Transcription Features

// // introduction most downstream analytics processes rely on transcribed text, making speech to text one of the most valuable features in any contact center solution the noises that are common in call centers – for example, other agents conversing in the background – the conversational flow often branching off in multiple directions, and poor quality telephone signals pose unique challenges in accurately transcribing calls powered by decades of research and billions of contact center interactions, elevateai by nice provides unparalleled conversational accuracy and immediate access to transcripts, formatted https //docs elevateai com/tutorials/get phrase by phrase transcript or https //docs elevateai com/tutorials/get punctuated transcript // // models in november, we introduced echo , our next generation transcription model with echo elevateai delivers a significant leap in accuracy, outperforming our original, cx focused model by 40% and ensuring superior transcription quality across every use case to take advantage of the echo model, add the body parameter model to your post declare and set the value to echo as part of as part of declare an audio interaction note currently the echo model does not diarize between speakers, perform redaction or process for cx ai future releases will move echo towards feature parity with the cx model our original, purpose built cx model can be utilized by omitting the model parameter or setting it to cx // // pii redaction note pii redaction is performed on media processed with the cx transcription model media processed with echo are not redacted personally identifiable information (pii) associated with social social security numbers social social security numbers , credit card numbers credit card numbers and cvv numbers cvv numbers is automatically redacted prior to the transcription being stored or returned to you details related to the timing, type, and confidence for each redacted segment are returned when retrieving either a phrase by phrase phrase by phrase or punctuated transcript punctuated transcript remember all source data is deleted immediately and promptly upon processing see data retention & security data retention & security for additional detail sample transcription output { "redactionsegments" \[ { "starttimeoffset" 1467720, "endtimeoffset" 1468030 "result" "cvv", "score" 0 98745 }, ] } // // speaker labels elevateai automatically identifies and associates each phrase with a given participant (up to two) in the phrase by phrase phrase by phrase and punctuated transcript punctuated transcript mono audio speaker diarization for single channel audio files processed with the cx transcription model, elevateai leverages speaker diarization to identify and label each phrase within the transcript as one from participantone or participanttwo note this does not apply to mono media processed with the echo transcription model channel labels for dual channel audio files, such as a phone recording with the agent and customer on separate channels, elevateai will associate each phrase with a specific channel note that leveraging stereo recordings does not impact processing speed or fees