Audio Data Collection & Transcription – English Speakers

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  • Experience

    0 - 1 Years

Description

TELUS Digital (“TIAI”) is seeking English (India) speakers for our new Audio Data Collection project.

 

Task description:

 

The participants will have to record 2 unscripted audio samples (each approx. 30s long) – one natural and one with emotions, according to the provided instructions. The goal is to obtain natural recordings showcasing your accent.

 

In addition to the recordings, each participant needs to provide accurate transcriptions of the audios.

 

Please note: The participant-provided recordings may be used publicly by the client. By participating in this project, participants acknowledge and accept that their audio samples may be utilized in public-facing applications or services.

 

Expected Project Duration: September – November 2025

Estimated time to complete the task: up to 1 hour

 

Qualification path

 

Requirements:

  • Have access to a smartphone with either iOS 17.0 (or above) OR Android 8.0 (or above).
  • English (India) speaker.
  • Located in India.
  • Stable Internet connection for the duration of the task.
  • A quiet environment to record the audios.

 

Payment:

  • 10.5 USD for the whole task, paid upon successful completion and submission of the task.
  • This is an independent contractor opportunity.
  • Payment will be processed via our AI Community platform through Hyperwallet.

 

If interested, please send a copy of your resume to tiai_diverse_crowd@telusdigital.com with the subject title: Divyang Career: Audio Data Collection & Transcription – English Speakers (India)

 

Equal Opportunity

All qualified applicants will receive consideration for a contractual relationship without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected veteran status. At TELUS Digital AI, we are proud to offer equal opportunities and are committed to creating a diverse and inclusive community. All aspects of selection are based on applicants’ qualifications, merits, competence, and performance without regard to any characteristic related to diversity.

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