NOISE DATASETS FOR AI

Fuel the accuracy of your AI with noise datasets to recognize environment

Train smarter AI with Pangeanic's noise datasets. Fuel the accuracy of your AI with diverse environmental soundscapes.

Home & Indoor Environments

Human Activity Sounds: sneezing, coughing, yawning, breathing patterns, sleeping, snoring, infant cooing/crying, laughter variations, footsteps on carpet/wood/tile, dragging furniture.
Appliance & Device Cycles: washing machines, kettles boiling, toaster pops, vacuum cleaners, printers, phone notifications, and robot vacuum navigation.
Safety & Alerts: smoke/CO alarms, fire extinguishers, glass shattering (different sizes), doorbell variations (smart, mechanical, regional), alarm clocks.
Object Interaction: keys jangling, doors locking/unlocking and opening/closing, drawers opening, glasses, water being poured, dishes clattering, silverware sorting, paper rustling, and remote clicks.

a spanner as a symbol of industrial environment noise datasets

Industrial & Work Environments

Construction: jackhammers, drills, cranes, welding sparks, hammering.
Factories: conveyor belts, robotic arms, forklifts, intercoms, safety alarms.
Offices: typing, printers, phone rings, call center noises, people interacting, office chairs moving, conference chatter. Regional varieties available (Gulf office noise environment, European office noise environment, Japanese office noise environment, Chinese office noise environment, African office noise environment, etc.)

a delivery truck as a symbol mobility noise datasets for AI training

Mobility & Vehicles

Cars: engines idling, electric vs. combustion, doors closing, seatbelt clicks, horns (regional differences).
Public Transport: metro doors, bus hydraulics, ticket machines, train crossings.
Special Vehicles: ambulances, fire trucks, police sirens (regional variations), motorcycles, bicycles with bells.
Marine & Air: ferry horns, sail flapping, airplane takeoff/landing, drones buzzing.

Global & Specific Environments

Regional Urban Ambiance: open-air markets, subway systems (London Tube, NYC MTA, Tokyo Metro), trams (Lisbon, Melbourne), traffic patterns (rickshaws, scooters, tuk-tuks), street noises from Gulf countries, from Europe or from Japan, etc.
Transportation Hubs: airport sounds (boarding gates, rolling luggage, boarding announcements, boarding pass scanners), bus depots, train horns, conductor whistles, escalators, crowd boarding patterns.
Nature & Weather Phenomena:
- Rain (drizzle, downpour, roof hits, puddle splashes).
- Wind (through trees, high-altitude whistling, urban wind tunnels).
- Thunder (distant vs. close cracks).
- Regional fauna: cicadas, frogs, wolves howling, exotic birds, and roosters.

Commercial & Public Spaces

Retail & Food: supermarket scanners, shopping carts, bagging, deli slicers, cash registers, vending machines.
Hospitality: café espresso machines, bar chatter, restaurant silverware clinks, kitchen sizzling.
Recreation: arcade beeps, bowling alleys, pool tables, cinema pre-show murmur.
Institutional: library whispers, classroom murmurs, school bell rings, hospital monitor beeps, paging systems.

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Extreme / Rare Scenarios

Disasters: earthquakes (structural creaks, glass breaking), floods (water surges), wildfires (crackling + sirens).
Crowd Events: stadium cheering, protests, parades, concerts.
Military & Security: gunfire types, helicopters, drones, sirens under stress conditions.

Metadata required for noise datasets for AI

Metadata Needs

To make these datasets truly useful, each recording can include:

Context (location, environment size, indoors/outdoors).
Source details (device type, model, human demographics if voice-related).
Acoustic characteristics (distance, reverberation, background interference).
Annotations (timestamped labels for events, cycles, or intensity changes).

Listed in Gartner Hype Cycle for NLP Technologies - Neural Machine Translation, Emerging Tech for Conversational AI and Synthetic Data (Data Masking)

Pangeanic knows the journey. We understand the importance of the right data because we build ML tools — we’re setting the standard for AI-powered language technology and R&D programs for government.

We’ve been named in Gartner’s Hype Cycle for Language Technologies—a rare feat for two consecutive years (2023 & 2024), thanks to our customizable Neural Machine Translation (NMT) solutions that adapt to our clients’ needs.
Gartner also spotlighted our expertise in conversational AI and synthetic data (data masking), reinforcing our breadth across cutting-edge language domains.
Most recently, we earned recognition in Gartner’s “Emerging Tech: Conversational AI Differentiation in the Era of Generative AI” report — highlighting how our ECO platform elevates accuracy, scalability, and trust in AI-driven translation through optimized language models and advanced RAG systems.

Trust Pangeanic, as mentioned by Gartner

Companies and startups need dependable sources of environmental and acoustic datasets to train AI systems that truly understand the world around them. Pangeanic has a proven track record in supplying high-quality training data across industries, and we are continuously expanding into noise and soundscapes — essential for speech recognition, robotics, smart devices, and security applications.

Our expertise combines off-the-shelf (OTS) datasets with custom collection projects and exclusive agreements with data producers worldwide. This approach ensures clients gain access to a wide range of sounds — from daily household noises and safety alerts to complex transportation hubs and regional ambiances.

By uniting global OTS resources, proprietary recording pipelines, and trusted partnerships, Pangeanic guarantees diversity, precision, and compliance in every dataset delivered. We are constantly gathering, annotating, and enriching noise datasets, making us the reliable partner for organizations looking to build the next generation of context-aware AI.

Are you a generative AI company in search of data for success?

In today's data-driven world, large enterprises hold a competitive edge. At Pangeanic, we recognize the significance of high-quality data. We're here to assist you in overcoming data access challenges, establishing partnerships, and protecting sensitive information. Don't let a lack of data get in your way; contact us today to boost your success in generative AI!

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Improve keyword extraction and summarization

Feed your Machine Learning models with huge datasets for superior keyword and phrases extraction and summarization, in any language!

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Reinforcement Learning with Human Feedback

Need a custom human service vendor to decide how well your last training went? Pangeanic offers RLHF services so that humans make your AI more accurate.

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We test-train models for QA and information retrieval

Improve your question-answering models with massive quality datasets in any language. Data collection and data creation services available. Obtain higher relevance.

Why Pangeanic's noise datasets for AI?

LLMs can read and write — but real intelligence comes from understanding the world we live in. That means training AI not only on language, but also on the sounds of daily life: homes, cities, machines, alerts, and natural environments.

Pangeanic is your trusted partner for supplying noise and acoustic datasets that bridge the gap between text-based AI and real-life awareness.

Our strength comes from the right mix of expertise:

Data Science to design and scale collection pipelines.
Linguistics & Annotation to classify and label soundscapes with precision.
Engineering & Development to integrate datasets into your AI workflows.
Global Partnerships to source unique sounds through agreements with data producers worldwide.

With Pangeanic, your AI won’t just process words — it will recognize environments, detect context, and react like it truly understands the world around it.

Why Pangeanic noise datasets for AI?

Customized data collection in any language you need: Datasets for AI training and AI testing from our NLP team!

Pangeanic can offer large amounts of scalable datasets for AI training thanks to its huge repository of 10 billion aligned data segments or offer customized human-based solutions for datasets used for training AI.

With 20+ years of experience in language services, and as NLP developers since 2009, each project is carefully evaluated and a specific set of rules is created for our professional linguists to manage the data collection. All Pangeanic data for AI training is scalable, accurate and tailored to the particular needs of each client.

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Data for Training AI: Key Aspects and Best Practices

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Parallel Corpora for Machine Translation Systems

We provide clean, parallel segments from our large database, or as on-demand translation services. All translated data undergoes strict quality controls and checks to ensure that it is clean and valid for Machine Learning.

person working in parallel corpora

At Pangeanic we are used to managing large translation resources in different time zones and production peaks, and we work with more than 85 languages and combinations that do not include English (Polish-German, Spanish-Chinese, Arabic-French, among others).

Human input is key to the success of any Machine/Deep Learning project and guarantees much less noise than web translation alignment (scraping) or crowdsourcing. As developers of Machine Translation systems, we understand the effects that poor quality data can have on any algorithm, and use scalable human processes combined with our extensive experience in quality control of translation services.

Pangeanic has an entire department in charge of collecting, verifying, cleaning, gathering, augmenting and selecting Parallel Data.

Data Annotation

We offer customized, high-quality text data annotation services designed to improve machine learning (ML) models and AI applications.

Our customized services include Image Capture and Annotation (e.g. bounding boxes, handwriting recognition and multilingual video transcription).

Our proprietary tool called PECAT, which facilitates both monolingual and multilingual data labeling. PECAT incorporates "human-in-the-loop" (HITL) quality control, allowing human experts to review annotations and ensure the highest accuracy. The tool also supports glossaries, regular expressions, and integration with LLMs for precise labeling.

Key Services & Use Cases:

Services: We provide a wide range of annotation services, including named entity recognition (NER), sentiment analysis, part-of-speech (POS) tagging, intent classification, and topic modeling.
Use Cases: Their services are crucial for training AI in tasks like sentiment analysis (detecting nuance, sarcasm, and idioms), creating datasets for LLMs, detecting hate speech and bias, and extracting specific information for industries like finance (cryptocurrency), eCommerce, and medical research.

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Speech Data

We provide meticulously collected and annotated speech datasets, empowering your machine learning and NLP models to understand the world, ethically and accurately.

"Trusted by leading innovators in AI" creating AI home appliances of the future.
Transcription of thousands of hours for Spanish Parliament and Valencia's Parliament.

Speech Data Collection and OTS