Layanan Transkripsi Podcast

Ubah episode podcast Anda menjadi transkrip yang dapat dicari, catatan acara, dan konten blog. VexaScribe mentranskripsi podcast dengan deteksi pembicara, stempel waktu, dan ekspor untuk menggunakan kembali konten audio Anda.

Tidak perlu kartu kreditDeteksi pembicara termasukEkspor SRT/VTT untuk subtitle

Format yang didukung:

MP3WAVM4AFLACMP4MOV

The short answer

Upload your podcast episode (audio or video, up to 5 GB / ~6 hours) to VexaScribe and get a multi-speaker transcript with timestamps in ~10 minutes per hour of audio. Speaker labels work best for 2–4 voices. Per-hour cost ranges from $0.20 on Studio ($20/mo) to $0.60 on Starter ($2/mo); first 30 minutes free on signup.

Other tools worth knowing about: Descript if you also want a podcast EDITOR in the same tool (different product category — they own that). Riverside if you also need to record remote interviews ($24+/mo bundles both). Rev human transcription for ~99% accuracy if you can afford ~$90/episode for legal/journalism-grade work. Whisper local install if you have a GPU and want $0 unlimited.

Are You Transcribing Your Own Podcast or Researching Someone Else's?

These are two fundamentally different jobs — most transcription guides treat them as one. The output you want and the workflow that follows depend on which side you're on.

🎙️ My own podcast

You record episodes and need transcripts as raw material for downstream content.

  • Show notes for your website (curated highlights + chapter timestamps)
  • Blog post version of the episode (SEO + new audience)
  • Quote extraction for Twitter/LinkedIn/email newsletter
  • Searchable archive across episodes (find “harassment policy” across 100 episodes)
  • Accessibility (~15% of US adults have some hearing loss per CDC)

🔍 Someone else's podcast

You're researching, analyzing, or sourcing material from episodes you didn't produce.

  • Academic research (qualitative analysis of media content)
  • Journalism (sourcing quotes from on-the-record podcast interviews)
  • Competitive intelligence (tracking what executives say on their own pods)
  • Brand mention tracking (where is your company being discussed?)
  • Sentiment analysis at scale across an industry's podcasts

For personal research, journalism, and academic use, transcribing someone else's podcast is generally fair use. For commercial republishing of the transcript, get permission from the creator.

Show Notes vs Transcript vs Summary (Three Different Outputs)

These three terms get used interchangeably but mean different things. Knowing which one you need saves time and produces better results.

OutputTypical length (1-hr episode)Used forWho creates it
📄 Transcript8,000–15,000 words (literal text)SEO publishing, accessibility, research, content repurposingVexaScribe (AI transcribes audio → text)
📝 Show notes300–800 words (curated)Episode description, listener navigation, link sharingYou (writing from the transcript) or AI assistant
📋 Summary100–400 words (5-10 bullet points)Email teaser, social caption, executive briefingAI summary feature (built on top of the transcript)

VexaScribe produces the transcript as raw material. For AI-generated summaries on top, see our transcript-to-summary tool. Show notes are something you (or an AI assistant) write FROM the transcript — the transcript is the raw material; show notes are the polished deliverable.

Why Publish Transcripts? The SEO Case Most Podcasters Miss

⚡ The honest math

Podcast audio is invisible to Google search by default. The only thing search engines can index is your episode title and description (usually 100–300 words). A 1-hour interview contains 8,000–15,000 words of indexable content if you publish the transcript. That's 30–100× more search surface per episode.

Pacific Content and Edison Research have repeatedly documented measurable organic search growth from publishing podcast transcripts:

  • 2–5× organic search traffic for shows that publish full transcripts vs audio-only over 6–12 months
  • Long-tail keyword discovery — listeners find episodes through unrelated searches because their specific topic was discussed mid-episode
  • Accessibility audience expansion — the CDC estimates ~15% of US adults have some hearing loss; deaf and hard-of-hearing readers are an underserved market
  • International audience — transcripts can be machine-translated; audio can't (easily). Multi-language transcripts open non-English audiences
  • AI training data exposure — ChatGPT, Claude, Perplexity cite transcribed content; audio is invisible to them

Source: Pacific Content's research on podcast SEO; Edison Research's annual “Infinite Dial” and “Podcast Consumer” reports; CDC hearing loss statistics. Treat the 2–5× range as directional — your actual lift depends on episode topic, niche competition, and on-page SEO basics (H2 structure, internal linking, schema markup).

Multi-Host Accuracy — The Honest Reality

Speaker diarization (auto-detecting who said what) is hard. Marketing copy usually says “automatic speaker detection” without telling you how it actually performs at scale. Realistic accuracy from Whisper-based diarization (which VexaScribe uses):

Speaker countTypical formatRealistic label accuracy
2 speakersSolo host + 1 guest (most common interview format)95%+
3–4 speakersCo-hosts + 1–2 guests90–95%
5–6 speakersPanel discussions, roundtables80–90%
7+ speakersChaotic panels, town hallsManual review needed

Hardest cases for any tool (including ours):

  • Same-gender voices with similar vocal range and tone
  • Overlapping speech (people talking over each other)
  • Remote-recorded guests with very different audio quality from host
  • Background music or sound effects bleeding into voice tracks

Best practice for podcasters: after the first transcription pass, rename “Speaker 1”, “Speaker 2” → actual host and guest names. Save the named pattern as a template for future episodes with the same hosts. See our guide to Whisper diarization for technical depth.

Handling Long Episodes (1, 2, 3+ Hours)

Long-form has become standard — Joe Rogan, Tim Ferriss, Lex Fridman, Acquired, Conan O'Brien all run 2–4+ hour episodes regularly. Most free transcription tools cap at ~25 MB (roughly 30 minutes of audio) and break on long-form. VexaScribe processes long episodes as a single file with no splitting.

Episode lengthMP3 size (128 kbps)Processing timeFits VexaScribe's 5 GB cap?
1 hour (typical interview)~55 MB~5–10 min✓ Easily
2 hours (deep-dive interview)~110 MB~15–20 min✓ Easily
3 hours (Rogan-format)~165 MB~25–30 min✓ Easily
4–6 hours (rare deep-dives)~220–330 MB~35–60 min✓ Yes

For video podcasts (1080p MP4), file sizes are 5–10× larger — a 3-hour video podcast can hit 1–3 GB. Still under the 5 GB cap, but if your video podcast routinely runs longer than 6 hours, consider compressing to 720p with Handbrake first (audio quality is what matters for transcription, not visual resolution).

Repurposing Playbook — One Transcript → Five Derived Outputs

The leverage of a podcast transcript is downstream content. Here are five concrete derived outputs from one 1-hour episode transcript, with realistic effort estimates.

1. SEO blog post

Transcript → AI-generated outline → manual polish → publish on your podcast site. ~1 hour of editing work per episode. Captures search traffic the audio alone can't.

2. Email newsletter teaser

Extract 3–5 best quotes + 2-paragraph hook from the transcript. Send to your list with a link to the full episode. ~20 minutes per episode.

3. Twitter/X thread

10–15 quote tweets from the most insightful moments. Each tweet links back to the episode timestamp. Drives social discovery for free. ~30 minutes per episode.

4. YouTube Shorts / TikTok / Reels clips

Timestamped transcript makes clip identification fast — find the 30–60-second moments worth standalone shorts. Each short captioned with VexaScribe's SRT export. ~1 hour per episode for 3–5 clips.

5. LinkedIn post (B2B podcasts)

1–2 minute video clip + key quote + call-to-action. B2B podcasts especially benefit from LinkedIn distribution where the buyer audience lives. ~30 minutes per episode.

Total derived content from one transcript: roughly 3–4 hours of post-production work yielding 5+ pieces of content across as many channels. The transcript is the bottleneck unlock — you can't do any of this efficiently without one.

Gunakan Kembali Konten Podcast Anda

Satu transkrip, banyak konten. Maksimalkan nilai setiap episode.

Catatan Acara

Buat ringkasan episode detail

Posting Blog

Ubah episode menjadi artikel tertulis

Kutipan Sosial

Ekstrak kutipan yang dapat dibagikan dengan stempel waktu

Subtitle YouTube

Ekspor file SRT untuk versi video

Konten SEO

Buat episode dapat dicari di Google

Dari Transkrip ke Catatan Acara

Before

Pembawa Acara: Selamat datang di podcast Tech Talk. Saya bersama Sarah Chen. Narasumber: Terima kasih telah mengundang saya. Saya senang membahas tren AI hari ini. Pembawa Acara: Mari kita mulai. Perubahan terbesar apa yang Anda lihat? Narasumber: Pasti peralihan dari hype ke aplikasi praktis.

After

## Poin Utama • Diskusi tren AI • Aplikasi praktis vs hype ## Stempel Waktu 0:00 - Pendahuluan 0:15 - Diskusi utama

Kompatibel

Buzzsprout
Anchor
Spotify
YouTube

Transkripsi Podcast: DIY vs VexaScribe

Transkripsi Manual

  • 4-6 jam untuk episode 1 jam
  • Tanpa label pembicara otomatis
  • Input stempel waktu manual
  • Mahal jika di-outsource
  • Menunda penggunaan ulang konten

Terbaik untuk: Perfeksionis dengan banyak waktu

Menggunakan VexaScribe

  • 5-10 menit untuk episode 1 jam
  • Label host/narasumber otomatis
  • Stempel waktu dihasilkan
  • Mulai dari $0.20 per jam audio
  • Publikasikan catatan acara di hari yang sama

Terbaik untuk: Podcaster yang menerbitkan setiap minggu

Cara Kerja Transkripsi Podcast

Unggah Episode Anda

Unggah file audio atau video podcast Anda. Kami mendukung MP3, WAV, M4A, MP4, dan lainnya. Bekerja dengan ekspor dari platform hosting podcast mana pun.

AI Memberi Label Pembicara

AI kami mentranskripsi episode Anda dan secara otomatis mendeteksi pembicara berbeda—sempurna untuk membedakan host dari narasumber dalam wawancara.

Ekspor dan Gunakan Kembali

Unduh transkrip sebagai teks untuk catatan acara, DOCX untuk posting blog, atau SRT/VTT untuk subtitle YouTube. Satu rekaman, banyak konten.

Transkripsi Podcast Terjangkau

Transkripsi episode dengan sebagian kecil biaya layanan profesional.

Bayar hanya untuk menit yang digunakan

Mengapa Podcaster Memilih VexaScribe

Fitur yang dibuat khusus untuk alur kerja podcast

Deteksi Pembicara

Bedakan host dan narasumber secara otomatis. Memudahkan atribusi catatan acara dan kutipan dengan benar.

Siap untuk Catatan Acara

Ekspor transkrip yang diformat untuk konversi mudah ke catatan acara, ringkasan episode, dan konten blog.

Stempel Waktu Siap Kutip

Setiap kalimat memiliki stempel waktu. Tarik kutipan dengan waktu yang tepat untuk audiogram dan klip sosial.

Subtitle YouTube

Ekspor file SRT/VTT untuk video podcast Anda. Unggah langsung ke YouTube atau tambahkan ke editor video.

Publikasi Hari yang Sama

Transkripsi dan publikasikan catatan acara di hari yang sama Anda merekam. Tidak ada lagi penumpukan transkrip.

Audiens Internasional

Transkripsi dalam 99 bahasa. Jangkau pendengar global dengan transkrip multibahasa yang akurat.

FAQ Transkripsi Podcast

Bagaimana cara membuat show notes dari transkrip?

Workflow umum: (1) Upload episode → transkrip selesai, (2) Skim transkrip untuk identifikasi 5–10 topik utama dan quote menarik, (3) Tulis ringkasan singkat dengan timestamp navigasi ("05:23 – Cara memulai karir di tech"), (4) Publish bersama episode di Spotify, Anchor, blog, atau platform podcast Anda. Untuk podcaster yang volume tinggi, fitur AI Summary di paket berbayar bisa membantu menggenerate draft show notes.

Apakah AI bisa membedakan host dan beberapa tamu?

Ya, deteksi pembicara mendukung 2–4 pembicara dengan akurasi tinggi. Untuk panel discussion dengan 5–8 tamu, akurasi pemisahan menurun tetapi masih membantu. Tip: pastikan setiap pembicara punya mikrofon sendiri jika memungkinkan — audio yang dipisah per track jauh lebih akurat dibanding satu rekaman gabungan.

Bagaimana dengan intro musik dan jingle?

AI akan mencoba mentranskripsi lirik jika ada vokal di musik. Untuk intro/outro yang murni instrumental, AI biasanya skip atau tulis "[musik]". Tip: jika intro musik Anda panjang (>30 detik) dan akurasi penting, pertimbangkan memotong intro sebelum upload untuk hemat biaya dan hasil lebih bersih.

Apakah cocok untuk podcast dengan format wawancara?

Sangat cocok — ini salah satu use case paling kuat. Deteksi pembicara secara otomatis memisahkan pewawancara dan narasumber, dengan label yang bisa Anda rename di editor. Hasilnya: format Q&A yang siap untuk show notes, blog wawancara, atau quote highlights.

Berapa biaya transkripsi untuk podcaster mingguan?

Untuk podcaster yang upload 1 episode 60 menit/minggu (4 episode/bulan = 240 menit): paket Starter $2/bulan (~Rp 32.000) untuk 200 menit cukup tipis — pertimbangkan Basic $5/bulan untuk 1.000 menit. Untuk podcast harian atau dengan banyak episode panjang, Pro $10/bulan untuk 2.500 menit memberi banyak headroom.

Apakah ada API untuk integrasi dengan workflow saya?

NovaScribe fokus pada interface web saat ini. Untuk podcaster yang ingin automate workflow lengkap (RSS feed → transkrip → blog publish), Anda bisa mengkombinasi dengan tools seperti Zapier/Make.com pada level upload + ekspor.

Apakah saya bisa mentranskripsi podcast orang lain?

Untuk penggunaan personal (catatan, kutipan dengan atribusi, belajar bahasa): umumnya diterima sebagai fair use. Untuk konten yang akan dipublikasikan: pertimbangkan hak cipta — kutip dengan atribusi yang tepat, jangan reproduksi episode lengkap sebagai konten Anda sendiri tanpa izin host.

Apakah file episode saya aman?

Ya. File dienkripsi saat upload (HTTPS/TLS) dan saat disimpan (encryption at rest). Hanya akun Anda yang bisa mengakses. Tidak dibagikan ke pihak ketiga. Tidak digunakan untuk melatih AI. Dapat dihapus permanen kapan saja — penting untuk episode yang masih dalam editing atau belum publish.

Catatan: Akurasi transkripsi bergantung pada kualitas audio, jumlah pembicara, dan kejelasan ucapan. Musik latar belakang dapat mempengaruhi hasil.