Preview ready-to-license recordings of speech, voice commands, conversations and sound events from real-world environments. Built for speech recognition, voice assistant and audio AI teams that want to test audio data before commissioning a custom collection.
Speech
Read and spontaneous speech from diverse speakers, in multiple languages and accents, for speech recognition training and evaluation.
Voice Commands
Wake-word and command-phrase recordings for voice assistants, smart devices and automation systems.
Conversations
One-to-one and multi-speaker conversations, interviews and support-style dialogues, for chatbot, NLP and conversational AI models.
Sound Events
Recordings of traffic, household, industrial and public-space sounds for acoustic scene recognition and audio event detection.
About This Dataset
An off-the-shelf (OTS) audio dataset is a set of recordings that has already been collected and can be licensed for AI training. Ours include speech, voice commands, conversations and environmental sounds from diverse speakers and real-world recording environments, in multiple languages and accents. This is the kind of data speech recognition, voice assistant and audio intelligence models learn from.
Because the data already exists, you can open samples, check the languages and recording conditions, and judge quality before you commit. If you need other languages, speakers or environments, our custom audio data collection service records them to your brief. You can also browse every OTS dataset, including image and egocentric video.
Speech, voice commands, conversations and sound events
Multiple languages, accents and speaker demographics
Samples you can preview before you request a dataset
Custom audio collection available when OTS data is not enough
Why Real-World Audio
Voice and audio models perform only as well as the variety of sound they were trained on.
Recordings across accents, dialects and speaking styles help models understand how people really talk, not only how they read.
Real dialogues and multi-speaker interactions teach assistants and chatbots to follow turns, interruptions and intent.
Multilingual and region-specific audio supports models that must work for different speakers and markets.
Background noise, room acoustics and device differences in real recordings prepare models for production conditions.
Use Cases
These are the most common ways teams use speech and audio data.
Read and spontaneous speech from diverse speakers trains and evaluates speech-to-text models across accents and languages.
Command phrases and wake-word recordings train smart-device and in-car voice interfaces to respond reliably.
Dialogues, interviews and support-style conversations feed speaker, intent and conversation-understanding models.
Recordings of traffic, household, industrial and public sounds support acoustic scene recognition and audio monitoring.
Working with other data types? See our text data collection and image data collection.
Buyer's Checklist
A dataset is only useful if it matches your speakers and conditions. Ask about these five things.
Confirm which languages and accents are covered, and how age, gender and region are spread across speakers.
Ask about background noise, room acoustics and whether recordings are clean, noisy or both, to match your deployment.
Check whether transcripts, speaker labels or sound-event tags are included, or whether you will annotate the audio yourself.
Know which microphones and devices were used, and the sample rate and file format of the delivered audio.
Ask how speaker consent was obtained, how personal information is handled, and what licence terms apply.
Answers to common questions about off-the-shelf audio and speech datasets for AI training.
An off-the-shelf (OTS) audio dataset is a pre-collected set of recordings, such as speech, voice commands, conversations or sound events, that is available to license for AI training. You can review samples and check the languages and recording conditions before you commit, instead of waiting for a new collection project.
Our audio work covers speech data (read and spontaneous speech), voice commands and wake-word recordings, conversations and dialogues, and environmental and sound-event recordings. Ask us which of these are available as ready datasets.
We collect multilingual speech across accents and regions, with speakers recruited by language, age, gender and geography. Tell us the languages and accents your model needs and we will confirm what is available.
They can. Depending on the dataset, recordings may come with transcriptions, speaker details, language labels or sound-event tags. Audio can also be passed to our annotation team for labeling and review, or delivered as is if you annotate in-house.
An OTS dataset is fixed, pre-collected data you can evaluate right away. Custom audio data collection is planned around your own languages, speakers, scripts and recording environments. Many teams start with an OTS dataset to test results and add custom collection for gaps.
We record with professional microphones, mobile devices, headset microphones and field recorders, depending on the content. Exact devices, sample rates and file formats depend on the dataset and are agreed with your team before delivery.
Speakers take part with consent, and rights terms are agreed up front. Ask us for the consent and licence terms of the specific dataset you are evaluating, and for how personal information in recordings is handled.
Browse the sample cards above and open any of them to see its description and specification. Then use the contact button on this page and share your languages, audio types and the volume you need. We will reply with the matching dataset options.
More OTS Datasets
Need another data type? Browse our egocentric, multi-camera and image collections, or see all OTS datasets.
Get Started Today
We record speech and sound around your languages, speakers, environments and quality criteria, with samples to test first.
