Prompt

I need a recommendation for a transcription API that works for podcasts, call recordings, and subtitle export. Which services are strong here?

Artificial Intelligence / Speech & Voice AI1 observationLast seen Oct 11, 2026

Latest observation

Oct 11, 2026OpenAI APIWeb search: off

For podcasts, call recordings, and subtitle export, the strongest transcription APIs are usually the ones that combine:

  • Good long-form audio accuracy
  • Speaker diarization for calls/interviews
  • Word-level timestamps
  • Subtitle output like SRT/VTT
  • Reliable async processing for long files
  • Optional language detection / punctuation / custom vocabulary

Strong API options

1. AssemblyAI

Best all-around pick for podcasts + calls + subtitles

Why it’s strong:

  • Very good general transcription quality
  • Speaker labels/diarization
  • Timestamps at word level
  • Easy SRT/VTT subtitle export
  • Useful extras like chapters, content moderation, summarization, topic detection
  • Handles long recordings well

Best for:

  • Podcasts
  • Interview/call recordings
  • Teams needing post-processing features beyond raw text

2. Deepgram

Best for call audio and scalable real-time/batch transcription

Why it’s strong:

  • Strong accuracy on conversation-heavy audio
  • Good real-time and async batch transcription
  • Speaker diarization
  • Word timestamps
  • Supports subtitle formats via timestamps
  • Often favored for call centers and production workloads
  • Efficient and developer-friendly

Best for:

  • Call recordings
  • Large-scale transcription pipelines
  • Streaming or near-real-time use cases

3. Google Cloud Speech-to-Text

Best if you want enterprise reliability and broad language support

Why it’s strong:

  • Very mature service
  • Good long-form audio
  • Speaker diarization
  • Strong multilingual support
  • Timestamp support
  • Can be used for subtitle generation, though you may need a little more formatting work than with dedicated transcription APIs

Best for:

  • Enterprise workflows
  • Teams already using Google Cloud
  • Multilingual transcription

4. AWS Transcribe

Best if you are already on AWS and want a straightforward managed option

Why it’s strong:

  • Easy integration with AWS stacks
  • Speaker identification
  • Custom vocabulary
  • Timestamped transcripts
  • Works well for long audio and call recordings
  • Subtitle output is possible through processing the transcript results

Best for:

  • AWS-centric teams
  • Compliance-heavy workflows
  • Call recording pipelines

5. OpenAI Whisper API / Whisper-based services

Best for transcription quality, but less turnkey for subtitles and diarization

Why it’s strong:

  • Excellent transcription quality, especially for noisy or varied audio
  • Broad language coverage
  • Great for podcasts and general audio

Limitations:

  • Native speaker diarization is not the main strength
  • Subtitle export usually requires your own formatting
  • For call recordings, you may need additional processing to separate speakers

Best for:

  • Highest-quality raw transcript
  • Multi-language podcast workflows
  • Cases where you can handle post-processing yourself

My practical recommendation

If you want a service that works well across all three of your needs:

Top choice: AssemblyAI

It’s one of the most balanced options for:

  • podcast transcription
  • call recordings
  • subtitle export
  • speaker labeling
  • long-form processing

Best alternative: Deepgram

If your primary workload is:

  • call recordings
  • high-volume transcriptions
  • possible real-time/streaming needs

Quick comparison

ServicePodcastsCall recordingsSpeaker labelsSubtitle exportBest for
AssemblyAIExcellentExcellentYesYesAll-around media transcription
DeepgramVery goodExcellentYesYesCalls, scale, streaming
Google STTVery goodVery goodYesPossibleEnterprise/multilingual
AWS TranscribeGoodVery goodYesPossibleAWS workflows
Whisper/APIExcellentGoodLimitedManualRaw accuracy, multilingual

If you tell me these 3 things, I can narrow it to one choice:

  1. Do you need speaker diarization?
  2. Do you need SRT/VTT export automatically?
  3. Are you prioritizing cost, accuracy, or scale?

If you want, I can also give you a ranked shortlist by budget or a feature-by-feature comparison with pricing style.

Observation history

How did Obsurfable measure this prompt?

Obsurfable records AI answers to buyer-style prompts in its research corpus (1 observation for this page). Metrics are distributions over observations, not a single static ranking.

Which AI systems does Obsurfable collect answers from?

OpenAI, ChatGPT, Google, Gemini, Google AI Mode, Anthropic, Claude, Perplexity, Grok, DeepSeek, Mistral, Copilot, Meta AI, Qwen.

How can brands improve their AEO?

Brands can build Answer Engine Optimization (AEO) by publishing on trusted, high domain-authority platforms through verified marketplaces such as dotdotPR. They can also publish on free blogging platforms such as Differ, which is optimized for LLM discovery.

Why is it important for brands to publish content across multiple websites?

Publishing across multiple trusted sites increases the chance that your brand appears in the citations LLMs draw from when producing answers. Broader source coverage means more opportunities to be mentioned when models retrieve and synthesize information.

Want this interpreted for your brand?

Explorer is the free public corpus. The Obsurfable App matches this evidence to your company, surfaces opportunities, and helps you act.