At Tolly, we believe rigorous testing is essential to extracting real value from AI transcription. Our recent best practices exercise (#225501) provided deep insights into achieving consistent, accurate transcription in real-world scenarios. Here are the top five takeaways:
1. Word Error Rate (WER) is Still King
WER remains the gold-standard measure. Solutions with a WER under 5% are considered excellent, but achieving that consistently requires careful selection and thorough testing under realistic conditions.
2. Dialect and Accent Variation Dramatically Impacts Accuracy
Even the strongest AI transcription engines struggle with dialect diversity. Transcription accuracy can vary significantly from as low as 3% WER for Midwestern American English to over 17% for Scottish English accents. Businesses must comprehensively test their specific use cases.
3. Repeated Testing Uncovers Hidden Variability
Single-run tests can misrepresent performance. Our research found notable variance between runs, reinforcing the need for multiple test iterations per audio sample (at least three recommended) to accurately gauge performance.
4. Synthetic Voices Accelerate and Standardize Testing
Leveraging Text-to-Speech (TTS) significantly streamlines testing by rapidly generating diverse accents without human variability. TTS allowed our team to design extensive, repeatable evaluation frameworks quickly and cost-effectively.
5. Background Noise and Crosstalk Testing Are Essential
Real-world audio isn't pristine. Our best practices guide emphasizes that background noise and overlapping speech significantly disrupt transcription and speaker diarization accuracy. Simulating these conditions is crucial for realistic assessment.
Putting Best Practices into Action
For organizations evaluating AI transcription, we recommend:
Defining clear WER targets based on business needs
Building accent and dialect testing matrices using TTS
Running multiple tests per scenario to identify true performance variability
Intentionally incorporating background noise and crosstalk into testing scenarios
Documenting all tests thoroughly for future reference and benchmarking
By adhering to these best practices, you ensure your transcription solution can handle the complexities of real-world communication effectively.
Ready to enhance your AI transcription accuracy? Reach out to our team today for guidance on conducting robust, insightful tests that inform smarter technology decisions.