How accurate is the automatic transcription of voice notes?

With clear speech and a quiet environment, automatic conversion into text is very usable today – the meaning comes across reliably, even if individual words can be wrong. With a lot of noise, very broad dialect or unclear speech, the error rate rises. For important notes, a quick read-through is advisable; the original recording is kept as the source.

Does speech recognition also work with Austrian dialect?

Modern speech recognition understands dialect-coloured standard German well – much better than just a few years ago. Broad dialect remains more difficult and leads to more errors. In practice, it works well to consciously speak closer to standard German when dictating, just as you would on the phone with a German supplier.

Does the employee have to edit the transcribed note?

Not necessarily. Many companies take over routine notes unchecked and only skim notes that carry weight – for example on complaints or unusual repairs. As the audio recording remains stored as the source, you can always listen again to what was actually said if in doubt.

Does the voice note replace the service report or the job sheet?

No. Working time, material and billing still belong in the job sheet, the service report and the ERP – that is where they are invoiced and kept. The voice note adds what has no place there: the cause of the fault, the solution and the particularities at the customer's site.

What happens to the audio recording after transcription?

It remains stored as the source document for the note, so you can listen again if anything is unclear. Role management controls who may access the recording. With a provider using EU servers and a data processing agreement (DPA), the recordings do not leave the European legal area and are not used to train third-party AI models.

Voice notes and dictation

Voice notes can be captured in your company by having employees briefly dictate into their phone after a job, with speech recognition automatically converting what was said into text – this is called transcription. The knowledge base assigns the note to the right customer or project and makes it searchable for the whole team. In this way, knowledge that previously existed only in the fitter’s head becomes a document that someone can still find in five years’ time. The effort for the individual: two minutes of speaking instead of twenty minutes of typing.

In brief

The most valuable knowledge in a company is created out on the job – and gets lost because nobody types up a report after the working day.
A voice note is the lowest hurdle for capturing this knowledge: dictate briefly, and the technology does the rest.
Speech recognition converts the dictation into text; the knowledge base assigns it to the customer, installation or project and makes it searchable.
Dialect and technical terms are a much smaller problem today than they used to be, but a brief check of important notes still makes sense.
Times and material still belong in the job sheet and the ERP – the voice note records the how: cause, solution, particularities.

Why does spoken knowledge get lost in companies?

A fitter has spent three hours puzzling over an awkwardly laid-out installation, found the fault and fixed it. What he worked out along the way would be worth its weight in gold on the next job: that on this type of installation the valve sits behind the panelling, that the manufacturer has a known series problem, that it is better to drive in via the yard at this customer’s. What usually gets recorded: nothing. The job sheet shows time and material – the rest stays in his head.

That is no reproach to the employees but a question of the hurdle. Someone coming back from their fourth job in the late afternoon does not sit down at the computer and write a report. For many practitioners, writing is a chore – talking is not. This is exactly where voice notes come in: capturing happens where the knowledge is created, directly after the job in the car, while everything is still fresh.

How does a dictation become a searchable document?

The route from spoken note to findable knowledge takes four steps, of which the employee only has to actively do the first:

Record. After the job, the employee dictates a short note into their phone: customer, installation, what the problem was, what the solution was, what the next person should know. Two minutes is enough – it is about substance, not nice sentences.
Transcribe. Speech recognition automatically converts the recording into text. The audio file is kept and linked to the text so you can listen again if in doubt.
Assign. Automatic tagging recognises from the content which customer, installation or project the note belongs to and files it accordingly – without anyone choosing folders or naming files.
Check and approve. Optionally, the note goes through a short check: skim it, correct obvious recognition errors, approve. For routine cases this step can be skipped.

From this moment on, the note is part of the company’s knowledge. If a colleague asks a year later “What was the issue with the ventilation failure at the joinery back then?”, the AI search delivers the answer together with a reference to the specific note – for example the dictation from January in which the colleague described the cause. The source is decisive here: the AI formulates the answer, but it has to back it up with the original document, because AI can be wrong.

How well does speech recognition understand dialect and technical terms?

Honest answer: surprisingly well, but not without errors. Modern speech recognition has made a big leap in recent years and copes well with the dialect-coloured standard German spoken in Austrian companies. Limits show with broad dialect, with strong background noise – for example when dictating right next to a running machine – and with very fast, unclear speech. The practical recommendation: dictate in the car or a quiet corner and consciously speak closer to standard German.

For technical terms, product names and proper names, a simple trick helps: terms frequently used in the company – manufacturer names, installation types, internal designations – are given to the system as a word list, so that “condensate drain” does not turn into recognition gibberish. Even so: a note on which a warranty question or a complaint might later depend should be skimmed briefly. The effort for this is a fraction of typing, and the recording is kept as evidence.

Which notes belong in the knowledge base – and which don’t?

Not everything spoken is company knowledge. Times, kilometres driven and material installed belong in the job sheet and the ERP – that is where they are invoiced, that is their leading system. The ERP knows what happened: which job, which material, which invoice. The knowledge base knows how it’s done: why the fault occurred, how it was fixed, what the next person needs to watch out for. A voice note that only repeats what is on the delivery note anyway achieves nothing – what is valuable is what is written down nowhere else.

A simple guiding question for dictation has proven itself: “What should the colleague know who drives to this customer in two years’ time?” This includes the cause of the fault and the solution, peculiarities of the installation, access and contact persons. Personal judgements about people do not belong there – a factual note such as “Access only after prior notice to the caretaker” must not become a character study of the caretaker. This keeps the knowledge base clean and saves discussion when customers request information about stored data under the GDPR.

What about data protection and the working atmosphere?

Important for context: a voice note is a self-dictation, not a recording of a conversation. No customer conversation is recorded; instead, the employee summarises afterwards – legally and on a human level, that is a big difference. Secret recordings of conversations are off limits; if you want to know more about the legal boundaries, the Austrian Economic Chamber (WKO) provides basics on data protection in companies at wko.at.

The same rules apply to the recordings themselves as to all documents in the company’s knowledge: control access via roles, keep personal data to a minimum, inform the workforce transparently. With Goma-it’s AI knowledge base, recordings and texts are stored on EU servers and are not used to train third-party AI models, and every AI answer names the source – so it remains traceable which note a piece of information comes from. For the working atmosphere, the start is what matters most: begin voluntarily, with two or three employees, and make the benefit visible instead of imposing an obligation to dictate.

How do you get started with voice notes in your company?

The pragmatic way in: two or three employees who spend a lot of time out on jobs dictate a short note after every job with substance – a guiding question as a framework, no formal requirements. After a few weeks the effect shows by itself, namely with the first “How did we solve that back then?” that the search answers from a note rather than from memory. From then on it usually carries itself, because those dictating benefit most themselves.

Voice notes are one source among several: service reports, email attachments, network folders and the paper archive supply the other building blocks of company knowledge. Which sources there are and in which order connecting them has proven itself is shown in the overview Connecting documents and systems. How the introduction works in practice in your company – from the first conversation to everyday operation – is described step by step under implementation process.

Voice notes and dictation: capturing spoken knowledge in your company