Know how your product sounds, with evidence.
Practical, research-grade audio evaluation for teams building headphones, speakers, voice, immersive, and AI-driven audio.
Listening test design & analysis
Plan and run blind listening tests that give clear, repeatable answers.
- MUSHRA, BS.1116, ABX / paired comparison, MOS, attribute ratings
- Stimulus selection, listener screening, and test setup
- Statistics: confidence intervals and significance tests
- Plain-language report with a clear recommendation
AI & objective metric evaluation
Find out which quality metrics you can trust, and for what.
- Benchmark objective and AI-based metrics against listener ratings
- Identify where metrics fail for your content and use case
- Data-driven evaluation pipelines in Python
- Guidance on when a metric can replace a listening test
Perceptual targets & acceptance criteria
Define what "good" sounds like in terms engineering can build to.
- Perceptual attribute frameworks (sound profiles)
- Pass/fail thresholds tied to objective measurements
- Certification and regression test design
- Tuning guidance for field and customer teams
Competitive benchmarking
See how you stack up before your customers decide for you.
- Benchmark sets with competitor and reference devices
- Reusable scoring templates and scorecards
- Release-by-release tracking
- Go/no-go recommendations for leadership
Listening room & lab setup
Get reliable results from your listening space.
- BS.1116 compliance review and renovation guidance
- Test library: curated clips, test signals, reference recordings
- Repeatable procedures and playbooks
AI & technology adoption advisory
Bring AI into your evaluation workflow without losing rigor.
- Where AI saves time, and where human listeners still matter
- AI-assisted analytics tools and dashboards
- Process design so results stay trustworthy
A simple process
Discovery call
We talk through your product, the question you need answered, and your timeline.
Plan & test
I design the evaluation, run it (or guide your team), and analyze the results.
Clear answers
You get a plain-language report, the data, and a recommendation you can act on.
Areas of focus
- Headphones
- Loudspeakers
- Voice & dialogue
- Immersive / spatial audio
- Adaptive audio
- Codecs
- Automotive audio
- Audio AI/ML
Have a product that needs to sound right?
Or a team that needs a perceptual audio lead? Either way, let's talk.