Sourcing option
Podcast speech for recognition research
Scope long-form conversational audio and transcript requirements.
Long-form speech · Natural conversation
Podcast datasets.
Let the conversation run.
Long-form dialogue offers more than spoken words: context, questions, interruptions, and changing turns. Define the conversations you need, then explore the right source material.
A direct line to Fiund. Source fit and permissions reviewed for your project.
Task-first scope
Specify the outcome your model needs.
Source context
Keep file meaning and lineage connected.
Reviewable quality
Agree on evidence and acceptance criteria.
Direct conversation
Speak with Jaeden at Fiund.
Original photography
The people and places behind a recording.
Real conversations, microphone positions, set details, and production views from Podcast Studio AZ and Jaeden’s own recordings.
Real source photographs and video frames. Editorial examples; dataset availability and permitted uses are reviewed separately.View sources & full gallery →
Dataset solutions
Find the right source for the model task.
Sourcing option
Speaker diarization and conversational turns
Specify speaker attribution, overlapping speech, and session grouping.
Sourcing option
Domain-specific podcast conversation
Plan topic coverage for specialist conversational language.
Sourcing option
Paired podcast audio and video
Review edition matching and audiovisual synchronization.
Sourcing option
Publisher archive preparation
Map source recordings, contributors, and derivative files.
Category context
Different sources. Different review questions.
Multi-speaker conversations
Interviews, co-hosted discussion, and other dialogue formats. Specify speaker count, interaction style, duration, and whether overlap or spontaneous speech is important.
Language and topic collections
Identify languages, accents, subject areas, and the diversity you want across shows and speakers. Ask for counts that distinguish episodes, speakers, and unique recording sessions.
Source tracks and transcripts
Discuss mixed episodes, independent participant tracks, and text alignment. Include requirements for intros, advertising, music, edits, and excluded participants.
Why the details matter
Better data starts with a better definition.
Podcast datasets can range from a finished episode to separate participant recordings with aligned text. These are materially different inputs for a speech pipeline. This Fiund sourcing site focuses on the formats, conversational coverage, and participant considerations that matter when evaluating podcast audio for AI.
Explore quality & provenance →Specification essentials
01Recording level
02Dialogue coverage
03Editorial exclusions
04Speaker and source review
Technical scope
Specify the collection before counting the volume.
Recording level
Published episode, original session, mixed master, or independent participant tracks.
Dialogue coverage
Speaker count, recurring hosts, guest diversity, topics, languages, and recording conditions.
Editorial exclusions
Advertising, music, licensed inserts, intros, synthetic voices, and excluded contributors.
Speaker and source review
Permission scope, contributor documentation, attribution requirements, and any onward-use restrictions.
Real recordings
A look inside the recordings.
Browse short, silent excerpts from real studio conversations and Jaeden’s original recording tracks. Discuss source audio, transcripts, and the intended use when scoping a dataset.
Real conversations at Podcast Studio AZ
Recorded conversations at Podcast Studio AZ · 14 seconds · silent editorial clip.
Jaeden Schafer recording in his podcast studio
Jaeden’s original Riverside recording · 15 seconds · silent editorial clip.
Jaeden Schafer in a real Riverside recording
Jaeden’s original Riverside recording · 15 seconds · silent editorial clip.
Recorded voice
Jaeden Schafer — archival AI Chat speech excerpt
Real solo podcast speech from Jaeden’s July 2, 2025 recording. Editorial audio example; not a telephone call or an advertised training-data sample.
Read the automatic transcript
Today on the podcast, I wanted to do a big update on xAI, some things happening over at X, as I think this is a pretty significant amount of money that has just been put into the ecosystem.
How sourcing works
From the first brief to a reviewable handoff.
01 / PROJECT STAGE
Define the target
Podcast datasets can range from a finished episode to separate participant recordings with aligned text. These are materially different inputs for a speech pipeline. This Fiund sourcing site focuses on the formats, conversational coverage, and participant considerations that matter when evaluating podcast audio for AI.
02 / PROJECT STAGE
Write the specification
Languages, topics, and conversation styles; Hours and preferred speaker diversity; Mixed audio or independent tracks; Transcript, diarization, and edit exclusions; Training use and participant-permission requirements. These details establish the project’s review criteria and reveal where further clarification is needed.
03 / PROJECT STAGE
Review sourcing fit
Discuss which existing sources or collection approaches could address the brief. Identify access constraints, source documentation, and unanswered permission questions before treating a category as usable inventory.
04 / PROJECT STAGE
Inspect representative material
Where appropriate material can be shared, agree on handling and inspect it against the specification. Record defects, coverage gaps, and annotation questions against exact source identifiers.
05 / PROJECT STAGE
Agree the project scope
Confirm the selected material, intended uses, preparation work, acceptance criteria, commercial terms, and delivery arrangements in a project-specific agreement.
06 / PROJECT STAGE
Review the handoff
Check file references, manifests, documented processing, and accepted exceptions. Keep permission review and technical acceptance explicit, and resolve open issues before the collection is treated as approved for the intended use.
Field notes
Practical reading for a sharper brief.
Resource guide
Episodes are editorial units; sessions are recording units
Choose the unit that fits your experiment before counting podcast hours.
Resource guide
How to request separate podcast recording tracks
Plan a track-level request without assuming every archive contains isolated microphones.
Resource guide
Advertising boundaries in podcast collections
Distinguish original conversation, sponsorship reads, and dynamically inserted material.
Resource guide
A practical channel manifest for podcast audio
Describe what each file and channel actually contains.
Resource guide
Recurring hosts can dominate a podcast speech collection
Measure unique conversation coverage as well as total duration.
Resource guide
Choosing a podcast transcript specification
Verbatim words, readable prose, and timed annotations serve different purposes.
Common questions
Before you source.
Does a publicly available podcast come with AI training permission?
Public availability does not establish permission for a particular commercial training use. Ask which parties control the relevant material and what documentation supports the proposed license.
Can I request participant tracks instead of the finished episode?
Yes. Include that requirement. A published mix cannot be assumed to have recoverable original speaker tracks; availability depends on the source recordings and the owner’s delivery options.
Should I count episodes or unique conversations?
Include both where useful. An episode may be an excerpt, compilation, or alternate edit of a recording. Source session identifiers help distinguish unique conversations from multiple published versions.