AI-generated summary
Genesys Cloud voice transcription has several operational limitations and considerations that organizations should evaluate during implementation of speech and text analytics capabilities. Transcription of ACD agent consult recordings is not supported, and when agents initiate consults or transfers, the initiating agent's queue transcription settings remain active throughout the interaction regardless of the receiving agent's settings, potentially resulting in unnecessary transcription costs. Blind transfers can mitigate this by allowing the receiving agent's default settings to apply. All users involved in a consultation are considered transcription users for billing purposes, even if the transfer is not completed, and calls transferred to communicate users continue transcription with per-minute billing applied to the communicate user.
The platform exhibits specific transcription accuracy considerations, including potential misidentification of background music without vocals as filler words (um, ah) and inaccurate system icon representation in transcripts reflecting conference or agent activity. Consult segments are excluded from acoustic analysis calculations, and on-hold music may similarly be transcribed as filler words with incorrect agent attribution. Language changes configured through in-queue flows may not take effect if the transcription flow has not executed prior to transfer completion.
For BYOC Premises deployments, post-call voice transcription has a 10-hour maximum call duration limit, requires dual channel recording, and supports only Opus, PCMU, PCMA, or L16 audio formats. External trunk configuration dialect and language options are limited, with additional dialects requiring configuration through Architect flows. When transferring calls to external parties, participant identification in transcripts may not always be accurately reflected. Sentiment Feedback restricts phrase length to for Korean, Chinese, and Japanese language dialects.
Genesys Cloud provides comprehensive voice transcription capabilities supported by detailed documentation covering configuration, transcript understanding, and related speech and text analytics features, with additional resources available through community support channels