call-multilingual-code-switching-aligner · v1.0.0 · 2026-09-18 · sha256 24fcbe1d8b8091cc
call-multilingual-code-switching-aligner v1.0.0A
Immutable. This exact content is served forever at /api/v1/blob/24fcbe1d8b8091cc.
--- name: call-multilingual-code-switching-aligner description: Offline experimental English/Spanish lexicon helper for phone-workflow demonstrations. Returns a code-mixing ratio and suggested style; no ASR or LLM prompt integration is included. version: 1.0.0 --- # Multilingual Code-Switching Aligner This offline prototype counts a small Spanish vocabulary in supplied text and suggests an English/Spanish mixing style. It does not identify arbitrary matrix languages, support Hinglish, or establish improvements in inclusivity, trust, or cognitive load. The helper returns a style label only. A separate host could use it as a suggestion, subject to the caller's stated language preference; rapport or cognitive-load benefits are not established. ## Scientific Foundation | Paper / Framework | Relevance | |---|---| | **Output Language Alignment for CSW** | Demonstrates that AI mirroring code-switching frequencies increases user trust and reduces linguistic anxiety. | | **Matrix Language Frame (MLF) model** | Myers-Scotton framework for distinguishing embedded words vs the matrix language. | | **FCA Consumer Duty (Vulnerability)** | Reduces cognitive load for non-native speakers by allowing them to use their natural hybrid dialects. | ## How it works 1. Supply a transcript string. An optional host ASR component is outside this contribution. 2. It strips punctuation and detects embedded vocabularies to calculate a **Code-Mixing Index (CMI)**. 3. The system returns a structured `CodeSwitchingReport` containing the CMI and the suggested `PromptStyle`. 4. A host may review the suggested style before updating a prompt; the helper performs no prompt or speech mutation. ## Decision Matrix | Code-Mixing Index (CMI) | Derived Prompt Style | Expected LLM Output Behavior | |---|---|---| | `CMI == 0.0` | `monolingual_english` | Strict monolingual English (standard). | | `0.0 < CMI < 0.30` | `low_code_switching` | Occasional embedded loan words (e.g., "gracias", "pero"). | | `CMI >= 0.30` | `high_code_switching` | Fluid Spanglish; alternating sentence clauses. | ## Expected Outcomes & Metrics Latency is a design target, not a measured integration benchmark. | Metric | Target | Notes | |---|---|---| | CMI Computation Latency | < 5ms | Runs via ultra-fast lexicon matching. | | Rapport / Trust Score | Not measured | No A/B evaluation of this helper is supplied. | ## Limitations & Known Constraints - **Lexicon Coverage**: The prototype uses a hardcoded vocabulary set. Production systems should use dynamic NLP models to classify embedded words for any language pair. - **ASR Dependency**: Requires an ASR model capable of transcribing code-switched audio without forcing translations (e.g. Whisper large-v3). ## Integration This is an offline text helper. Real-time middleware, ASR, language preferences, and LLM prompt updates are proposed host integration work.