In August 2015, the Home Office challenged UK businesses and academia to come up with ways to improve the speed, efficiency, and effectiveness of recovering and analysing data from digital devices seized from suspects under investigation. This was conducted through the SBRI (Small Business Research Initiative) competition run by Innovate UK on behalf of the UK Home Office.
Oxford Wave Research participated in this highly competitive call and was one of the eleven businesses and universities selected for Phase 1 funding. OWR successfully completed Phase 1 and was one of the five companies from the Phase 1 participants that was further selected for Phase 2 of the competition.
The funding for this challenge helped us to enhance our existing MADCAT algorithms for extracting and comparing fingerprints in audio or video, to using GPU-acceleration to perform millions of comparisons in seconds and hundreds of millions in tens of minutes. We further developed this into a client and GPU-server based architecture capable of sharing and comparing audio fingerprint data for high speed cross-case comparisons.
Our R&D team attended the SBRI Digital Forensics Showcase Event in London on Friday, 3rd November 2017, to showcase MADCAT WHISKERS, our high-speed media fingerprint comparison solution that was developed as part of this challenge.
The showcase event provided an excellent opportunity to demonstrate how we used the Home Office funding and input to develop and improve a product which is now being used in certain UK law enforcement agencies with tremendous results.
To find out more about our software please contact us directly at email@example.com
Oscar and Nikki are excited to be attending the kick off of the TAPAS project in Switzerland. OWR are privileged to be industry partners on this exciting new project which brings together some of the best academic and industry leaders in Europe.
Last Friday, when we were just winding up for the end of the week we started getting a large number of messages on our website chat app, and also a a huge spike in the number of hits on our website (1283.05%), and in particular from our audio frequency spectrum analyser called Spectrumview.
Had we been hacked? Had some rivettingly interestingly pictures of the intimate details of audio analysis been unwittingly released on our webpage? Thankfully not. Our app had been used by the extremely talented stand-up comedian and maths communicator Matt Parker () to measure how fast he could get a fidget spinner to go. This video had hundreds of thousands of views each day, and just under 300,000 at the time of writing.
This is a brilliant video that shows how to use Spectrumview to calculate the frequency and thereby the speed of the tips of the fidget spinner. We are delighted to see such a weird and wonderful use for our little app.
Before you ask, we don’t have an Android version. There are no plans to have one just yet, but we may be persuaded. If you ask nicely.
The Linguistic Data Consortium (LDC), USA and Oxford Wave Research (UK) are proud to announce a new collaboration. Oxford Wave Research (OWR) is an audio and speech R&D company based in Oxford, UK that works on audio processing and speaker diarization and recognition. This collaboration encompasses the use of LDC’s speech corpora and OWR’s audio fingerprinting, speaker diarization and recognition software.
In particular, LDC will use OWR’s audio fingerprinting technology as part of the MADCAT software (Multimedia Audio Duplication & Content Analysis Tool) to find repeated content in broadcast data including audio signatures that mark program boundaries.
The OWR Research Director, Dr Anil Alexander says,
“The OWR team is really looking forward to working with LDC on this exciting real-world application of audio fingerprinting of short utterances.”
LDC Executive Director Chris Cieri says
“The Consortium continually looks for new ways to integrate speech technology into data collection and annotation processes to improve speed, scale and quality while avoiding bias. We are excited by the increased capability that OWR tools offer.”