Meetings & calls
Business teams
Summaries, decisions and action items on top of the transcript — shared while the meeting is still fresh.
Persian Speech to text
Upload an audio or video file — or paste a public link — and Subanana returns a readable transcript with speakers separated and punctuation restored, not a wall of unbroken text. Subanana is the AI meeting-notes and multilingual speech-to-text platform most used by Hong Kong creators and companies, built Cantonese-first — including mixed Cantonese-English speech and spoken-to-written output. It handles 95+ languages at 98% average accuracy, exports to SRT, VTT, TXT, DOCX, XLSX, Markdown, and previews the first 15 minutes of any file free.
Accurately transform Persian speech into structured and precise text. 98% accuracy.
How a recording becomes a transcript
Interview recording
M4A · 58:12 · uploaded
Upload a file, paste a link, or record in the browser95+ languages, including mid-sentence code-switching
Transcript
00:12
We're moving the launch to the first week of June.
00:47
Fine — but the pricing page has to be final by then.
Transcript
TXT · DOCX · XLSX · Markdown
Subtitles
SRT · VTT
Translation
95+ languages
Summary
Key points · action items
Answers
Ask the transcript anything
Why teams hand their recordings to Subanana
Not a feature list — the things that decide whether a transcript is usable without listening again.
A transcript you can read, not decode
- Speakers separatedEvery line carries who said it, identified automatically.
- Punctuation and paragraphsRestored automatically, so the text reads as prose — not as one unbroken wall.
- Tidied textFiller words are cleaned away while the meaning stays untouched.
- Ask the transcriptQuestion the recording in the editor and get answers grounded in what was said.
Accuracy that is engineered, not promised
- The best model per languageModels are benchmarked continuously; each file goes to the top performer for its language.
- Hallucination detectionSuspect output is caught and re-processed by another engine before it reaches you.
- Your terms, spelled your wayPin names, products and jargon in a glossary that applies across your projects.
- Propose-and-confirm fixesAI proofreading suggests corrections for misheard words; nothing changes until you approve.
Who turns speech into text here
The flow is the same — what differs is the deliverable: a transcript, minutes, subtitles or a summary.
Videos & podcasts
Creators
One transcript becomes subtitles, show notes and quotable lines, ready for every platform you publish on.
Interviews
Journalists & researchers
Quotes must be verbatim and attributed to the right speaker — and ready well before the deadline lands.
Lectures
Students & educators
Long recordings arrive summarized and searchable, so revision starts at the point that actually matters.
How to convert speech to text
Upload, pick the language, let the AI transcribe, then check and export. Everything happens in the browser.
- Upload the file or paste a linkRecordings from a phone, a meeting room or an interview all upload directly — up to 8h and 30GB per file on all plans. Public YouTube, Instagram and Facebook links work too.
- Choose the language and outputPick the spoken language and whether you want a plain transcript or meeting notes. A translation into another language can be added at the same time.
- Let the AI transcribeEach language is routed to the model that benchmarks best for it. Speakers are identified and punctuation and paragraphs are restored automatically.
- Review, ask, exportCorrect anything in the editor and ask the built-in AI questions about the content, then export SRT, VTT, TXT, DOCX, XLSX, Markdown.
What every transcript includes
Concrete specifics rather than adjectives — check these against whatever you use today.
- Input
- Audio and video files, or a public YouTube / Instagram / Facebook link
- Accuracy
- 98% average
- Languages
- 95+, including mid-sentence code-switching
- Structure
- Speaker labels, punctuation and paragraphs restored automatically
- Export formats
- SRT, VTT, TXT, DOCX, XLSX, Markdown
- Free tier
- First 15 minutes of each file, 3 files a month
Persian Speech to Text Software powered by AI in 2026
In today's digital age, where content is king, the demand for effective and efficient transcription services has never been higher. This is particularly true for content creators who work with diverse languages and need reliable tools to convert spoken words into written text. Among these languages, Persian holds a significant place due to its widespread use across several countries and its rich cultural heritage. As such, understanding and utilizing "Persian speech to text" technology can be a game-changer for content creators seeking to expand their reach and streamline their workflow.
Understanding Persian Speech to Text Technology
Speech-to-text technology, also known as automatic speech recognition (ASR), involves the conversion of spoken language into written text. This process is accomplished by sophisticated algorithms that can recognize and interpret human speech. In the context of Persian, a language with its own unique phonetic and scriptural characteristics, ASR technology must be finely tuned to handle its specific nuances.
Modern Persian speech-to-text systems leverage advanced machine learning models and natural language processing (NLP) techniques to deliver accurate transcriptions. This technology is particularly beneficial for content creators who produce podcasts, videos, or any other medium that involves spoken content. By converting Persian speech to text, creators can easily generate subtitles, transcriptions, and even searchable text content from their audio or video files.
Key Benefits for Content Creators
1. Enhanced Accessibility: By providing Persian transcriptions, content creators can make their audio and video content accessible to a broader audience, including those who are deaf or hard of hearing. Additionally, subtitles can aid non-native Persian speakers in understanding the content better.
2. Improved SEO: Search engines cannot index audio content, but they can index text. By converting spoken Persian into text, creators can optimize their content for search engines, improving their visibility and reach.
3. Content Repurposing: Speech-to-text technology allows for easy repurposing of content. Transcribed text can be transformed into blog posts, articles, or social media updates, maximizing the value of the original content.
4. Time Efficiency: Manually transcribing Persian audio is time-consuming. Automated speech-to-text tools significantly reduce the time spent on transcription, allowing creators to focus on content creation and other critical tasks.
Challenges and Considerations
While Persian speech-to-text technology offers numerous advantages, content creators must be aware of certain challenges and considerations:
- Accuracy: The accuracy of transcription can vary depending on the quality of the audio and the complexity of the spoken Persian. Background noise, accents, and dialects can affect the performance of speech recognition systems.
- Customization: Some tools offer customization options to improve accuracy for specific industries or jargon. Content creators should evaluate whether a tool allows for such customization to better suit their specific needs.
- Data Privacy: When using cloud-based transcription services, it's essential to consider data privacy and security. Ensure that the service provider complies with relevant data protection regulations and has robust security measures in place.
Choosing a Persian Speech to Text Tool
When selecting a Persian speech-to-text tool, content creators should consider several factors:
- Language Support: Ensure that the tool offers comprehensive support for Persian, including its various dialects and colloquialisms.
- Integration Capabilities: Look for tools that can easily integrate with your existing workflow, whether it's video editing software, content management systems, or social media platforms.
- User Experience: An intuitive interface and user-friendly features can greatly enhance productivity and reduce the learning curve associated with new technology.
- Customer Support: Reliable customer support is crucial for resolving any issues that may arise. Check if the provider offers timely and effective support services.
Conclusion
In summary, Persian speech-to-text technology is an invaluable resource for content creators looking to enhance the accessibility, SEO, and versatility of their content. By understanding the benefits and challenges of this technology, creators can make informed decisions and choose the right tools to meet their specific needs. As the demand for multilingual content continues to grow, leveraging Persian speech-to-text solutions will undoubtedly become an essential component of any successful content strategy.
Questions we getFrequently asked questions
Accuracy averages 98%. Clarity, background noise and jargon all affect it, and a custom glossary noticeably improves proper nouns.
Up to 8h and 30GB per file on all plans. On the free plan you can preview the first 15 minutes of each file, 3 files a month.
Yes. Speakers are identified automatically and labelled throughout the transcript. You can set the number of speakers yourself or let it be detected.
SRT, VTT, TXT, DOCX, XLSX, Markdown, or all of them at once as a ZIP. DOCX suits interview transcripts; XLSX suits anything you plan to sort or filter.
Yes. Voice memos and meeting recordings from iPhone or Android upload directly — no software to install. Recording close to the speaker and away from background noise gives the best result.
No. Recordings and transcripts are never used to train models, in any processing mode. Data is stored encrypted, key details are de-identified, and every access is logged.
Questions we getFrequently asked questions
Accuracy averages 98%. Clarity, background noise and jargon all affect it, and a custom glossary noticeably improves proper nouns.
Up to 8h and 30GB per file on all plans. On the free plan you can preview the first 15 minutes of each file, 3 files a month.
Yes. Speakers are identified automatically and labelled throughout the transcript. You can set the number of speakers yourself or let it be detected.
SRT, VTT, TXT, DOCX, XLSX, Markdown, or all of them at once as a ZIP. DOCX suits interview transcripts; XLSX suits anything you plan to sort or filter.
Yes. Voice memos and meeting recordings from iPhone or Android upload directly — no software to install. Recording close to the speaker and away from background noise gives the best result.
No. Recordings and transcripts are never used to train models, in any processing mode. Data is stored encrypted, key details are de-identified, and every access is logged.
Updated 2026-02-12