Audio Review, also called Voice QA Desk, is a quality-control application designed to evaluate short audio submissions during AI-training workflows. It supports the screening stage before a submission moves to client review and a main task campaign.

An expert is onboarded.

The expert submits a screener task through Audio Review.

The submission is reviewed by the client.

Approved experts are added to the main task campaign.

The app analyzes audio clips of roughly 10 seconds to help determine whether an expert qualifies to proceed to client review.

It checks a recorded submission word for word against an expected reference script.

The review combines technical and linguistic checks, including:

Audio specifications, including a minimum 24 kHz standard for WAV or FLAC files

Spelling and grammar

Naturalness and consistency

Gender and dialect

Audio Review is designed around a target average handling time of 50 seconds per task. It produces audit reports and supports corrected-audio generation with male or female voice options when the original recording does not meet the required quality standard.

The app combines speech-to-text for transcription comparison, NLP and LLM-based evaluation for linguistic criteria, text-to-speech for corrected audio, digital signal processing for audio-specification checks, and a web interface for task management, file uploads, and operational metric tracking.

As an AI Trainer, I defined the evaluation workflow, quality requirements, and operational logic for a repeatable audio-review process. The aim was to turn audio screening into structured, reviewable quality data that supports consistent decisions before experts enter a campaign.