explicit consent.
• —Naming convention: NN_<descriptor>.wav where NN is chronological capture order

Reference transcripts

audio-fixtures-transcripts.jsonl carries Devanagari Hindi + English gloss per clip, plus the source script segment ID.

OIWER benchmark protocol

Compare base E2B vs fine-tuned E2B transcriptions on the 30 clips. Threshold: −2pp absolute regression triggers fine-tune drop. See tools/oiwer_eval.py in the upstream repository.

Known limitations

• —Single speaker — no inter-speaker reliability characterization
• —Single recording environment (quiet indoor)
• —30 clips is small for statistical claims; treat as sanity-check, not rigorous ASR benchmark

License

CC-BY 4.0

Authorship & consent

Co-authored by Huzayfah Patel (UK-registered psychiatrist + software engineer) and Nazir Patel (native Hindi reader/writer + co-contributor; named with explicit consent). No real patient data is included in any artifact in this collection.

Ethics & responsible AI

• —Synthetic clinical vignettes only. All Hindi utterances are authored by Nazir Patel (Phase A direct dictation via SuperWhisper Scribe with cloud LLM post-process) or generated by a Gemma 4 26B-A4B MoE teacher (Phase B teacher expansion). No real patient data, no real clinical encounters, no de-identified records.
• —IRB review not required under FDA / NHS digital-health responsible-AI norms — synthetic-data + no human-subjects research exemption applies. Documented in the upstream repository's dataset card per project specification.
• —Native-speaker consent. Nazir Patel is named with explicit permission to credit. His contribution is foundational to the dataset's Hindi quality: hand-dictated 144 seeds (Phase A) + voiced 30 OIWER audio fixtures (Phase A Friday) + reviewed 30 stratified random rows for Hindi authenticity (Phase D, 0/30 rejection).
• —Clinical-deployment caveat. This dataset is NOT validated for clinical deployment. Production use in India would require: (a) multi-clinician inter-rater reliability study; (b) ASHA field testing with usability + clinical-outcome measurement; (c) CDSCO/DCGI regulatory review per India Medical Devices Rules 2017. Treat all artifacts in this collection as a research demonstration submitted to the Gemma 4 Good Hackathon, not as a deployable clinical tool.
• —Safety architecture beyond the LLM. The companion iOS app handles Item-9 (suicidality) via a deterministic rule engine layered on top of the fine-tuned LLM — the model is one signal in a defense-in-depth pipeline, NOT the sole safety net. Mandatory Tele MANAS 14416 + KIRAN 1800-599-0019 helpline blocker screen ships with every Item-9 positive regardless of the LLM's confidence. Marginal-improvement policy pre-specified: sub-threshold Likert improvement (6-9pp delta) → drop the fine-tune and ship the base model honestly.

Medical references

This work draws on the following clinical-screening + India-deployment precedents:

• —PHQ-9 Hindi validation — Kochhar PH, Rajadhyaksha SS, Suvarna VR. Translation and validation of brief patient health questionnaire against DSM IV as a tool to diagnose major depressive disorder in Indian patients. J Postgrad Med. 2007 Apr-Jun;53(2):102-7. PMID: 17495375. DOI: 10.4103/0022-3859.32209.
• —PHQ-9 + GAD-7 cross-cultural India applicability — De Man J, Absetz P, Sathish T, et al. Are the PHQ-9 and GAD-7 Suitable for Use in India? A Psychometric Analysis. Front Psychol. 2021;12:676398. PMID: 34054677. DOI: 10.3389/fpsyg.2021.676398.
• —WHO mhGAP Intervention Guide v2.0 (2016) — World Health Organization. mhGAP Intervention Guide for mental, neurological and substance use disorders in non-specialized health settings — Version 2.0. Geneva: WHO; 2016. Link. Paired with the 2023 mhGAP guideline update (third iteration of underlying evidence-based recommendations). Link.
• —SMART Mental Health (ASHA-administered screening RCT) — Maulik PK, Devarapalli S, Kallakuri S, et al. Mental Health Care Support in Rural India: A Cluster Randomized Clinical Trial. JAMA Psychiatry. 2024;81(11):1061-1070. PMID: 39141399. DOI: 10.1001/jamapsychiatry.2024.2305. ASHAs trained to administer PHQ-9 + GAD-7 via tablets across 44 PHCs in Andhra Pradesh + Haryana; ~170,000 adults screened.
• —ASHABot (LLM chatbot for community health workers) — Ramjee P, Chhokar M, Sachdeva B, et al. ASHABot: An LLM-Powered Chatbot to Support the Informational Needs of Community Health Workers. In: Proceedings of CHI '25. April 2025. arXiv:2409.10913. Microsoft Research India + Khushi Baby (Rajasthan deployment).
• —Pfizer PHQ-9 + GAD-7 licensing — per phqscreeners.com: "All PHQ, GAD-7 screeners and translations are downloadable from this website and no permission is required to reproduce, translate, display or distribute them." Hindi translation hosted under same free-use terms. Developed by Drs. Spitzer, Williams, Kroenke with an educational grant from Pfizer Inc.

Citation

@misc{patel2026mindbridge,
  title  = {MindBridge: Hindi-first PHQ-9/GAD-7 Screening with Gemma 4 E2B},
  author = {Patel, Huzayfah and Patel, Nazir},
  year   = {2026},
  url    = {https://github.com/HP-00/MindBridge-Gemma-4},
  note   = {Gemma 4 Good Hackathon submission}
}

Project context

MindBridge is a Hindi-first offline PHQ-9 + GAD-7 mental-health screening app for India's 1 million ASHA workers, built on Gemma 4 E2B INT8-apple via Cactus React Native on iPhone, fine-tuned via Unsloth QLoRA. Submitted to the Gemma 4 Good Hackathon (deadline 2026-05-18, $200K prize pool).