Live Consular AI Language Augmentation (LCALA) - OCS/ACS Pilot

Overview

Development stage

PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2025-01-01 (day precision)Source: 01/01/2025 00:00:00

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Emergency Management

Operational functions

Translation and transcription Derived by keyword rules; see methodology

Problem the AI is intended to solve

LCALA OCS/ACS Pilot aims to close language gaps in routine, time-sensitive citizen services by providing on-demand interpretation for calls and in-person interactions. Today, limited interpreter availability and uneven reliance on bilingual staff can cause delays, confusion, and repeat contacts when conveying guidance or coordinating with local authorities. LCALA seeks to improve clarity and timeliness of these communications, reducing callbacks and handoffs, while remaining assistive only and not replacing certified interpreters where required.

Expected benefits

Faster, clearer OCS/ACS communications; Fewer repeat contacts and escalations; Service equity and accessibility; Staff efficiency; Interagency coordination.

System outputs

LCALA provides real-time transcription and neural machine translation of spoken exchanges on demand, delivering translated audio and on-screen text on the device; when enabled, it can generate a brief time-stamped transcript of the conversation.

Technology

AI classification

Natural language processingSource: Natural Language Processing: AI that processes, interprets, and shares information in human language.

System name(s)

Not reported

Custom-developed code

No

Public source code

Not reported

Sourcing

How it was built

Purchased from vendorSource: a) Purchased from a vendor

Vendor (as reported)

Microsoft

Vendors (standardized)

Microsoft

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

No

Privacy Impact Assessment

Not reported

Authorization to Operate

No

Demographic features

k) None of the above

Training and evaluation data

LCALA uses Microsoft’s vendor-managed Speech-to-Text and Neural Machine Translation models, which are trained and fine-tuned on large, proprietary multilingual speech/text corpora and evaluated with standard metrics (e.g., WER for speech; BLEU/ChrF/COMET with human review for translation). No Department of State audio or transcripts are used to train or fine-tune these models (no-trace processing). For this pilot, the team performs limited operational Quality Assurance (e.g., sampled named-entity accuracy, latency, officer re-ask rates) to evaluate performance in the visa-interview context.

Federal Data Catalog

Not reported

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported