Accurate speech to text
Turn spoken audio into clear text with MAI-Transcribe-1 speech-to-text processing built for production transcription workflows.
MAI-Transcribe-1
accurate speech to textMAI-Transcribe-1 speech to text
MAI-Transcribe-1
Use MAI-Transcribe-1 to transcribe calls, meetings, interviews, subtitles, podcasts, and recorded speech with accurate speech-to-text output across multilingual and noisy-audio conditions.
MAI-Transcribe-1 dashboard
Upload audio and transcribe to text
Transcript
Transcription result
Preview
Product
Accurate transcription for real audio
MAI-Transcribe-1 is designed for users who need speech-to-text that performs well outside perfect studio recordings. It is built for meetings, support calls, media files, interviews, and production audio where transcript quality directly affects usability.
If you need cleaner transcripts from difficult audio, multilingual speech, or long recordings, MAI-Transcribe-1 is built for that kind of workload.
Features
What MAI-Transcribe-1 does well
Strong noisy-audio handling
Transcribe audio more reliably in noisy environments, including background noise, low-quality recordings, and overlapping speech.
25-language transcription
Use MAI-Transcribe-1 across 25 supported languages for multilingual speech-to-text and cross-market transcription workloads.
Fast batch transcription
Process uploaded audio efficiently for subtitle generation, meeting archives, media libraries, and large transcription queues.
Built for real audio
Use it on calls, meetings, interviews, podcasts, training recordings, and other speech data that is rarely perfectly clean.
Flexible export workflows
Convert audio into transcript-ready text for notes, captions, searchable archives, summaries, and downstream automation.
Community
MAI-Transcribe-1 on x
Use Cases
Where MAI-Transcribe-1 fits best
Urban Commute · English
Scene: On a moving subway or light rail, with rhythmic track noise and station announcements in the background.
I’m just heading back from the tech meetup. The presentation on neural networks was actually quite insightful. I was thinking we should pivot the landing page to highlight the real-time processing speed. Let’s sync on this once I’m back at my desk and can look at the codebase.
Busy Street Side · English
Scene: On a busy street, with distant traffic noise and occasional pedestrian conversations in the background.
Quick thought while I’m out grabbing lunch. We need to double-check the billing logic for the pro tier. Make sure the 'Redo' button is clearly visible in the dashboard UI. I’ll sketch out the updated user flow for the transcription history later tonight.
Timber Yard · English
Scene: In a timber yard or workshop, with wood handling sounds and distant machinery humming in the background.
I'm reviewing the inventory requirements for the timber yard project. We need to ensure the database can filter by wood species and moisture content. If we can get this logic into the Next.js frontend by Friday, we'll be ahead of schedule for the beta release.
Airport Terminal · German
Scene: In an airport terminal, with open ambient reverb and occasional German announcements in the background.
Ich sitze gerade am Flughafen und warte auf den Anschlussflug. Ich habe mir die neuen Marketing-Entwürfe angesehen. Die Farben passen perfekt zur Marke, aber wir sollten die Schriftart im Header noch etwas anpassen. Ich schicke dir die Details, sobald ich gelandet bin.
Outdoor Exhibition · French
Scene: At an outdoor exhibition or market, with light wind and low visitor chatter in the background.
Je me promène dans l'exposition, c'est très inspirant. J'ai eu une idée pour notre prochaine vidéo : on pourrait utiliser des animations de vieilles photos pour montrer l'évolution du projet. Qu’en penses-tu ? On peut en discuter plus longuement pendant le dîner.
Piazza Bistro · Italian
Scene: At an outdoor piazza bistro, with clinking tableware and distant bell chimes from the square.
Ciao! Sono in piazza, stiamo per ordinare. Ti ho chiamato solo per confermare il numero di persone per la riunione di domani mattina. Saremo in cinque, giusto? Perfetto, segno tutto su MAI-TRANSCRIBE-1 così non dimentico nulla. A più tardi!
Meeting transcription
Transcribe internal meetings, team calls, interviews, and recorded discussions into searchable text.
Call center transcripts
Turn customer support calls into structured transcripts for QA, auditing, review, and follow-up workflows.
Subtitle generation
Create text from podcasts, webinars, videos, and lessons for subtitles, captions, and accessibility use cases.
Podcast and media archives
Process long-form spoken content into transcripts that are easier to search, reuse, and summarize.
Research interviews
Convert user interviews, focus groups, and research sessions into text for analysis and reporting.
Training and education audio
Transcribe lectures, onboarding sessions, and learning content for review, search, and retention.
Pricing
Choose a plan and start using MAI-Transcribe-1
Basic
Best value for recurring light usage
$16.58/mo
$199/year
$238.802 months free
27,600 credits/year
2,300 credits/month average
About 372 transcription hours per year
- MAI-Transcribe-1 speech to text
- Credits billed by actual processing time
- Predictable annual budget
- No watermark or branding on transcripts
- Private transcription workflow
- Email support
- Commercial use
Standard
Best for growing transcription teams
$41.58/mo
$499/year
$598.802 months free
69,000 credits/year
5,750 credits/month average
About 930 transcription hours per year
- MAI-Transcribe-1 speech to text
- Credits billed by actual processing time
- Best fit for recurring call and meeting volume
- No watermark or branding on transcripts
- Private transcription workflow
- Priority support
- Commercial use
Pro
For agencies and high-volume audio pipelines
$83.25/mo
$999/year
$1198.802 months free
138,000 credits/year
11,500 credits/month average
About 1,860 transcription hours per year
- MAI-Transcribe-1 speech to text
- Credits billed by actual processing time
- Designed for long-form and batch-heavy pipelines
- No watermark or branding on transcripts
- Private transcription workflow
- Priority support
- Commercial use
Overview
What MAI-Transcribe-1 can do
MAI-Transcribe-1 is built for speech-to-text workloads where transcript quality matters. It is designed for multilingual audio, difficult recording conditions, and production transcription tasks that need cleaner output than casual voice notes.
This product page focuses on what users actually care about: accurate speech recognition, stable results on noisy audio, practical language support, and a workflow that turns audio files into usable text.
Performance
Built for challenging recordings
A strong transcription product has to handle real audio, not just clean demos. MAI-Transcribe-1 is especially relevant for recordings with background noise, low-quality capture, mixed accents, and overlapping speech.
That makes it a strong fit for meetings, support calls, live recordings, interviews, subtitles, and archive processing where audio quality is inconsistent.
Languages
Multilingual speech-to-text for global use
MAI-Transcribe-1 supports 25 languages, which makes it useful for teams handling multilingual content, international operations, or mixed-language transcription workloads.
If your product or workflow depends on speech-to-text across multiple languages, MAI-Transcribe-1 gives you one model family to evaluate for both accuracy and operational consistency.
Workflow
How MAI-Transcribe-1 works
Upload your audio
Submit audio files such as MP3, WAV, or FLAC for speech-to-text processing.
Transcribe with MAI-Transcribe-1
Run the audio through MAI-Transcribe-1 for fast, accurate transcription across multilingual and noisy-audio scenarios.
Use the transcript
Turn the output into notes, captions, subtitles, searchable archives, summaries, or downstream product workflows.
Highlights
Why users choose MAI-Transcribe-1
Accurate speech-to-text output matters most when the source audio is messy, long, multilingual, or business-critical.
MAI-Transcribe-1 is relevant for users who care about transcript quality, not just model branding.
Noisy environments, low-quality recordings, and overlapping speech are core speech-to-text pain points this model is meant to address.
A strong MAI-Transcribe-1 product page should explain what the product does, which audio it handles well, and who should use it.
Accurate speech-to-text output matters most when the source audio is messy, long, multilingual, or business-critical.
MAI-Transcribe-1 is relevant for users who care about transcript quality, not just model branding.
Noisy environments, low-quality recordings, and overlapping speech are core speech-to-text pain points this model is meant to address.
A strong MAI-Transcribe-1 product page should explain what the product does, which audio it handles well, and who should use it.
FAQ
Frequently asked questions about MAI-Transcribe-1
What is MAI-Transcribe-1?
MAI-Transcribe-1 is a speech-to-text model used for turning spoken audio into text across multilingual and production-style transcription workloads.
What can MAI-Transcribe-1 transcribe?
MAI-Transcribe-1 can be used for meetings, support calls, interviews, subtitles, podcasts, training recordings, and other speech-heavy audio files.
Can MAI-Transcribe-1 handle noisy audio?
Yes. One of the key strengths associated with MAI-Transcribe-1 is handling difficult recording conditions such as background noise, low-quality audio, and overlapping speech.
How many languages does MAI-Transcribe-1 support?
MAI-Transcribe-1 is positioned around 25-language transcription support for multilingual speech-to-text use cases.
Is MAI-Transcribe-1 good for batch transcription?
Yes. MAI-Transcribe-1 is especially relevant for batch transcription workflows like subtitle creation, archive processing, and large sets of uploaded recordings.
Who should use MAI-Transcribe-1?
It is a good fit for teams and creators who need accurate speech-to-text for calls, meetings, captions, archives, customer conversations, and multilingual content.