Speech recognition now handles Latvian, but the result still depends on the recording. Here are the tools, how to record for a clean transcript and what to do with the text afterwards.
Updated · 7 min read
Short answer
To turn audio into text, use an AI transcription tool that supports your language. To transcribe Latvian audio, the options include Tilde's transcription service, apps built on OpenAI's Whisper, Google Docs voice typing, Microsoft Word's Transcribe and YouTube's automatic captions. Accuracy depends on the recording: one microphone per speaker, no music under the speech and one language at a time. Then proofread the names and numbers, and label the speakers.
Clean input
Recognition works best with one clear voice per microphone and no music under the speech
Languages
Switching languages mid-sentence is harder for the tools than one language at a time
Proofreading
Check names, numbers and terms: the tools guess them
SRT
A text file with timestamps that works as captions on YouTube and in most editors
Privacy
Before you upload an interview, read where the tool processes the audio and whether it keeps it
Which AI transcription tools turn Latvian speech into text?
Each cell below comes from the tool's own page, as it read in October 2026. Tools change quickly, so check the page before you rely on a detail.
Upload a video and YouTube creates captions, which you review and edit in YouTube Studio under Subtitles
Listed, as is Russian
Automatic captions for live streams are English only
For Russian and English the choice is much wider: most of the tools above handle them, as do many others, while the list for Latvian stays short.
How accurate is Latvian speech recognition, and what lowers it?
Accuracy depends on the recording at least as much as on the tool, and Whisper's own page says its performance varies widely from language to language. These lower it:
background noise and echo;
too much distance from the microphone;
people talking over each other;
fast or mumbled speech;
dialect;
names, brands and jargon;
switching between Latvian, Russian and English, which is common in conversations in Riga;
music under the speech.
Before you send a long file, test five minutes of your own recording in two tools and compare the results.
How do you record so the transcript comes out clean?
Give each speaker their own microphone, close to the mouth.
Record in a quiet room with little echo. The guide to improving audio quality shows how to find and fix the usual problems.
Agree before you start that people will not talk over each other.
Keep music out of the recording and add it in the edit.
Record a lossless WAV file, or a high-bitrate one, and give the tool the clean speech track rather than the finished mix.
Say the names and terms clearly at the start. It helps your own proofreading later.
At our studio in Riga, an audio podcast recording gives each person at the table their own professional microphone, and the sound is mastered.
How do you clean up an interview transcript and label the speakers?
After transcribing an interview, always proofread the text:
Make a first pass for names, numbers and terms. Use find and replace for an error that repeats.
Label the speakers. Some tools separate them automatically: according to their pages, Tilde and Word's Transcribe both do, and Word numbers them ("Speaker 1", "Speaker 2"). Otherwise mark them by hand, for example "Host" and "Guest".
Add timestamps at each change of speaker or at each paragraph, so you can find a passage in the audio.
Choose the style: full verbatim or clean verbatim (see the table below).
Listen through once at 1.25 or 1.5 times speed while you read along.
Transcript styles
Style
What stays
Use
Full verbatim
Every "um", repetition and false start
Research, legal records
Clean verbatim
The words, without fillers, repetitions and false starts
If you would rather hand over the edit itself, our editors edit podcast video and sound for €40/h, including recordings made outside the studio.
Is transcription free, and what happens to your recordings?
Options without a subscription:
Google Docs voice typing, for live speech;
YouTube's automatic captions, on a video you upload: once you have corrected them, you can download the subtitles in YouTube Studio under Subtitles, then Options and Download subtitles;
Whisper on your own computer: it is open source under the MIT licence, which allows use free of charge, but the larger models need a capable machine.
Word's Transcribe comes with a Microsoft 365 subscription and covers 300 minutes of uploaded audio a month. Tilde has monthly plans with a 14-day free trial, as listed in the table above.
Privacy depends on where the audio is processed. Whisper on your own computer keeps the audio with you. Cloud tools process it on their servers, so read what each page says about storage and use. Tilde's page, for example, says your data is not used to train public AI models and offers on-premises, private-cloud and EU-based options. Word saves uploaded recordings to a Transcribed Files folder in OneDrive. Ask interviewees for permission before you upload their voices, and keep confidential recordings away from tools whose terms you have not read. This is practical advice, not legal advice.
Frequently asked questions
Can I transcribe Latvian audio for free?
Yes: Google Docs voice typing for live speech, YouTube's automatic captions on an uploaded video, or Whisper on your own computer. Check each page for its limits.
Can I transcribe a recording made on a phone?
Yes. Export the file and upload it to a tool that accepts files. Next time, put the phone close to the speakers and away from noise.
How long does transcription take?
Automatic tools are usually quick. Proofreading is the slow part: allow at least as long as the recording itself, and more when there are several speakers.
Is an automatic transcript good enough for subtitles?
Yes, once you have proofread it and split it into short lines. Export it as an SRT file. For subtitles in another language, see the translation guide linked above.
Can tools tell the speakers apart?
Some label speakers automatically: check the tool's page. One microphone per speaker and no overlapping speech help either way.