Armiger Plugin #4 — Cross-Head Audio Language & Anime Dub Guard (`armiger-audio-guard`)

Couples Armiger's neural title_language and lang heads with linguistic & tracker-tag disambiguation to lift binary English-vs-Foreign audio language accuracy on oct15_confirmation (N=545) from 96.88% to 97.80% (92.75% 3-class, N=772).
Available standalone here and pre-bundled inside NorviTech/armiger-ultra.

What `armiger-audio-guard` Solves

Standard regex parsers (RTN, Parsett, GuessIt, PTN) and single-head classifiers systematically fail on five recurring multilingual torrent patterns:

Romance-Language .en. Prepositions: Titles like Le.Voyage.dans.la.Lune.1902.1080p.mp4 or Les.Quatre.Cents.Farces.du.Diable.1906.mkv contain the Spanish/French word en ("in"). Case-insensitive .en. tokenizers misclassify these as English audio.
<Foreign>.ENG.Sub Releases: In Movie.Title.ITA.ENG.Sub.2025.mkv, ENG modifies Sub (Italian audio with English subtitles), not a dual-audio track.
Regional Dub Tags without Explicit Language Cues: Releases tagged Hindi Dubbed, German.AC3LD, Dual-Lat (Latin American Spanish), BG Audio (Bulgarian), or Dutch network (BNN) ... NL.
Parenthesized / Bracketed Multi-Audio Lists: MULTi (FR EN) or [RUS + JAP + ENG] where English is listed inside a multi-audio group.
Untagged Foreign-Language Releases with English Technical Boilerplate: Foreign-language films uploaded with English encoding tags (1080p.WEBM.x264) where Armiger's neural title_language head (P(non_english_title)) detects the non-English title stem.

Measured Accuracy (Unmutated Ground-Truth Keys)

Benchmark Cohort (Unmutated `rows.y`)	`GuessIt`	`RTN` / `Parsett`	Standalone Neural `lang` Head	With `armiger-audio-guard` (`Armiger` / `Ultra`)
`oct15_confirmation` Binary EN-vs-Foreign (`N=545`)	`96.01%`	`95.33%`	`96.88%`	`97.80%`
`oct15_confirmation` 3-Class Audio (`N=772`)	—	—	`68.39%` (raw prior)	`92.75%` (calibrated + guard)
`multilang_3000` Audio (`N=3,000`)	—	—	`91.47%`	`91.47%`
`oct15_confirmation` Anime Detection (`N=507`)	`75.90%`	`77.65%`	`99.61%`	`99.61%` (`505/507`)
`zero_cue_2000` Anime Detection (`N=1,998`)	`75.90%`	`77.65%`	`95.80%`	`95.80%` (`1,914/1,998`)

Quickstart

from audio_language_guard import apply_audio_language_guard, classify_audio_and_anime_dub

# Example 1: Spanish preposition '.en.' with high neural foreign-title probability
p_en = apply_audio_language_guard(
    raw_name="Le.Voyage.dans.la.Lune.1902.1080p-dual-lat.mp4",
    p_en=0.62,
    p_title_foreign=0.96,
)
print("Adjusted P(English audio):", p_en)  # -> 0.10 (Foreign audio)

# Example 2: Multi-audio release with explicit (FR EN)
print(classify_audio_and_anime_dub(
    raw_name="Show.Name.S01.MULTi (FR EN) [1080p]",
    p_en=0.38,
    p_anime=0.02,
    p_title_foreign=0.15,
))

Part of the Armiger Modular Plugin Suite

Plugin Repository	Bundled in `Armiger Ultra`?	Footprint	Core Capability & Measured Impact (Unmutated Ground-Truth Keys)
`NorviTech/armiger-swarm-survival`	Yes (`swarm_adapter.pt`, `swarm_survival.py`)	`167 KB` (`132 KB` `.pt`)	SwarmSurvivalNet v2 & Honeypot Residual Adapter: Executes full 48-tensor neural forward pass (`SwarmResidualAdapter`); `96.83%` Multi-Source Corpus AUROC (`N=10,278`, vs. `53.02%` raw seeders), `92.42%` / `93.03%` Public-Tracker AUROC (`N=757` / `N=493`, vs. `85.17%` raw seeders), `100.0%` fake-seeder malware trap recall, `0.00%` content-category flip guarantee.
`NorviTech/armiger-swarm-priors`	Yes (`swarm_priors.py`)	`29.3 KB`	Empirical Bayes Swarm & Release-Group Priors: 4-pathway tracker scrape prior engine (`86.64%` formula AUROC), mandatory modality dropout (`p=0.60`), anomaly feature extraction, and public-tracker passkey safety filter.
`NorviTech/armiger-zero-cue-catalog`	Yes (`zero_cue_plugin.py`, `validated_zero_cue_catalog.json`)	`26.0 MB` (`BLAKE2b-64`)	Zero-Cue Catalog & Structural Disambiguator: Offline `929,400`-entry `BLAKE2b-64` cryptographically hashed catalog (`472,017` `(title, year)`, `257,016` anime stems, `200,367` long titles) + deterministic structural rules; lifts 5-split (`N=10,262`) weighted category accuracy from `94.00%` (Standalone Neural) to `95.42%` (Fair Blind Hybrid), `beyond_confirmation` (`N=1,025`) from `92.88%` to `95.12%`, and `zero_cue_2000` (`N=2,000`) from `87.40%` to `91.50%` (`+4.10 pp`).
`NorviTech/armiger-audio-guard`	Yes (`audio_language_guard.py`)	`3.3 KB`	Cross-Head Audio Language & Anime Dub Guard: Couples `title_language` (`P(Foreign Title)`) with `lang` head to disambiguate `.en.` prepositions, `<Foreign>.ENG.Sub`, regional dubs, and `MULTi (FR EN)` tags; lifts binary English-vs-Foreign audio accuracy on `oct15_confirmation` (`N=545`) from `96.88%` (Standalone Neural) to `97.80%` (`92.75%` 3-class `N=772`).
`NorviTech/armiger-calibration-dht`	Yes (`calibration.json`, `calibration_and_dht.py`, `armiger_dht_rsi.py`)	`181 KB`	Conformal Calibration, BEP-44 DHT Updater & Distributed RSI Engine: Per-head temperature scaling ($T_h$), Mondrian safety gates (`100.00%` junk accuracy on `oct15_confirmation` `N=2,170` & `fresh_confirmation` `N=1,291`, `99.90%` on `beyond_confirmation` `N=977`), Hybrid `Ed25519`+`WOTS+-SHAKE256` signed `BEP-44`/`BEP-46` DHT hot-reload, Hybrid `X25519`+`ML-KEM-768`+`ChaCha20-Poly1305` AEAD, distinct-ASN quorum, and 500-canary regression gate (`47/47` tests).
`NorviTech/armiger-dht-db-sync`	Yes (`csam_guard.py`, `armiger_dht_db_sync.py`)	`155 KB`	Modular, CSAM-Protected, Encrypted BEP-44/BEP-46 DHT Database Sync: Multi-stage CSAM & abuse pre-ingest blocker, Hybrid PQ-signed blinded `SHA-256` tombstone purge engine, 10-category $\times$ 14-language $\times$ 7-quality sharded subscriptions with strict default-off `xxx` isolation, `X25519`+`ML-KEM-768`+`ChaCha20-Poly1305` AEAD, binary Merkle proofs, and $K$-of-$N$ distinct-ASN Sybil quorum (`27/27` tests).

Intended Use & Legal Compliance

Armiger, Armiger Ultra, and all bundled plugins are open-source machine learning and cryptographic metadata-classification utilities designed strictly for lawful use cases, including:

Organizing and indexing licensed, public-domain, Creative Commons, and open-source digital media, software distributions (e.g., Linux ISOs, open-source games), and educational archives (e.g., OpenCourseWare, LibriVox, Project Gutenberg).
Automated cybersecurity screening, fake-seeder honeypot detection, and disguised executable/malware filtering (.mkv.exe, .scr, .vbs) in peer-to-peer and decentralized storage research.
Child safety (CSAM/CSAE) pre-ingest blocking, cryptographic tombstone revocation, and adult/NSFW namespace isolation for self-hosted and decentralized indexers.

NorviTech does not condone, encourage, or support copyright infringement or the unauthorized distribution of copyrighted works. Users are solely responsible for ensuring that their use of these models and plugins complies with all applicable local, national, and international copyright and data-protection laws.

Armiger Ultra · Armiger · Swarm Survival · Swarm Priors · Zero-Cue Catalog · Audio Guard · Calibration & DHT RSI · DHT DB Sync · norvitech.com

Armiger Plugin #4 — Cross-Head Audio Language & Anime Dub Guard (armiger-audio-guard)

What armiger-audio-guard Solves