Subanana

English Audio 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.

Seamlessly transcribe English audio into clear and organized text. 98% accuracy.

  • Google
  • Deloitte
  • dentsu
  • Manulife
  • NAVER
  • Philips
  • Amazon
  • Shopify
  • Figma
  • Coinbase
  • WPP
  • Semrush
  • Google
  • Deloitte
  • dentsu
  • Manulife
  • NAVER
  • Philips
  • Amazon
  • Shopify
  • Figma
  • Coinbase
  • WPP
  • Semrush

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.

Meetings & calls

Business teams

Summaries, decisions and action items on top of the transcript — shared while the meeting is still fresh.

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.

  1. 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.
  2. 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.
  3. 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.
  4. 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

English Audio to Text Software powered by AI in 2026

Understanding English Audio to Text: A Comprehensive Guide for Content Creators In an increasingly digital world, the demand for converting English audio to text has never been higher. Whether you're a content creator working on podcasts, a journalist handling interviews, or a corporate professional documenting meetings, transcribing audio files into text can significantly enhance accessibility and efficiency. This comprehensive guide will explore the nuances of English audio to text conversion, providing insights into its importance, challenges, and the best practices for achieving accurate transcriptions. The Importance of English Audio to Text Conversion 1. Accessibility and Inclusivity: Transcribing audio into text makes content accessible to a broader audience, including those who are hearing impaired. It also aids in reaching non-native speakers who may find it easier to comprehend written English. 2. Improved Searchability and SEO: Text content can be indexed by search engines, improving the discoverability of your content. Transcriptions can enhance SEO efforts by allowing search engines to crawl content more effectively. 3. Content Repurposing: Transcriptions can be repurposed into blogs, articles, and social media posts, maximizing the utility of a single piece of content across multiple platforms. 4. Enhanced User Engagement: Providing a text version of audio content caters to users who prefer reading over listening, potentially increasing engagement and retention. Challenges in Converting English Audio to Text Despite its benefits, converting English audio to text presents several challenges: 1. Accents and Dialects: English is spoken with diverse accents and dialects worldwide, which can complicate the transcription process. High-quality transcription tools must be equipped to handle these variations. 2. Background Noise and Audio Quality: Poor audio quality and background noise can hinder accurate transcription. Ensuring clear, high-quality recordings is crucial for effective conversion. 3. Technical Jargon and Industry-Specific Terms: Content creators often deal with niche topics that include technical jargon. A reliable transcription tool should be capable of understanding and accurately transcribing such terms. 4. Speaker Identification: In multi-speaker environments, distinguishing between different voices can be challenging yet essential for producing coherent transcriptions. Best Practices for Accurate English Audio to Text Conversion 1. Choose the Right Tools: Select a transcription tool that uses advanced AI algorithms to handle a variety of accents and dialects, offers high accuracy, and includes features like speaker identification and timestamping. 2. Optimize Audio Quality: Use high-quality recording equipment and minimize background noise to improve transcription accuracy. Consider using directional microphones and soundproofing solutions. 3. Proofread and Edit: While AI transcription tools are highly effective, manual proofreading is essential to correct any errors and ensure the accuracy and coherence of the final text. 4. Utilize Custom Dictionaries: Some transcription tools allow the creation of custom dictionaries to include specific terms and jargon, enhancing transcription accuracy. 5. Regular Updates and Training: Keep your transcription software updated to benefit from the latest advancements in AI and machine learning. Regularly train the software with new content for better accuracy. The Future of English Audio to Text Technology The future of audio to text technology is promising, with continued advancements in artificial intelligence and machine learning. Future innovations may include real-time transcription capabilities, improved context understanding, and enhanced integration with various digital platforms. As these technologies evolve, content creators are likely to experience smoother and more efficient workflows, allowing them to focus on producing high-quality content rather than the logistics of transcription. Conclusion Converting English audio to text is an invaluable process for content creators aiming to enhance accessibility, improve SEO, and repurpose content. While challenges exist, leveraging the right tools and adhering to best practices can result in highly accurate transcriptions. By staying informed about technological advancements, content creators can continue to optimize their workflows and expand their reach in an ever-evolving digital landscape.

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