Transcription is merely a starting point for call recording review and even the voice portion video recording review.. That said, voice-to-text technologies and even search tools built for transcripts still haven’t met both of the distinct last-mile-needs around using transcripts for compliance. This paper will provide specifics on how and why that will impact your compliance program, and what you can do about it. That includes discussing how to use NLP to move beyond word errors and focus instead on context, domain relevance, and intent within the conversation. The paper will also cover ways to then leverage Machine Learning-based detections on those normalized transcripts to automate the detection of specific risks.
All this with the intent of helping you to avoid the common pitfalls and over focus on word accuracy of the transcript versus creating an efficient and effective way to identify the right compliance risks in your recordings.
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