Lifted, an Upwork Company™
Audio Tagging Specialist English Language Emotion Manner Annotation
Lifted, an Upwork Company™, San Francisco, California, United States, 94199
Job Description
Summary We’re seeking detail-oriented Audio Tagging Specialists for English Language to assist with annotating transcribed audio clips. This role involves labeling audio content with emotional tags (e.g., happy, frustrated, neutral), manner tags (e.g., shouting, whispering, calm), and precise timestamps down to the millisecond.
You’ll use our internal tagging tool, so candidates should be comfortable learning new platforms quickly and following detailed annotation guidelines. Experience in linguistic labeling, audio transcription, or dataset creation is highly preferred.
Responsibilities
Review transcribed audio clips for accuracy and context
Apply emotional and manner tags to each segment (e.g., tone, intensity, vocal expression)
Insert precise timestamps for all relevant moments (down to the millisecond)
Ensure consistent tagging following provided guidelines and examples
Collaborate with project managers or QA reviewers to maintain high data quality
Qualifications
Prior experience with audio tagging, transcription, or annotation projects
Strong attention to detail and consistency
Comfort using web-based or proprietary tools for labeling data
Excellent comprehension of English and language that you are applying for
Ability to follow written instructions precisely
Reliable internet connection and access to a computer with audio playback capability
Preferred Experience (Nice to Have)
Background in linguistics or related field
Familiarity with audio analysis tools or time-based tagging software
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Summary We’re seeking detail-oriented Audio Tagging Specialists for English Language to assist with annotating transcribed audio clips. This role involves labeling audio content with emotional tags (e.g., happy, frustrated, neutral), manner tags (e.g., shouting, whispering, calm), and precise timestamps down to the millisecond.
You’ll use our internal tagging tool, so candidates should be comfortable learning new platforms quickly and following detailed annotation guidelines. Experience in linguistic labeling, audio transcription, or dataset creation is highly preferred.
Responsibilities
Review transcribed audio clips for accuracy and context
Apply emotional and manner tags to each segment (e.g., tone, intensity, vocal expression)
Insert precise timestamps for all relevant moments (down to the millisecond)
Ensure consistent tagging following provided guidelines and examples
Collaborate with project managers or QA reviewers to maintain high data quality
Qualifications
Prior experience with audio tagging, transcription, or annotation projects
Strong attention to detail and consistency
Comfort using web-based or proprietary tools for labeling data
Excellent comprehension of English and language that you are applying for
Ability to follow written instructions precisely
Reliable internet connection and access to a computer with audio playback capability
Preferred Experience (Nice to Have)
Background in linguistics or related field
Familiarity with audio analysis tools or time-based tagging software
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