Any podcast episode as clean Markdown in one API call.

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June 5, 2026

2026 Rank: #1674

Spoken

Podcast transcription

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Any podcast episode as clean Markdown in one API call.

Podcast Transcripts Transcription Speaker Recognition Podcast Markdown Format Speech Recognitionfrom $15

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Overview Discussion

Overview

Spoken is an API tool that provides transcripts for any podcast episode in clean Markdown format. This efficient solution replaces manual audio transcribing processes with a single API call, saving time and resources for developers and allowing them to focus on building their products.

Spoken also uniquely distinguishes real speaker names instead of using generic labels such as 'Speaker 1', enhancing the readability and comprehension of the transcripts.One key feature of Spoken is its ability to detect speaker names by analyzing the context of the transcript, thus eliminating manual lookup tables or post-processing requirements.

Additionally, it offers an easy search facility where users can query by text or paste a URL from various podcast platforms, including Spotify, YouTube, and other podcast apps.Designed to be integrated with AI agents, Spoken's transcripts can be used as input data for various applications like summarizers, RAG pipelines, podcast tools, etc.

It provides a straightforward integration process, supporting any agent framework and accepting simple HTTP calls.Despite being a paid service, Spoken allows potential users a trial experience where they can evaluate the transcript's quality and format using a demo API key.

With a commitment to quality assurance, Spoken ensures that credits are never charged for errors, and it maintains a flexible payment model, without subscriptions or expiration of credits.

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Initial release

June 5, 2026

Initial release of Spoken.

Author

Robert Tomko

@robert-tomko

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Joined: June 2026

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Paid

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$15/unit

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Pay-as-you-go

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Podcast transcription Spoken

Podcast transcription

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Pros and Cons

Pros

Single API call

Markdown formatted transcripts

Real speaker name recognition

Speaker names from context

Easy text or URL search

Compatible with various podcast platforms

Straightforward integration process

Supports any agent framework

Compatibility with HTTP calls

Trial experience with demo API

Quality assurance for errors

Flexible payment model

No expiration of credits

No subscription requirement

Narration summarization feature

Text search functionality

No post-processing requirements

Direct transcript fetch via URL

Naming fallbacks for ambiguous speakers

Transcripts fit into LLM context windows

Metadata included in response headers

Agent skill URL for direct installation

OpenAPI spec for agent integration

Automatic LLM discovery

Credits top-up feature

Error denotation in response

Transcript preview before purchase

Volume-based pricing discounts

Full-service transcript retrieval

Results returned in text/markdown

Name mention analysis for speaker detection

Compatibility across various podcast apps

Supports plain HTTP calls

No manual lookup table for speakers

API response includes top-up link

No timing artifacts in transcript

Supports podcast search by text

Extraction of real speaker names

Search tool integration

Ready-to-use transcripts without cleanup

Allows for text-based episode search

View 36 more pros

Cons

No realtime transcription

No multi-language support

No offline functionality

Relies heavily on context

Doesn't support custom formatting

Probable speaker misidentification

No error correction options

Pricing per transcript

Limited to podcast data

No user interface

View 5 more cons

Q&A

What is Spoken?

Spoken is an API tool designed to provide transcripts for any podcast episode in clean Markdown format. It combines transcript generation with speaker recognition to deliver transcripts that use real speaker names instead of generic labels. Designed for AI agents, it serves various applications such as summarizers, RAG pipelines, podcast tools, and more.

What services does Spoken provide?

Spoken provides a range of services including audio transcription, markdown formatting, speaker recognition, text search, content analysis, speaker detection and context analysis, API services, and integration with AI systems. It also provides a trial experience for potential users to assess its services, maintaining a quality assurance system that doesn't charge credits for errors.

How does Spoken work?

Spoken works by replacing the conventional manual audio transcribing process with a single API call. Users can search for a podcast episode and get the transcript with real speaker names. Spoken also analyses the context of the dialogues to distinguish between speakers and eliminates the need for manual lookup tables or post-processing.

How does Spoken distinguish real speaker names?

Spoken distinguishes real speaker names by analyzing the context of the transcript. Instead of generic labels such as 'Speaker 1', 'Speaker 2', it identifies real names, enhancing the readability and comprehension of the transcripts. When actual names cannot be determined, it uses alternate labels like 'Host' or 'Guest'.

How can I search for podcast episodes with Spoken?

To search for podcast episodes with Spoken, users can query by text or paste a URL from various podcast platforms. It provides an easy and efficient search facility accommodating the needs of podcast listeners and analysts.

What platforms is Spoken compatible with?

Spoken is compatible with various podcast platforms, including but not limited to Spotify and YouTube. It also supports any agent framework, making it versatile and universally applicable.

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How can Spoken be integrated with my AI agents?

Spoken can be integrated with AI agents in a very straightforward process. It provides an OpenAPI spec that works with any agent framework. Users simply need to install the agent skill and it can then accept simple HTTP calls, making the integration seamless and hassle-free.

What format does Spoken provide transcripts in?

Spoken provides transcripts in clean Markdown format with speaker names in bold and timestamps per turn. It aims for convenience, thus eliminating the need for post-processing. The format is designed to be easily readable and is sized to fit in most Language Model Limits (LLM) context windows in a single call.

Does Spoken provide a trial experience?

Yes, Spoken provides a trial experience where potential users can calibrate the transcript's quality and format using a demo API key. This allows users to evaluate the service without any upfront commitment or payment.

What is Spoken's payment model?

Spoken maintains a flexible payment model. It charges on a per transcript basis, without subscriptions or expiration of credits. Though it is a paid service, credits are not charged for erroneous transcripts, ensuring that users only pay for accurate results.

How fast can I get a transcript from Spoken?

Spoken delivers the first transcript in under 30 seconds. The key is delivered instantly after payment, ensuring a swift turnaround for users.

Can Spoken be used for large volume of transcripts?

Yes, Spoken can handle large volumes of transcripts. It offers a range of pricing tiers, from a starter pack of 100 transcripts up to a volume pack of 2,000 transcripts. Larger quantities also come with a discount per transcript.

How does Spoken ensure quality of transcripts?

Spoken ensures the quality of transcripts by identifying and recognising real speaker names through context analysis. It offers a trial experience which allows users to evaluate the transcript's quality before the purchase. Moreover, it employs a quality assurance system where credits are not charged for erroneous transcriptions.

What happens if there are errors in Spoken's transcripts?

In the event of errors in Spoken's transcripts, the company assures that credits are never deducted for such instances. This means if there are any mistakes, the user is not charged, reinforcing Spoken's commitment to quality and accuracy.

Is there a limit to the number of transcripts I can get with Spoken?

There is no explicit limit to the number of transcripts you can get with Spoken. Its pricing model is designed for flexibility and scalability, offering a range of options from smaller batches of 100 transcripts up to larger volumes of 2,000 transcripts.

How can Spoken be helpful for developers building podcast tools?

Spoken can be extremely beneficial for developers building podcast tools. By eliminating the need to manually transcribe audio and recognising speaker names, developers can focus on their core product delivery. In addition, Spoken's API can replace an entire transcription pipeline, expediting the building process and reducing the maintenance burden.

Can I use Spoken to convert spoken language to text?

Yes, Spoken is adept at converting spoken language to text. It uses sophisticated natural language processing capabilities to transcribe any podcast episode into text, replacing the manual audio transcribing processes.

Can Spoken be used as a content analysis tool?

Yes, Spoken can be used as a content analysis tool. It processes and transcribes spoken content from a podcast, converting it into searchable and analyzable text format. This can be instrumental for comprehending, summarizing or referencing spoken content from various podcasts.

Is Spoken suitable for data extraction from audio files?

Yes, Spoken is suitable for data extraction from audio files. It efficiently transcribes spoken content from podcasts into textual data, making it possible to extract, analyze, and utilize the information present in these audio files for various applications.

What is the cost per transcript using Spoken?

The cost per transcript using Spoken can vary. It starts at $0.15 per transcript for a pack of 100 transcripts. The company also offers volume discounts, bringing the cost down to $0.10 per transcript for 500 transcripts, or $0.08 per transcript for 2,000 transcripts.

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