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QA Speech-to-Text Audio Collection Project

telus digital·Worldwide·mid
llm
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Job description TELUS Digital is seeking quality assurance specialists to participate in a Speech-to-Text (STT) script validation project. Participants will review and validate LLM-generated scripts in Malay English (Manglish), ensuring they meet quality standards for grammatical accuracy, completeness, and naturalness. During script validation reviews through our FTS platform, you will review LLM-generated Malay English (Manglish) scripts with predefined headers/tags, validate scripts for incomplete sentences and critical grammatical errors, conduct manual quality review to ensure naturalness and colloquial accuracy, process and QA sample batches through our FTS platform, and flag linguistic inconsistencies or edge cases for escalation. The Primary Objective The primary objective of this project is to ensure the integrity and quality of scripts that will be used for audio recording. Your work ensures that only high-quality, natural-sounding scripts are used for audio recording and speech recognition technology development, which will help improve speech recognition models that understand and process natural speech in the Malaysian context. Expected Project Duration July 2026 – September 2026 Time to Complete the Task 20 hours per week Location: Remote (work from home) Qualification path Payment Rate: $4.50 USD per hour for script validation tasks Payment is calculated based on the hourly tasks assigned and completed. The number of hours and tasks assigned will depend on script availability, your QA performance quality, and project needs. This is an Independent Contractor opportunity. Payments will be made via Hyperwallet. Other Requirements: 18+ years of age Native speaker of Malay language Proficiency in English (including Malay English/Manglish) Strong understanding of Malaysian English colloquialisms and dialect variations Keen attention to detail and ability to identify grammatical inconsistencies Ability to use FTS platform and other digital QA tools Stable in

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