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AudioShake says The Refinery converts existing recordings into structured audio data for training speech and conversational AI. Its central distinction is that it is designed not just to label who spoke when, but to separate overlapping voices into individual, labeled audio tracks—even when the source is a finished mix rather than original session files.
What The Refinery does
AudioShake describes The Refinery as a service that takes raw, real-world recordings and returns structured, training-ready audio. It says customers do not need original stems or session files: the system works from the mixed recording itself. It can separate speakers who talk over one another into labeled tracks and can also isolate dialogue, music, and background sound from finished recordings. AudioShake’s October 8, 2026 launch article describes the product and workflow.
This is intended to make existing audio archives more useful as training material. The company names AI labs, owners of audio libraries, and data providers or marketplaces as target customers.
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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Speaker labeling is not the same as speaker separation
Diarization identifies which speaker is active at a given point in a recording. It can mark turns and attribute speech to speaker labels, but labeling alone does not create clean, individual audio tracks when voices overlap. Separation attempts to recover each voice as its own track from the mixed audio.
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That difference matters for conversations with interruptions, simultaneous speech, laughter, or one person finishing another’s sentence. AudioShake says The Refinery can preserve these overlapping moments as separate labeled tracks rather than treating the recording as a simple sequence of non-overlapping turns.
How AudioShake says the workflow handles uncertainty
The Refinery supplies confidence scores for speaker assignment and separation quality. A team can use those scores to retain or reject material, rank it for usefulness, or route uncertain segments for human review. AudioShake’s September 22, 2026 Multi-Speaker 2.0 release likewise describes low-confidence moments being flagged for review.
AudioShake says the underlying Multi-Speaker 2.0 technology separates a mixed conversation into individual voice stems and an ambience stem. It describes its approach as using the real source recording rather than synthesizing or filling in speech. That is the company’s characterization of its system, not an independently verified finding.
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What it may be used to prepare
AudioShake lists several intended uses for structured audio data:
- Automatic speech recognition (ASR)
- Speaker diarization and speaker identification
- Text-to-speech (TTS)
- Conversational AI
The usefulness of a processed corpus will depend on the target model and the quality and rights status of the source recordings. The launch materials describe audio-processing capabilities, but do not establish The Refinery’s legal, privacy, or contract terms.
Reported scale and performance
The figures below come from AudioShake’s product materials. The launch coverage available here does not independently audit the scale or benchmark claims.
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| Claim | What AudioShake says | How to interpret it |
|---|---|---|
| Processing volume | More than 100 million minutes of audio processed over the previous year | AudioShake’s reported figure for early private versions of The Refinery; the company says it deployed them with frontier AI labs and names Luel and Rime as customers. |
| Transcription errors | 4.1 times fewer transcription errors than a tested open-source separation baseline | AudioShake’s result for separated tracks in its LibriCSS evaluation; the launch article links to its technical evaluation and methodology. |
| Audio bleed | 32% less bleed versus Multi-Speaker 1.0 | AudioShake’s reported comparison for Multi-Speaker 2.0. |
These are vendor-reported figures, not a guarantee of performance on a particular customer’s recordings. The LibriCSS result is tied to AudioShake’s stated evaluation and baseline; it should not be read as a universal improvement across datasets or recording conditions.
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Multi-Speaker 2.0 availability and input range
AudioShake says Multi-Speaker 2.0 handles audio from 8 kHz to 48 kHz and is available through AudioShake Studio and its API. Those details describe Multi-Speaker 2.0; they do not, by themselves, specify The Refinery’s commercial deployment options or terms.
For a team assessing the offering, the practical questions are whether its source recordings fit the supported conditions, how it will review low-confidence segments, and whether its rights and operational requirements are met. Public pricing, licensing terms, and full deployment options for The Refinery are not stated in the launch materials.
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What customers and AudioShake say
AudioShake co-founder and CEO Jessica Powell described the value of retaining overlap in a Multi-Speaker 2.0 conversation: “Some of our richest, most human moments come at the point of overlap — an interjection, a laugh, finishing someone else’s sentence,”
William Namgyal, CEO and co-founder of Luel, said in a customer testimonial hosted by AudioShake: “AudioShake has helped us process thousands of hours of clean, speaker-separated data, enabling the world’s leading labs to build better models.” This supports that Luel has described using the service, but it is a customer statement rather than independent performance evidence.
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