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SUMMARY
A leading video game company partnered with us to optimize speech-to-text outputs from meeting audio shared in English. Though the audio was processed by a speech engine with millisecond-level timestamps, accuracy gaps remained due to non-native speech patterns. We enhanced the transcriptions using high-proficiency, non-native English resources, delivering clean, accurate output aligned with time-coded error reports.
THE CHALLENGE
- Inaccurate recognition of non-native English speech by the automated engine
- Inconsistencies in millisecond-aligned timestamps and actual spoken words
- High volume of audio (250k milliseconds) requiring precise manual intervention
- Need for domain understanding to resolve terminology misinterpretation
SOLUTION
- Deployed expert linguists with high English proficiency and domain familiarity
- Manually corrected and validated time-stamped transcriptions
- Developed structured workflows for aligning engine output with human edits
- Used in-house QC protocols to ensure accuracy and consistency
- Delivered annotated outputs in CSV format for easy client integration
KEY OUTCOMES
- Achieved 98% transcription accuracy using human-in-the-loop refinement
- Generated detailed CSV-based error reports with corresponding timestamps
- Successfully optimized outputs from pre-run speech engine data
- Delivered fully cleaned and verified transcripts over 4.5 months
