Audio Annotation Trainer

Company Description:MillionLogics is a trusted Oracle Partner and global leader in IT solutions, with operations in London, UK, and a development hub in Hyderabad, India. Specialising in innovative and scalable services, MillionLogics empowers enterprises through data & AI, cloud solutions, IT consulting, and custom application development. With a team of 85+ AI/ML experts, we deliver tailored solutions that foster digital transformation and operational excellence. We're committed to client success. We blend world-class technical expertise with strategic insight to deliver results.
Role:We are building a highly accurate, evaluation-grade dataset of transcribed, multi-channel audio recordings to assess multilingual, multi-speaker AI systems. This project involves evaluating high-quality and realistic conversations representing diverse dynamics, contexts, and demographics.
Offer detailsMode of work: Remotepay: Pay per task (Task can range from $55/per task -$66/per task)Number of Positions: 200 AvailabilityAvailability: Part Time Availability
Key Responsibilities
Audio Quality Assurance:Evaluate multi-channel audio recordings to ensure they meet strict technical and fidelity requirements.Verify channel isolation (ensuring no audio bleed) and confirm that recordings were captured in appropriate, quiet environments free from disruptive background noise, clipping, or low gain.
Transcription & Diarization Verification:Review human-validated transcriptions to guarantee exceptionally high accuracy and adherence to strict low error-rate (WER) targets.Confirm that transcripts correctly capture spontaneous, unnormalized speech, preserving natural conversational dynamics such as overlaps, interruptions, and false starts.Validate the precision of turn-level and word-level timestamps, as well as speaker identification, paying special attention to complex, overlapping dialogue , while comfortably reading and validating the underlying JSON-formatted data to ensure accurate metadata tagging and timestamp logic.
Metadata & Content Review:Verify the accuracy of all applied metadata, including demographic markers, contextual domains, and specific conversational tags.Enforce strict safety and privacy standards by auditing sessions to ensure no Personally Identifying Information (PII), toxic, or sensitive content is present.
Execution & Reporting:Assess the end-to-end quality of the annotation task, assigning clear pass/fail or agree/disagree statuses during your review.Provide detailed, actionable comments and feedback whenever disagreeing with an annotator's work.
Requirements & QualificationsExceptional ear for audio fidelity and the ability to detect subtle background noises, channel bleed, or clipping.Meticulous attention to detail for verifying word-level timestamps and strict, unnormalized verbatim transcription rules.Native proficiency in Spanish (Mexico)Ability to accurately assess complex multi-speaker dynamics.
The Workflow Contributors record unscripted group conversations. These recordings are run through an initial transcription and diarization pass, which contributors then human-validate and correct. As a QA Specialist, you are the final line of defense, responsible for reviewing the end-to-end quality of both the audio recordings and the human-verified annotations.
Ideal Backgrounds include:Linguists/Phonetics Experts: Deep understanding of natural, unnormalized speech patterns. Expertise in accurately identifying and annotating complex conversational dynamics, including overlaps, false starts, and backchannels.Language Teachers: Exceptional, native-level mastery of the target language. Ability to strictly adhere to verbatim transcription guidelines, documenting every stutter, filler word, and disfluency without applying prescriptive grammar corrections.Professional Transcriptionists: Ear for audio fidelity , rigorous timestamping skills, and experience meeting strict accuracy targets. Rigorous approach to precise turn-level and word-level timestamping.
Selection Process:Candidates must complete the assessment as part of the selection process.