---
id: two-stage-user-styled-translation/06-game-dialogue-systems-supply-the-field-vocabulary
title: 'Two-stage styled translation exists only in pieces: 6. Game dialogue systems
  supply the field vocabulary'
report: https://ai.hiina.space/reports/two-stage-user-styled-translation.md
section: 6
version: 1
updated: '2026-10-27'
author: Hiina
---

Index of everything on this site: https://ai.hiina.space/index.md

# Two-stage styled translation exists only in pieces: 6. Game dialogue systems supply the field vocabulary

- Section 6 of 12 of the report "Two-stage styled translation exists only in pieces" by Hiina (v1, updated 2026-10-27)
- Report overview and contents: https://ai.hiina.space/reports/two-stage-user-styled-translation.md
- Previous: https://ai.hiina.space/reports/two-stage-user-styled-translation/05-a-small-renderer-is-plausible-measuring-it.md
- Next: https://ai.hiina.space/reports/two-stage-user-styled-translation/07-a-concrete-record-design-and-where-the.md

## 6. Game dialogue systems supply the field vocabulary

Older game dialogue systems already split what a line does from the words played. Valve's Response System layers concepts (reasons to speak, such as TLK_DANGER), criteria (speaker and world state), weighted rules, response groups and responses, with built-in repeat avoidance; the most specific matching rule wins, with fallback to less specific ones ([Valve Response System](https://developer.valvesoftware.com/wiki/Response_System); [Emily Short on Ruskin's GDC 2012 talk](https://emshort.blog/2012/03/16/gdc-2012-talk-on-dynamic-dialogue/)). Versu authors lines as "quips" that pair a text template with social effects, so one line carries surface and subtext at once, and characters get verb-level text overrides and adverbs for internal state ([Evans and Short, Versu: A Simulationist Storytelling System](https://www.cs.uky.edu/~sgware/reading/papers/evans2014versu.pdf)). Comme il Faut in Prom Week gives each social exchange a primary intent, several instantiations chosen by salience, and conditions on statuses, relationships, traits, social networks and a database of past social facts the dialogue can cite ([McCoy et al.](https://cs.uky.edu/~sgware/reading/papers/mccoy2014cif.pdf)). PERSONAGE drove extraversion through 29 continuous generation parameters, with judges rating extravert output 5.98 and introvert output 2.96 on a 1-7 scale ([Mairesse and Walker, ACL 2007](https://preview.aclanthology.org/fix_video/P07-1063.pdf)), which supports a user style interface of a few named knobs rather than paragraphs of prose.

LLM-era character systems bear on the renderer in one specific way. Character Card V2 separates situation (`description`, `scenario`) from voice samples (`mes_example`) across 15 fields, and supports `{{original}}` composition in both `system_prompt` and `post_history_instructions` ([Character Card V2 spec](https://github.com/malfoyslastname/character-card-spec-v2/blob/main/spec_v2.md)). Jun et al. tested 211 base profiles, each in structured and unstructured versions, on Qwen3-8B, Qwen3-235B-A22B, Mistral-Small-3.2-24B, OLMo-3.1-32B and DeepSeek-v3.2. Character familiarity was negligible on PersonaGym, structure had only marginal and inconsistent effects, and disposition was the bottleneck: immoral characters scored lower on every model ([Jun et al. 2026](https://arxiv.org/pdf/2601.04716)). Ubisoft's NEO NPC prototype fed writer-authored backstory and traits to an LLM that "impersonates" rather than improvises, and shipped nothing ([Game World Observer](https://gameworldobserver.com/2024/03/20/ubisoft-neo-npc-genai-real-dialogue-with-game-characters), secondary). Two consequences follow for translation. Spend the record's budget on intent and relationship content, not elaborate persona schemas. And flag intended harshness explicitly, because an aligned small model softening a villain, or refusing like Llama2 did in the formality study, is a fidelity failure. The generalisation toward "AI improvises from story templates", and on to assistant persona selection, is real but mostly irrelevant here: a translation renderer has a fixed source and should behave like a Valve response lookup with a generative last mile, not like a free agent.

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Text licensed CC BY 4.0 (attribution: Hiina, ai.hiina.space). Source: https://github.com/hiinaspace/ai-hiina-space