Meetings & calls
Business teams
Summaries, decisions and action items on top of the transcript — shared while the meeting is still fresh.
Persian voice 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. 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.
Quickly convert Persian voice into clear and accurate 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 Voice to Text Software powered by AI in 2026
Understanding Persian Voice to Text: A Comprehensive Guide for Content Creators
In the rapidly evolving digital landscape, the demand for efficient and accurate transcription services has skyrocketed. One area that has seen significant growth is the conversion of Persian voice to text. With the increasing need for content accessibility and the expansion of Persian-speaking audiences, content creators are seeking reliable solutions to transcribe Persian audio into text seamlessly. This blog aims to provide a comprehensive understanding of Persian voice to text, highlighting its importance, challenges, and key considerations for content creators.
The Importance of Persian Voice to Text
The Persian language, known as Farsi, is spoken by over 110 million people worldwide, with significant populations in Iran, Afghanistan, and Tajikistan. As digital content consumption grows in these regions, the need for localized content becomes imperative. Voice to text technology enables content creators to tap into this audience by providing accurate transcriptions of audio and video materials. This not only enhances content accessibility for the hearing impaired but also improves search engine optimization (SEO), making content discoverable to a broader audience.
Challenges in Transcribing Persian
Transcribing Persian voice to text presents unique challenges that are distinct from those associated with other languages. Understanding these challenges is crucial for content creators who aim to produce high-quality transcriptions.
1. Complex Script: Persian uses a modified Arabic script, which can be complex for transcription software to interpret accurately. The nuances of the script, including diacritics and ligatures, require advanced recognition capabilities.
2. Dialect Variations: Persian has several dialects, such as Tehrani, Isfahani, and Shirazi, each with its own phonetic nuances. Transcription tools must be capable of recognizing and accurately transcribing these variations to ensure precision.
3. Homophones and Contextual Ambiguity: Persian, like many languages, contains homophones—words that sound alike but have different meanings. Understanding context is essential for accurate transcription, necessitating sophisticated AI algorithms that can discern meaning from context.
Key Considerations for Content Creators
To effectively leverage Persian voice to text technology, content creators should consider the following factors:
1. Choosing the Right Software: Not all transcription software is created equal. When selecting a tool for Persian transcriptions, look for features such as advanced speech recognition, support for multiple dialects, and a robust language model. Consider platforms that offer AI-driven solutions capable of learning and adapting to improve accuracy over time.
2. Quality Assurance: Even with sophisticated technology, errors can occur. Implement a quality assurance process that involves human review to verify and correct transcriptions. This ensures the final output is accurate and reliable.
3. Integration with Existing Workflows: Choose a voice to text solution that integrates seamlessly with your existing content creation workflow. This will save time and reduce the potential for errors during the transcription process.
4. Data Security and Privacy: Ensure that the transcription service complies with data protection regulations and offers secure handling of audio files. This is particularly important when dealing with sensitive or proprietary content.
Educating Your Team
For content creators, understanding the intricacies of Persian voice to text is just the beginning. Educating your team on how to effectively use transcription tools will maximize their benefits. Provide training sessions on the software’s features and best practices for achieving high-quality transcriptions. Encourage team members to stay updated on the latest advancements in voice to text technology to continuously improve the transcription process.
The Future of Persian Voice to Text
As artificial intelligence and machine learning technologies continue to advance, the accuracy and efficiency of Persian voice to text solutions will improve. Emerging trends, such as real-time transcription and enhanced natural language processing, promise to make voice to text technology even more accessible and reliable for content creators.
In conclusion, Persian voice to text technology is an invaluable asset for content creators looking to expand their reach and improve content accessibility. By understanding the challenges and key considerations associated with this technology, content creators can produce high-quality transcriptions that resonate with Persian-speaking audiences. Embracing these tools not only enhances communication but also paves the way for a more inclusive digital experience for everyone.
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 2026-04-10