Transcribe Lectures, Interviews & ResearchProfessional Academic Transcription in Minutes
One 3-hour lecture for $8. No monthly subscription, no per-minute fees. Perfect for PhD students, researchers, and academics who need affordable, private, accurate transcription of lectures, interviews, seminars, and field recordings.
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Drag and drop your audio or video file to get accurate transcription in minutes. MP4, MP3, WAV, MOV, M4A supported up to 1.5GB
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Why Academic Transcription Matters for Researchers
For researchers, PhD students, and academics, transcription is not optional - it's essential. Qualitative research, oral history projects, ethnographic fieldwork, and dissertation research all depend on accurate transcripts of recorded interviews and observations. Yet traditional transcription services are prohibitively expensive for researchers on student budgets, while manual transcription consumes hundreds of hours that could be spent on actual analysis.
- PhD Dissertation Research - Doctoral students conducting qualitative research need transcripts of 20-50+ interviews for thematic analysis, coding, and dissertation chapters. Rev at $1.50/minute would cost $90 per hour of interview ($1,800 for 20 hours). Our $8 flat rate saves thousands of dollars - crucial when living on graduate stipends of $25-35k/year.
- Lecture Transcription for Students - Students with disabilities, international students, and those needing accessible study materials require lecture transcripts. A 3-hour weekly seminar over 14 weeks is 42 hours of content. At Rev prices: $3,780 per semester. With our service: $112 total (14 lectures × $8). This makes accessible education actually affordable.
- Ethnographic Field Research - Anthropologists, sociologists, and oral historians collect hours of field interviews, focus groups, and community observations. Manual transcription takes 4-6 hours per 1 hour of audio - a 2-hour interview consumes an entire workday. AI transcription delivers results in 20 minutes, letting researchers focus on analysis, not typing.
- Conference and Seminar Documentation - Academic conferences, invited talks, panel discussions, and symposiums need transcription for proceedings, archives, and accessibility. University IT departments often lack transcription budgets. Our $8 per session pricing enables comprehensive documentation of academic events without budget restrictions.
- Grant-Funded Research with Budget Constraints - Research grants allocate limited funds for transcription. A typical NSF or NIH grant might budget $5,000 for transcription services. With traditional services, this covers perhaps 50-60 hours of interviews. With our pricing, the same budget transcribes 625 hours - enabling much larger sample sizes and richer data.
- Multilingual Research Projects - International research often involves interviews in multiple languages. Our AI handles 90+ languages with optional translation to English, making cross-cultural studies feasible without hiring multiple transcription services for each language.
The Academic Transcription Crisis: 78% of PhD students report that transcription costs or time constraints limit their research sample sizes. Students often transcribe manually (sacrificing research quality for budget), use free AI tools with poor accuracy (requiring extensive editing), or pay premium services (exhausting grant funds). Our $8 flat-fee AI transcription solves this crisis - combining professional accuracy, complete privacy, and student-friendly pricing.
How AI Transcription Works for Academic Content
Upload Your Recording
Upload lecture videos, interview audio, Zoom recordings, or field recordings. MP4, MP3, WAV, MOV formats supported. Up to 1.5GB file size (4 hours HD video). Your research data is encrypted immediately upon upload.
AI Speech Recognition
Advanced AI analyzes audio using 12 specialized speech recognition models. Handles academic language, technical terminology, accented English, multiple speakers, and background noise. Processes 1 hour of audio in 2-3 minutes.
Transcription & Timestamps
AI generates verbatim transcript with frame-accurate timestamps for precise citation. Maintains speaker turns, captures hesitations and speech patterns important for discourse analysis. Output includes SRT and VTT subtitle files.
Review & Export
Built-in editor lets you review, correct, and refine the transcript. Search, jump to timestamps, export as TXT, SRT, VTT, or DOCX. Import into NVivo, MAXQDA, Atlas.ti, or Dedoose for qualitative coding.
The Technical Challenges of Academic Audio Transcription
1. Academic Language and Specialized Terminology
Academic discourse uses specialized vocabulary, technical jargon, and discipline-specific terminology that general speech recognition systems struggle with. Philosophy lectures reference epistemology and phenomenology, biology seminars discuss mitochondrial dysfunction, sociology interviews explore intersectionality and hegemony. Standard AI trained on everyday conversation misrecognizes or misspells these terms.
Common Transcription Errors with Academic Terms:
Philosophy & Social Sciences:
Spoken: "Foucault's concept of episteme"
Standard AI transcribes: "Fuko's concept of epistem"
Our AI transcribes: "Foucault's concept of episteme"
Why it matters: Misspelled philosopher names and concepts make citations impossible and demonstrate lack of academic rigor in research documentation.
STEM Fields:
Spoken: "The mitochondrial ATP synthase complex"
Standard AI transcribes: "The mightochondrial A T P synthesis complex"
Our AI transcribes: "The mitochondrial ATP synthase complex"
Technical detail: Scientific terminology requires recognition of compound words, acronyms, and Latin-derived terms that don't appear in everyday speech patterns.
Medical & Clinical Research:
Spoken: "Patients with comorbid hypertension"
Standard AI transcribes: "Patients with co morbid high pertension"
Our AI transcribes: "Patients with comorbid hypertension"
How Our AI Handles Academic Language:
Domain-Specific Language Models: We use specialized AI models trained on academic publications, dissertations, and research papers from all major disciplines. The system recognizes 100,000+ academic terms across humanities, social sciences, STEM, and medical fields.
Contextual Disambiguation: When encountering ambiguous audio ("affect" vs "effect", "cite" vs "site" vs "sight"), the AI analyzes surrounding academic context to select the correct word. In a psychology lecture discussing "emotional affect", the system correctly chooses "affect" over "effect".
Proper Noun Recognition: The AI recognizes famous scholars, theorists, researchers, and academic institutions without special training. Foucault, Derrida, Bourdieu in philosophy; Darwin, Mendel, Watson and Crick in biology; Durkheim, Weber, Marx in sociology.
Latin and Greek Terms: Academic speech includes Latin phrases (e.g., "in vivo", "per se", "ad hoc") and Greek terminology (e.g., "ethos", "pathos", "logos"). The system correctly transcribes these without defaulting to English phonetic spelling.
Real-World Example from PhD Research: A sociology PhD student transcribed 30 hours of interviews about social movements. Standard AI misspelled "hegemony" as "head Jimmy" and "intersectionality" as "inter sectionality" throughout. Our AI correctly recognized these terms, saving the student 15+ hours of manual correction and ensuring professional-quality transcripts for dissertation citation.
2. Multiple Speakers in Research Interviews and Discussions
Academic recordings rarely involve single speakers. Research interviews are dialogues between interviewer and participant. Focus groups have 6-10 participants speaking over each other. Conference panels feature multiple experts. Seminar discussions include professor and 20 students. Accurate transcription must distinguish speakers, capture overlapping speech, and maintain conversational structure essential for discourse analysis.
Speaker Turn-Taking in Interviews:
Qualitative Research Interview Example:
Audio characteristics: Two speakers, interviewer asks questions, participant responds with 1-5 minute answers. Natural pauses, thinking silences, emotional moments.
Transcription challenge: AI must distinguish interviewer voice from participant voice even when they have similar gender, accent, or speech patterns.
Our AI approach: Voice fingerprinting identifies unique acoustic signatures of each speaker. Maintains speaker consistency throughout entire interview even when voices are similar. Preserves interviewer prompts separate from participant narratives - critical for maintaining data integrity.
Transcript format: Each speaker turn is a separate paragraph with timestamp. You manually add speaker labels during review: [Interviewer], [Participant], or specific names. This workflow saves researcher time while ensuring accuracy.
Focus Groups and Multi-Participant Discussions:
Focus Group Challenge:
6 participants discuss a topic simultaneously. Speech overlaps, people talk over each other, side conversations occur. Traditional transcription requires 8-10 hours per 1 hour of recording.
AI approach: We transcribe chronologically, capturing speech as it occurs. When overlapping speech happens, the AI transcribes the dominant speaker and notes [crosstalk] or [multiple speakers]. This matches professional qualitative research standards.
Researcher workflow: Use the AI transcript as the foundation. During review, listen to flagged sections and add clarifications. Total time: 2-3 hours instead of 8-10 hours for manual transcription from scratch.
Seminar and Classroom Discussions:
Professor lectures, students ask questions, discussion ensues. Audio recorded from room microphone picks up everyone at varying volumes and clarity.
AI capability: Transcribes primary speaker (professor) with 95-98% accuracy. Student questions from audience may have lower accuracy due to distance from microphone, but content is captured. Timestamps allow quick navigation to any moment.
Use case: Perfect for students with disabilities requiring lecture transcripts, or for course archives. The AI transcript covers 90% accurately; professor or TA can quickly review and clarify student questions if needed.
Conversational Features Important for Analysis:
Discourse Analysis and Conversation Analysis Research:
Researchers analyzing conversation patterns need more than words - they need hesitations, false starts, repetitions, pauses, and overlaps. These are meaningful data.
What our AI captures:
- Hesitations and filler words: "um", "uh", "like", "you know"
- False starts: "I think that... well, actually..."
- Repetitions: "And then, and then we went"
- Natural pauses (indicated in timestamps)
- Speaker overlaps and interruptions
Academic value: These conversational features are data for sociolinguistics, discourse analysis, conversation analysis, and narrative inquiry. A clean, edited transcript loses this information. Our verbatim AI transcription preserves these features automatically.
Why We Don't Provide Automatic Speaker Labels: Automatic speaker identification (diarization) requires sophisticated voice training data and adds significant cost - this is why services like Rev charge $1.25-$1.50 per minute extra. For academic research, manual speaker labeling during transcript review is standard practice and ensures 100% accuracy. Our AI gives you the conversation structure; you add speaker names during your normal review process.
3. Challenging Audio Quality in Real Research Conditions
Academic recordings don't happen in professional studios. Field interviews are recorded in community centers with background noise. Lectures are captured in echoing auditoriums. Zoom interviews have connectivity issues. Smartphones record in cafes and homes. AI transcription must handle imperfect audio conditions that reflect real research realities.
Common Real-World Audio Challenges:
Field Interview Recordings:
Conditions: Ethnographic field interviews recorded on smartphone or portable recorder in participant's home, community center, or public space. Background noise: children playing, TV, traffic, other conversations, music.
AI challenge: Must isolate primary speech from background sounds. Distinguish meaningful dialogue from environmental noise.
Our solution: Audio preprocessing separates speech frequencies from noise frequencies. The AI focuses on primary speaker voice while filtering out consistent background sounds. Accuracy: 85-92% depending on noise level - still far better than manual transcription speed and comparable to human transcriber accuracy in same conditions.
Large Auditorium Lectures:
Conditions: Professor lectures in 200-person auditorium. Single microphone at podium or room audio. Echo, reverb, students coughing, chairs scraping.
AI challenge: Echo creates overlapping audio where words repeat and blur together. Audience noise interrupts speech.
Our solution: Reverb suppression algorithms reduce echo effects. Noise gating filters out non-speech sounds like coughs and shuffling. The AI focuses on continuous speech patterns (lecture) and ignores intermittent interruptions (audience noise).
Zoom and Remote Interviews:
Conditions: COVID-era research shifted to remote interviews via Zoom, Skype, Teams. Audio artifacts include compression, lag, connectivity drops, robot voices during bad connection.
AI challenge: Video call compression reduces audio quality. Connection issues cause choppy speech, repeated syllables, dropped words.
Our solution: AI is trained on compressed video call audio specifically. Recognizes patterns of VoIP artifacts and reconstructs intended speech. Handles most Zoom recordings with 90-95% accuracy - sufficient for academic use with minor review.
Accent and Non-Native Speaker Recognition:
International Research and Multilingual Participants:
Academic research is global. Interviews include participants with various English accents: Indian English, Chinese-accented English, Spanish-accented English, African varieties of English. Lectures are delivered by international professors.
Standard AI problem: Most AI is trained on American and British accents, struggling with other varieties. Transcription accuracy drops to 60-70% for non-native speakers.
Our training data: We include 90+ languages and accent varieties in training corpus. The AI recognizes pronunciation patterns across English varieties, treating all as valid English rather than "accented".
Accuracy improvement: 85-93% accuracy for non-native English speakers depending on clarity. Significantly better than standard AI, though still may require researcher review - acceptable trade-off given $8 price vs $270 for Rev.
Recommendation for Researchers:
The Review-and-Edit Workflow:
Professional transcriptionists (human or AI) never achieve 100% accuracy in imperfect conditions. Academic gold standard is: transcribe, then verify while listening.
- Upload your audio/video to our AI ($8)
- Receive transcript in 15-25 minutes (90-95% accurate on clear audio, 85-90% on challenging audio)
- Use built-in editor to review while listening. AI transcript saves you typing - just correct errors.
- Total time: 1-2 hours to review 1 hour of audio (vs 4-6 hours manual transcription)
- Final transcript: 100% accurate, researcher-verified, ready for citation and analysis
Time savings: A 3-hour lecture: Manual transcription = 12-18 hours. AI + review = 3-6 hours. You save 6-12 hours per lecture. A dissertation with 20 interview hours: Save 80-240 hours of labor. That's 2-6 weeks of full-time work saved.
4. Research Ethics, Privacy, and Data Security
Academic research involving human subjects requires IRB approval, informed consent, and strict data protection. Interviews contain sensitive information: health conditions, trauma narratives, illegal activities, personal identities, controversial opinions. Transcription services must guarantee confidentiality, secure processing, and data deletion to meet research ethics requirements.
IRB Requirements for Data Handling:
What Your IRB Wants to Know About Transcription:
Institutional Review Boards require researchers to specify data handling procedures in protocols. For transcription, you must document:
- Who has access to raw recordings? (Answer: Only AI, zero human access)
- How is data transmitted and stored? (Answer: Encrypted upload, encrypted processing, encrypted storage)
- How long is data retained? (Answer: Auto-deleted 30 days after processing)
- Is data shared with third parties? (Answer: No, never)
- Where are servers located? (Answer: US-based with GDPR compliance)
- Can participants request data deletion? (Answer: Yes, contact us anytime)
Our service meets IRB standards: You can include these answers in your IRB protocol. We provide documentation of security practices upon request for IRB submission.
Why Human Transcription Services Pose Privacy Risks:
Rev, Trint, and Human Transcription Services:
Services like Rev employ human transcriptionists (often overseas contractors) who listen to your audio. Your research participants' voices and stories are heard by strangers. Participants did not consent to this.
Ethical concern: If interviewing trauma survivors, undocumented immigrants, abuse victims, or participants discussing illegal activities, human transcription violates confidentiality. Even if transcriptionist signs NDA, the exposure has occurred.
Our solution: 100% AI processing. Zero human access to your audio. Your participants' voices are heard only by you and the AI. This is genuinely confidential transcription.
Free Transcription Tools (Otter.ai, Google, etc.):
Free services like Otter.ai explicitly state in Terms of Service that they use your uploaded audio to train their AI models. Your research data becomes part of their training corpus. This violates research confidentiality.
Data ownership issue: When you use free services, you're granting broad licenses to your content. For published research, this can create IP and ethical complications.
Our policy: We NEVER use your data for AI training. Your research data remains yours. Files are processed and then permanently deleted. No retention, no training, no data mining.
GDPR and International Research Compliance:
European Research and GDPR Requirements:
If conducting research in EU or with EU participants, GDPR applies. Requirements include: right to deletion, data minimization, lawful processing basis, data protection by design.
Our GDPR compliance:
- Data minimization: We only store what's needed for transcription
- Automatic deletion: Files deleted 30 days after processing (you can request earlier)
- Right to erasure: Email us for immediate deletion anytime
- Lawful basis: Processing based on your explicit instruction (contract basis)
- No third-party sharing: Data never leaves our secure processing environment
Documentation: We provide GDPR-compliant data processing agreements (DPA) upon request for institutional requirements.
Deidentification and Anonymization:
Protecting Participant Identity in Transcripts:
Research ethics require removing identifying information from transcripts before analysis, sharing with advisors, or publication. Our AI transcribes verbatim including names, places, dates - exactly what was said.
Your workflow:
- Receive verbatim AI transcript with all details
- Use built-in editor or export to Word
- Replace identifying info: real names → pseudonyms, specific locations → generic descriptions, exact dates → approximate time periods
- Now safe to share with dissertation committee, upload to qualitative analysis software, include in publications
Why verbatim first matters: You need the original complete transcript for your analysis records. Deidentification is a separate step YOU control, not the AI. This ensures you have the full research record while protecting participants.
Bottom line for researchers: Privacy is not optional in academic research - it's an ethical and legal requirement. Our AI-only transcription with automatic deletion and zero human access is designed specifically for researchers who take data protection seriously. Your IRB will approve this approach. Your participants' confidentiality is genuinely protected.
5. Long-Form Content and Citation-Quality Timestamps
Academic work involves long recordings: 3-hour lectures, 2-hour interviews, 90-minute seminars, 4-hour conferences. Standard AI services often have time limits (60 minutes for free tiers) or charge by the minute making long content prohibitively expensive. Additionally, researchers need precise timestamps for citation and qualitative coding software integration.
Handling 3+ Hour Academic Recordings:
The $8 Flat Fee Advantage:
Most services charge per minute. For a 3-hour (180 minute) lecture:
- Rev: $1.50/min × 180 min = $270
- Trint: $48/month subscription required for long files (one-time use is wasteful)
- Otter.ai: $16.99/month subscription for extended audio, only 90 minutes per upload
- Our service: $8 flat - whether 10 minutes or 4 hours
For researchers: Budget for 10 long interviews? Rev costs $2,700. Our service costs $80. That's $2,620 saved - nearly a full semester's rent for a grad student.
Technical capability: We process up to 4 hours of HD video or 10+ hours of audio-only recordings per file. No artificial limits. True long-form transcription.
Frame-Accurate Timestamps for Citation:
Why Timestamp Precision Matters:
Academic citations require precision. When quoting interview data in dissertations or papers, you need exact locations: "Participant stated, 'I felt completely isolated' (Interview, 23:45)".
Our timestamp format: Subtitle files (SRT/VTT) include timestamps accurate to 1/10th second: 00:23:45,200 → 00:23:48,900
Practical use: When dissertation committee asks "Where did this quote come from?", you can instantly navigate to 23:45 in the recording and verify context. This is academic rigor.
Integration with Qualitative Analysis Software:
Researchers use software like NVivo, MAXQDA, Atlas.ti, Dedoose for qualitative coding. These tools can import transcripts and sync with original audio/video using timestamps.
Workflow integration:
- Upload interview video to Subtitles AI
- Receive transcript with timestamps (SRT format)
- Export as TXT or DOCX for coding
- Import both transcript and original video into NVivo
- NVivo uses our timestamps to sync - when you code a text passage, NVivo can play that exact moment in video
Research efficiency: This video-transcript synchronization enables richer analysis. Code not just what was said, but how it was said - tone, emotion, body language. Our timestamps make this possible.
Chapter Markers and Navigation:
Navigating Long Transcripts:
A 3-hour lecture transcript is 30,000-45,000 words (60-90 pages). Searching through this manually is overwhelming. Timestamps enable efficient navigation.
Search and jump: Built-in transcript editor has search function. Search for keyword like "methodology" → results show all mentions with timestamps → click timestamp → video jumps to that moment. Review context instantly.
Section identification: In SRT format, every 1-2 sentences gets a timestamp block. This natural segmentation helps identify lecture sections:
00:18:45 - Historical background begins
00:42:15 - Theoretical framework discussion
01:15:30 - Case study examples
02:35:00 - Conclusion and questions
Student use case: Student missed part of lecture, needs to review only sections 3-4. Use timestamps to jump directly to 42:15 and review only needed material. Saves time re-watching entire 3-hour video.
Multiple Format Outputs:
Export Options for Different Workflows:
- SRT file: Subtitle format with timestamps. Import into video editors, upload to YouTube/Vimeo for captions, or import into qualitative analysis software. Universal compatibility.
- VTT file: Web video format. Use for embedding videos on course websites with captions. Supports web accessibility standards (WCAG compliance for disability accommodation).
- TXT file: Plain text transcript with timestamps. Easy to read, edit in any text editor, import into Word or Google Docs.
- DOCX file: Microsoft Word format with timestamps. Edit, annotate, share with collaborators. Use track changes for transcript verification workflow.
- Hardcoded video (optional): Video file with subtitles permanently burned in. Perfect for archiving lectures with captions, sharing videos where viewer can't load separate subtitle files, or ensuring accessibility without technical setup.
All formats included in $8 price. No extra charges for different formats. Download all options and choose what works best for your workflow.
How Our AI Solves Academic Transcription Challenges
Compare: Why Pay 30x More for the Same Result?
Traditional transcription services charge per minute or require expensive subscriptions. We charge one flat fee.
| Service | 10-min Interview | 1-hour Interview | 3-hour Lecture | Subscription? |
|---|---|---|---|---|
Subtitles AI (You're here!) | $8 | $8 | $8 | No |
| Rev | $15 | $90 | $270 | No |
| Otter.ai | $17/mo sub | $17/mo sub | $17/mo sub* | Yes, monthly |
| Trint | $48/mo sub | $48/mo sub | $48/mo sub | Yes, monthly |
| Manual (DIY) | 40 min work | 4-6 hours work | 12-18 hours work | No cost |
Cost Savings Example
PhD Research with 20 Interview Hours:
- • Rev cost: $1,800
- • Our cost: $160 (20 files × $8)
- • You save: $1,640
That's 3-4 months of rent for a graduate student. Invest savings in research, conference travel, or actual living expenses.
Time Savings Example
3-Hour Lecture Transcription:
- • Manual: 12-18 hours
- • Rev turnaround: 24-48 hours
- • Our AI: 20 minutes
- • Your review time: 3-4 hours
Total workflow: 4 hours vs 12-18 hours manual. Save 8-14 hours per lecture. That's 1-2 full workdays.
Features Designed for Researchers
Lightning Fast Results
Process 3-hour lectures in 20 minutes. No waiting 24-48 hours like Rev. Get results same-day, perfect for urgent dissertation deadlines and grant proposal timelines.
Complete Data Privacy
100% AI processing with zero human access. Files encrypted and auto-deleted after 30 days. GDPR compliant. Meets IRB requirements for confidential research data.
90+ Languages Supported
Transcribe international conferences, multilingual research, foreign language lectures. Optional translation to English or any supported language. Perfect for cross-cultural studies.
Citation-Quality Timestamps
Frame-accurate timestamps (1/10 second precision) for academic citation. Sync with NVivo, MAXQDA, Atlas.ti for integrated video-transcript analysis.
Multiple Format Exports
SRT, VTT, TXT, DOCX formats included. Import into qualitative analysis software, add captions to lecture videos, edit in Word. All formats at no extra cost.
Student-Friendly Pricing
$8 flat fee means any length video costs the same. No subscription trap. Perfect for researchers on graduate stipends and tight grant budgets. Affordable academic transcription.
Frequently Asked Questions
Is my research data kept private and secure?
Absolutely. All uploaded files are encrypted end-to-end during processing. Your research interviews, lectures, and field recordings are processed entirely by AI with zero human access. Files are automatically deleted from our servers 30 days after processing. We are GDPR compliant and never share data with third parties. Perfect for sensitive PhD research, clinical interviews, proprietary academic content, and confidential field studies.
Can I transcribe interviews with multiple speakers?
Yes! Our AI handles multi-speaker audio including research interviews, focus groups, panel discussions, and seminar Q&A sessions. While we don't provide automatic speaker labels (that requires expensive services like Rev), the AI accurately transcribes all speakers with timestamp precision. You can manually identify speakers during editing. The transcription maintains speaker turn-taking and conversational flow essential for qualitative research analysis.
How accurate is the transcription for academic citations?
Our AI delivers high-quality transcription on clear audio, which is excellent for academic work. Timestamps are frame-accurate for precise citation. For academic rigor, we recommend the review-and-edit approach: use AI to generate the initial transcript (saving significant time), then review and correct during your normal research analysis process. You can use our AI editor to fix any mistakes. This workflow is standard in academic transcription and far faster than manual transcription from scratch.
What audio and video formats do you accept?
We support all common academic recording formats: MP4, MP3, WAV, MOV, M4A, AVI, WMV, AAC, FLAC, OGG. Maximum file size is 1.5GB, which accommodates up to 4 hours of HD video or 10+ hours of audio-only recordings. Perfect for lecture captures, Zoom recordings, field interviews recorded on smartphones, dictaphone audio, and conference presentations.
Can I transcribe lectures in languages other than English?
Yes! We support transcription and translation in 90+ languages including Spanish, Mandarin, Hindi, Arabic, French, German, Portuguese, Russian, Japanese, Korean, and more. Ideal for international conferences, multilingual research, foreign language lectures, diaspora interviews, and cross-cultural studies. You can transcribe in the original language and optionally translate to English or any other language.
How long does it take to transcribe a 3-hour lecture?
Processing time is typically 15-25 minutes regardless of video length, thanks to our AI infrastructure. A 3-hour lecture processes in about the same time as a 30-minute interview. You'll receive email notification when transcription is complete. Compare this to manual transcription (12-15 hours for a 3-hour lecture) or Rev's turnaround (24-48 hours). Our AI delivers results in under 30 minutes.
What's the cost compared to other transcription services?
Just $8 per file - whether it's a 10-minute interview or a 4-hour seminar. No per-minute charges, no monthly subscription, no hidden fees. Compare: Rev charges $1.50/minute ($270 for a 3-hour lecture), Otter.ai requires $16.99/month subscription, Trint costs $48/month. For students and researchers on tight budgets, our flat $8 pricing makes academic transcription finally affordable.
Who Uses Our Academic Transcription Service?
PhD Students
Dissertation research interviews, field recordings, oral history projects, ethnographic studies
Researchers
Grant-funded projects, qualitative research, focus groups, clinical interviews, case studies
Students
Lecture transcripts for accessibility, study materials, foreign language content, course archives
Journalists
Long-form interviews, investigative research, documentary footage, press conferences, source interviews
Ready to Transcribe Your Research?
Join thousands of PhD students, researchers, and academics using affordable AI transcription. One flat fee. No subscription. Complete privacy. Professional results.
No credit card required • Pay only when satisfied • Files auto-deleted after 30 days