Custom vocabulary for contact center transcription: product names, brands, and agent jargon
Blog post from Gladia
Contact centers often face transcription challenges when generic speech-to-text (STT) models fail to accurately transcribe product names, brand terms, and agent jargon, leading to errors in downstream systems such as QA scorecards and CRM records. These issues primarily arise from out-of-vocabulary (OOV) errors, where models substitute unfamiliar terms with phonetically similar but incorrect words. Custom vocabulary dictionaries, using phoneme-similarity matching, address these errors by guiding transcription engines toward the correct terms before they reach downstream systems. This approach differs from post-transcription find-and-replace techniques by catching errors at the acoustic layer, thereby improving transcription accuracy for domain-specific terms. Implementing custom vocabulary involves building and maintaining a dictionary based on a company's product catalog and frequently used terms, with adjustments to ensure ongoing accuracy and alignment with compliance requirements. By improving transcription accuracy, contact centers can enhance QA processes, reduce manual overrides, and optimize overall operational efficiency.
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