In my youth, I would experiment with different baseball swinging mechanics to find the right combination to hit a ball over the outfield fence. Today, as a scientist, I’m tweaking experiment variables such as microphone gain stages to optimize audio performance of acoustic systems. Over the years, I have found one thing to be consistent... the more absolute the truth, the more difficult it is to prove.

Absolute truth requires experimentation and a large amount of data. Every company and team that I’ve been on have unique strategies to conduct experiments, collect and manage their data. Herein lies two of my biggest frustrations over my decade-plus experience: inconsistency that leads to re-invention.

Engineers and scientists like myself are tired of burying ourselves in spreadsheets, rewriting code, double-checking other colleagues' work, and wasting their talents on clerical tasks such as finding, reorganizing, and renaming files.

Most of my early test validation work at Amazon Lab126 was squandered, chasing down who had worked on similar experiments in the past, where data and equipment could be found, and creating/sharing results with colleagues to produce insightful project direction. I still recall very vividly having to fly to China to set up a test station at a factory, just because there was a discrepancy in calibration.

Therefore, I’ve built the Lyceum. The Lyceum is a software application where scientists, system engineers, and research and development teams can store and post-process large amounts of data, then collaborate with teammates and/or other professionals on project problems.

Currently, the Lyceum can functionally service audio systems engineers in the product development process. It ingests measurement data from software such as Listen Soundcheck or Audio Precision APx, and provides users the ability to graph/visualize, calculate statistics, and generate yield numbers from a manufacturing build. For example, when a company is developing a product to go-to-market, it's often required to baseline the product's performance against its competition. An audio engineer does this by evaluating a metric, such as frequency response, of a speaker they’re developing to current speakers being sold.

So, when a team is developing a product called the “Speaker X,” their requirements are that it performs louder and more clearly than “Speaker Y” and “Speaker Z.” In order to establish a baseline target, they develop a measurement experiment to acquire data of the frequency responses of all three speakers.

After the data is acquired, a user can upload it to the Lyceum via the data ingestor. The data ingestor attaches descriptions, permissions, and even cleans the data properly to be used in post-processing in the future.

Post-process is where the analysis happens. This is handled by the Lyceum by creating a working session, whereby multiple users can access the data and post-processing applications.

The functional applications the Lyceum currently offers will be supplemented by additional tools for more advanced post-processing, as well as contributions by the Lyceum community. The community will be able to submit and use their own data-processing scripts/apps, further enhancing the platform’s capabilities.

Over the course of three days and two nights, June 8–10, the Audio Engineering Society’s 2022 International Automotive Audio Conference in Dearborn, MI, served as a great event for everyone in the automotive audio community to reconnect. The event also featured a full track of sessions promoted by the AES Audio Product Education Institute (APEI). This report, written by Roger Shively, the AES Conference Chair, reviews the most important presentation topics discussed and the exciting demonstrations by companies such as Dolby, Fraunhofer, Dirac, Tymphany, and DSP Concepts, among many others. This article was originally published in audioXpress, September 2022. Read the Full Article Now Available Here

James Croft continues to explore the patents that have been filed and granted to Dutch company Mayht Holding B.V., the startup that was recently acquired by Sonos for $100 million. Having previously reviewed one of the early Mayht patents covering their general bipolar, interleaved multiple motor structure architecture, this article reviews the "Linear Motor Magnet Assembly and Loudspeaker Unit" patent (2022/0191621), which was granted to Timothy Ruben Scheek (Amsterdam, NL) on behalf of Mayht. This patent is the company's most recent US publication (June 16, 2022), which addresses the most dramatic claim for the Mayht transducer technology of the ability to allow a contravention of Hofmann’s Iron Law and provide a greater-than 10x reduction in enclosure volume, while maintaining the same efficiency and bandwidth as compared to the current state of the art. This article was originally published in Voice Coil, August 2022.  Read the Full Article Now Available Here