AI Audio Data Services & Dataset Licensing
Analog music datasets, stem ownership, and structured training data for machine learning and generative audio models.
Sonic Atlas provides AI audio data services for companies, researchers, and developers building music and sound models. We supply fully owned analog recordings, stems, and structured datasets designed for machine learning, audio synthesis, and generative AI applications.
Master & Stem Ownership
Sonic Atlas provides controlled access to fully owned analog master recordings and multitrack stems, including culturally significant material from major artists rarely available in AI training datasets.
Sourced from historic tape archives and preserved sessions, our recordings capture tonal depth, harmonic complexity, and performance nuance often missing from digitally native audio data.
All assets are professionally digitised and structured for machine learning workflows, enabling efficient dataset ingestion, scalable training, and compatibility across modern AI systems.
AI Music Dataset Licensing
We license fully owned analog master recordings and multitrack stems for AI training, machine learning, and advanced audio research.
Our datasets are designed for clean integration into model development pipelines, supporting high-quality training across a range of generative and analytical audio applications.
1. Advanced Audio Synthesis:
High-Fidelity Analog Inputs for Synthesis Models
Hardware-processed audio for training virtual-analog systems, physical modelling engines, and next-generation synthesis architectures.
2. Source Separation:
Precision Multitrack Data for Source Isolation
Phase-aligned stems and clean Layer 1 audio enable accurate source separation and neural mapping across complex recordings.
3. Style Transfer:
Authentic Signal Paths for Style Modelling
Hardware-verified processing, including Studer and Neve signal chains, supports realistic timbre transfer and cross-domain audio modelling.
Available assets include:
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Comprehensive Multi-Track Archives: Each asset includes a full 24–48 track session, with every individual stem mastered to peak technical standards. These sessions preserve the complete harmonic relationship between instruments, providing the "Ground Truth" data required for complex generative modeling and structural music analysis.
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Bi-Layered Training Sets: We provide a dual-stream delivery format for every isolated stem:
Layer 1 (Source): The pristine, dry digital transfer—ideal for baseline neural training and source separation testing.
Layer 2 (Refined): The hardware-processed variant, passed through an authentic analog signal chain (Studer A827 / Neve 1073).
This L1/L2 pairing allows AI models to "learn" the mathematical transform of high-end analog saturation, a critical component for advanced Style Transfer Frameworks.
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Lossless High-Bitrate Delivery: All assets are delivered at industry-leading resolutions (96kHz/24-bit or higher) to ensure maximum spectral detail. Our delivery pipeline is built for seamless API integration, providing machine-ready files that meet the rigorous ingestion standards of Tier-1 AI synthesis engines and LLM frameworks.
Dataset Delivery & Compliance
Structured, compliant dataset delivery designed for seamless integration into AI and machine learning workflows.
1.Structured Dataset Delivery
All recordings are professionally digitised and delivered in standardised formats, enabling direct ingestion into machine learning pipelines and audio model development environments.
2. Custom Dataset Curation
Targeted datasets curated by genre, era, production style, and signal behaviour, tailored to specific training objectives and model requirements.
3. Data-Driven Partnerships
Ongoing dataset development aligned with product roadmaps, supporting scalable training and continuous model improvement.
4.Compliance & Rights Transparency
Every asset is fully owned and delivered with documented provenance and clear chain of control, ensuring legal certainty and eliminating downstream rights risk.