| --- |
| pretty_name: "Pro Sound Effects — AI/ML Audio Dataset Sample" |
| license: other |
| license_name: pse-research-evaluation |
| license_link: LICENSE |
| language: |
| - en |
| task_categories: |
| - audio-classification |
| - audio-to-audio |
| - text-to-audio |
| - automatic-speech-recognition |
| tags: |
| - audio |
| - sound-effects |
| - sfx |
| - foley |
| - environmental-sound |
| - ucs |
| - universal-category-system |
| - generative-audio |
| - source-separation |
| - noise-cancellation |
| - professionally-recorded |
| - rights-cleared |
| size_categories: |
| - n<1K |
| |
| |
| |
| |
| |
| |
| |
| |
| extra_gated_heading: "Get the Pro Sound Effects AI/ML Audio Dataset sample" |
| extra_gated_prompt: >- |
| This is a free, non-commercial **evaluation sample** drawn from the Pro Sound |
| Effects Audio Dataset. By requesting access you agree that: |
| |
| - Use is limited to internal research and evaluation; commercial use, |
| redistribution, resale, and sublicensing are not permitted. |
| - You will not use the audio to identify individuals or in any way that |
| invades privacy. |
| - Full terms are in the accompanying LICENSE file. |
|
|
| Need the full dataset, a larger curated subset, or commercial rights? See |
| "Going further" below, or reach us at data@prosoundeffects.com. |
| extra_gated_fields: |
| Full name: text |
| Company or institution: text |
| Role: |
| type: select |
| options: |
| - Researcher / PhD |
| - ML Engineer |
| - Product / Content lead |
| - Other |
| What are you building?: text |
| Intended use: |
| type: select |
| options: |
| - Academic / non-commercial research |
| - Evaluating for a commercial project |
| - Other |
| I understand this sample is for non-commercial evaluation only, per the LICENSE: checkbox |
| I'd like PSE to follow up about full dataset or Research License options: checkbox |
| extra_gated_button_content: "Request access to the sample" |
| --- |
| |
| # Pro Sound Effects — AI/ML Sample Dataset |
|
|
| **The Most Comprehensive Audio Dataset for AI & Machine Learning.** |
|
|
| A free, downloadable evaluation slice of the Pro Sound Effects (PSE) Audio Dataset: |
| professionally recorded, 100% human-annotated, UCS-organized sound effects with |
| clean, fully-owned commercial rights. This sample lets you benchmark PSE data |
| against whatever you're using today before committing to anything. |
|
|
| > Built and licensed by [Pro Sound Effects](https://prosoundeffects.com) — |
| > recording, annotating, and licensing professional audio since 2004. |
|
|
| --- |
|
|
| ## TL;DR for researchers |
|
|
| - **What it is:** A representative `102`-clip / `18`-minute subset |
| spanning `28` categories, with the same uniform metadata schema used |
| across the full 1.2M+ audio dataset. |
| - **Why it's different from crowdsourced/public audio:** recordings by Oscar-winners' and masters of craft, uniform hand-tagged |
| metadata (not noisy auto-labels), consistent recording quality, and |
| unambiguous commercial rights — PSE owns the library outright, so there's no |
| provenance or licensing gray area to inherit into your model. |
| - **Publishing:** The Research License explicitly permits publication with |
| citation (see [Going further](#going-further)). Cite as below. |
| - **License (this sample):** non-commercial evaluation only — see `LICENSE`. |
|
|
| --- |
|
|
| ## What's in this sample |
|
|
| | | | |
| |---|---| |
| | Clips | `102` | |
| | Total duration | `~18 mins` | |
| | Categories covered | `28 — top ones are Swooshes, Fight, Animals, Destruction, Electricity, Glass, Ambience, Explosions` | |
| | Format | `WAV · 48 / 96 / 192 kHz · 16- and 24-bit · mono, stereo, and some multichannel` | |
| | Metadata fields | `file_name, Keywords, Description, Category, SubCategory, Channels, BitDepth, SampleRate, Duration, Library` | |
|
|
| Each row pairs an audio file with structured, human-written metadata. A |
| `metadata.csv` (or `metadata.jsonl`) maps every file to its tags so the dataset |
| loads directly with 🤗 `datasets`. |
|
|
| --- |
|
|
| ## The full private PSE Audio Dataset (what this sample is drawn from) |
|
|
| - **1.2M+** exclusive, discrete sounds — growing toward 3M+ by 2028 |
| - **5,000+ hours**, ~5.8 TB of audio |
| - **650+ categories**, optimized for the Universal Category System (UCS) |
| - **100% human-annotated** with uniform metadata (100K+ editorial hours) |
| - **Full rights owned by PSE** — private, not aggregated, not scraped, not crowdsourced |
|
|
| --- |
|
|
| ## Built for AI use cases |
|
|
| The library is structured to support, among others: |
|
|
| - **Speech recognition & voice AI** — assistants, transcription, voice auth |
| - **Environmental sound recognition** — accessibility, assistive tech, IoT, transportation |
| - **Active noise cancellation & audio separation** — comms, broadcast, restoration |
| - **Generative audio & text-to-sound** — text-to-SFX, creative AI, music generation |
| - **Audio classification & tagging** — moderation, intelligent classification |
| - **Dynamic retrieval & RAG** — adaptive playback, audio search |
|
|
| --- |
|
|
| ## Why the rights & provenance matter |
|
|
| Training-data provenance is now a real legal and reputational exposure for AI |
| teams. PSE is built to remove that risk: |
|
|
| - **Full ownership of rights** — cleanly licensable for commercial use, unlike |
| Creative-Commons-mixed or scraped sources |
| - **Artists are compensated** — licensing revenue flows back to the creators |
| - **Affiliations:** Fairly Trained · Dataset Providers Alliance · Human Artistry |
| Campaign · Content Authenticity Initiative |
|
|
| > *"Human creativity is the foundation of AI's existence. Our mission is to help |
| > creators bring ideas to life — ethically and at scale."* — Douglas Price, CEO |
|
|
| --- |
|
|
| ## Quickstart |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Requires a Hugging Face token (gated dataset); accept the terms once on the Hub. |
| ds = load_dataset("ProSoundEffects/pse-audio-sfx-dataset", split="train") |
| print(ds) |
| print(ds[0]) # {'audio': {...}, 'category': ..., 'description': ..., ...} |
| ``` |
|
|
| Full PyTorch `DataLoader` examples, metadata walkthroughs, and integration |
| recipes live in the companion GitHub repo: |
| **<<FILL: https://github.com/ORG/pse-audio-sample>>** |
|
|
| --- |
|
|
| ## Going further |
|
|
| This sample is intentionally small — enough to validate quality and fit. When |
| your prototype shows the data earns its place, here are the paths: |
|
|
| - **Bigger curated subset / category analysis** — tell us your use case and we'll |
| scope a tailored slice. Email **data@prosoundeffects.com**. |
| - **Research License (non-commercial R&D)** — publication permitted **with |
| citation**. Indicative terms: $2,500/mo · $10,000/yr · $25,000 one-time |
| buyout (program one-pager). Starting at $15,000/yr for ongoing programs. |
| - **Commercial licensing** — Annual, Perpetual, or Revshare structures, scoped |
| to your stage and deployment. Custom GenAI / non-GenAI terms. |
| - **Custom curation & bespoke recording** — if you need coverage we don't have |
| off the shelf. |
|
|
| Start here: [prosoundeffects.com/machine-learning-ai](https://prosoundeffects.com/machine-learning-ai) |
| · [prosoundeffects.com/data](https://prosoundeffects.com/data) · |
| [book a call](https://hello.prosoundeffects.com/meetings/pse-licensing/meet-with-pse) |
|
|
| --- |
|
|
| ## Citation |
|
|
| ```bibtex |
| @misc{prosoundeffects_aiml_sample, |
| title = {Pro Sound Effects --- AI/ML Sample Dataset}, |
| author = {{Pro Sound Effects}}, |
| year = {2026}, |
| howpublished = {Hugging Face Hub}, |
| url = {https://huggingface.co/datasets/ProSoundEffects/pse-audio-sfx-dataset} |
| } |
| ``` |
|
|
| ## Contact |
|
|
| - Data / technical: **data@prosoundeffects.com** |
| - Web: [prosoundeffects.com/data](https://prosoundeffects.com/data) |
