5 reasons why AI is not replacing your transcription team, but is definitely ready to augment it

There has been talk since at least as far back as 2015, if not earlier, about AI speech-to-text (aka Automatic Speech Recognition/ ASR) systems taking over the jobs of transcriptionists. I’m here to tell you it’s not happening. Having followed ASR for the past 15 years, and working with clients over the past 18 years on transcription operations, transcriptionists do more than just turn the spoken word into text. They ensure the transcript makes sense in context. They deal with tough accents and poor acoustic quality. They format the transcript to make it readable, and comply with regulatory requirements when applicable.

While speech-to-text systems such as Claudio have made significant strides, transcriptionists are here to stay in industries where accuracy of the transcribed text is critical to the quality and safety of business operations, legal, medical, insurance, manufacturing, and several other areas where seemingly minor errors can have major consequences.

The combination of a skilled transcriptionist equipped with an over 95% accurate first draft transcript ready to edit using shortcuts and hotkeys is the ideal combination to speed up transcript production by 80%. Here are 5 reasons why AI is not replacing your transcription team, but is definitely ready to augment it:

1 — Challenging audios with high background noise, accented, emotional and overlapping speakers really do a number on ASRs

While the ideal ASR friendly environment is studio quality audio with each speaker mic’ed separately, transcriptionists know that is far from the truth in the field. Think court rooms set up in old high ceiling stone buildings or gyms (for remote small towns), parties speaking away from the mic, and emotionally charged conversations.

Transcript Automation systems such as Claudio are able to handle basic echo removal and produce transcripts where all the speakers are transcribed. Transcriptionists are then able to pick up from where these systems stop, and edit the transcript to clean up any errors, ensuring the finalized transcripts can withstand legal scrutiny.

2 — The wrong homonyms in text change the context of the spoken word

A good transcriptionist’s pet peeve is seeing a homonym misspelt in context of the transcript. These tricky words sharing pronunciation or spelling but differing in meaning, wield an unexpected power within text, subtly manipulating the intended message. Picture a written conversation where "right" and "write" swap places or "their," "there," and "they're" play musical chairs.

Transcriptionists ensure that homonym errors are corrected when editing first transcripts.

3 — Readability and formatting are important to make the written word easy to read

This is one aspect where Transcript Automation definitely has a long way to go. While the transcribed text is over 95% accurate for over 85% of audios that we see with Claudio, punctuation and other aspects of formatting require transcriptionist verification. While customized profiles from systems such as Claudio provide the ability to set up rules for number of spaces between sentences, number formatting, vocabulary lists, and styling for capitalization, italics and underlining, they still require confirmation for accuracy.

4 — Transcript setup involves data from other sources

In legal, medical and insurance transcripts, a significant amount of setup is involved where data is required from source documents. Transcriptionists scour through these source documents to get data that goes onto the cover page, header, as well as in sectioning the transcript, specifically with respect to medical and medico-legal reports.

While systems like Loom Analytics’ Structura when used in conjunction with Claudio for medico-legal Transcript Automation workflows provide the ability to extract data from source documents such as insurance forms and letters of instruction, transcription staff still have to verify it for accuracy and ensure that the dictated report text is placed in the correct extracted sections.

5 — Speaker identification and notation requires the skills of a trained transcriptionists

Speech-to-text systems have a challenge with speaker identification (aka diarization) with more than 3 speakers in a single audio, as well as with speakers with similar voices. When first draft transcripts have speaker identification enabled, transcriptionists check the speakers and fix any errors including missed speaker changes. Claudio’s transcripts include hotkey enabled macros to make fixing these errors quick. For clients that choose to request transcripts without speaker identification, these same hotkeys make the process of adding in the speakers swift.

For legal transcripts, in addition to ensuring the speakers are correct, speaker notations for different parts of the legal proceeding are expected to follow a specific format. While hotkeys can be used to insert the correct notations, transcriptionists are the only ones who can provide the context on what notations to apply.

ASR transcription errors can change someone’s fate

In several sectors, transcription errors can have serious consequences:

Legal Proceedings: Court hearings, depositions, or legal documentations require precise transcription for accurate records. Misinterpreted or omitted words could significantly impact the legal process.

Medical Transcription: Transcribing medical dictations, patient histories, or consultations necessitates precision. Errors in medical transcription could lead to misdiagnosis or incorrect treatment.

Academic Research: Interviews, focus groups, or academic discussions need accurate transcription to maintain the integrity of research findings. Misinterpretation might alter conclusions.

Business Meetings: Transcribing meetings, conferences, or negotiations ensures accuracy in documenting decisions, agreements, or action points, crucial for organizational continuity.

In these contexts, transcription accuracy preserves information integrity, legal validity, and aids effective communication across various fields. Mistakes or inaccuracies could lead to misunderstandings, misinformation, or legal repercussions.

While Transcript Automation systems can produce formatted first draft transcripts that can save at least 80% time in the transcription process, transcriptionists ensure that the results are accurate and meet the stringent quality standards expected.