Automotive Papers - Listen, Inc.

Overcoming Challenges of Measuring Distortion Audibility in Automotive Audio Systems

August 13, 2026/in Automotive Papers, Blog, Papers/by Zarina

Standardized measurement of in-car audio systems remains an ongoing challenge, particularly regarding microphone configuration and placement, test signals, and correlation with perception. Current recommendations from the AES Technical Committee on Automotive Audio (TC-AA) advocate spatial averaging using multi-microphone arrays to improve repeatability.

While this method reduces the influence of reflections and standing waves to improve frequency magnitude measurement consistency and repeatability, it limits frequency, phase and amplitude resolution, which help identify the root causes of the distortions and evaluate their perceptual impact. An alternative approach is to apply frequency-normalized distortion analysis, where reflections or standing waves in the frequency response are also echoed in the distortion results, and greatly reduced by direct comparison of the two measurements. In this paper, spatial averaged distortion measurements using the TC-AA recommended 6 microphone array are compared with normalized distortion calculations, and a single microphone capture using the normalized distortion method.

Buzz, Squeak & Rattle (BSR) measurements otherwise known as Rub & Buzz or Impulsive Distortion measurements are also challenging. The TC-AA recommends a crest factor algorithm, available in a few audio measurement systems. This adequately detects transient distortions, but is susceptible to background noise, therefore requires a tightly controlled environment for making measurements. Two other methods, enhanced perceptual Rub & Buzz and enhanced Loose Particles offer improved repeatability in the presence of background noise, and the results are easier to correlate to audibility. The three methods are compared, both in a quiet environment, and with background noise.

Author: Steve Temme, Listen, Inc.
Presented at the AES Automotive Conference (July 2026) Detroit, Michigan

Full Paper

Overview

This paper investigates improved methods for measuring audible distortion in automotive infotainment systems. Traditional Total Harmonic Distortion (THD) measurements are often compromised by vehicle cabin reflections and standing waves, making it difficult to distinguish genuine loudspeaker distortion from acoustic artifacts. The paper demonstrates that Frequency-Normalized Total Harmonic Distortion (nTHD) produces more accurate and perceptually meaningful results than conventional THD, while also reducing measurement complexity and cost.

Key Findings

Frequency-normalized THD (nTHD) largely removes the effects of cabin reflections by comparing harmonics with the fundamental at the same measured frequency before calculating distortion.
nTHD produces clearer distortion measurements than conventional THD and more accurately identifies the true source of distortion.
A single microphone using nTHD closely matches measurements obtained from the AES TC-AA recommended six-microphone array, suggesting a practical lower-cost solution for production-line testing.
For Buzz, Squeak and Rattle (BSR) measurements, traditional Crest Factor analysis is susceptible to background noise.
Two alternative techniques—Enhanced Perceptual Rub & Buzz (ePRB) and Enhanced Loose Particles (eLP)—provide better repeatability, improved noise immunity, and stronger correlation with what listeners actually hear.

Why It Matters

Automotive audio systems are measured in highly reflective environments where conventional distortion measurements can misinterpret reflections as loudspeaker defects. Frequency-normalized distortion separates linear acoustic effects from true nonlinear distortion, allowing engineers to identify problems more accurately. The paper also shows that perceptually based distortion measurements better reflect human hearing and remain reliable in noisy environments such as vehicle production facilities.

Applications

The techniques described are particularly valuable for:

Automotive infotainment system development
End-of-line manufacturing testing
Loudspeaker quality assurance
Diagnosis of Buzz, Squeak and Rattle (BSR)
Production environments requiring faster, lower-cost acoustic measurements

Conclusion

The paper concludes that frequency-normalized THD provides a more accurate representation of audible distortion than conventional THD in vehicle cabins. Combined with perceptually based Rub & Buzz and Loose Particle measurements, it offers improved correlation with listener perception, greater immunity to background noise, and the potential to replace expensive multi-microphone measurement systems with a single microphone for many automotive production applications.

Standardized Automotive Audio Measurements

November 14, 2024/in Automotive Papers/by Zarina

Since 2020, the Audio Engineering Society Technical Committee on Automotive Audio (TC-AA) has worked on developing an equipment specification and test methodology for in-car acoustic measurements that will ensure repeatable measurements, allow comparisons, and improve interpretation of results. This will make system-level specifications and requirements more meaningful and facilitate alignment between vehicle manufacturers (OEMs) and Tier 1 suppliers. In this paper, the TC-AA recommendations are demonstrated. The same test configuration is then used to demonstrate an extended suite of measurements that provides a more complete characterization of automotive audio. Measurements demonstrated in this paper include frequency response, seat-to-seat spectral uniformity, THD, intermodulation distortion, overall Max SPL, Max SPL at 10% distortion, and impulsive distortion.

Author: Steve Temme, Listen, Inc.
Presented at 9th ISEAT Conference (November 2024) Shenzhen, China

Full Paper

Summary

Standardized Automotive Audio Measurements

This paper by Steve F. Temme discusses a suite of measurements designed to characterize automotive audio systems. Temme’s work builds upon the Audio Engineering Society (AES) Technical Committee on Automotive Audio (TC-AA) White Paper, a document aiming to standardize in-car acoustic measurements.

The TC-AA white paper emphasizes several key aspects of measurement:

Repeatable measurements, enabling accurate comparisons between different vehicles and systems.
Clear interpretation of results, leading to more meaningful system-level specifications.
Better alignment between vehicle manufacturers (OEMs) and Tier 1 suppliers, improving communication and collaboration.

Measurement Methods: The paper examines a range of measurements, including:

Frequency response: This fundamental measurement assesses the system’s tonal balance by analyzing its output across the audible frequency range.
Spectral uniformity: This measures how evenly sound is distributed across different seating positions, ensuring a consistent listening experience for all passengers.
Distortion (THD, intermodulation): These measurements evaluate the system’s linearity, revealing potential issues like a poorly centered voice coil or crossover problems.
Maximum SPL: This quantifies the system’s maximum volume, offering a valuable metric for both manufacturers and consumers.
Impulsive distortion: This test identifies vibrations or rattles caused by speakers, ensuring the system’s proper installation and build integrity.

Test Setup: The paper describes a practical test configuration utilizing a six-microphone array, following the TC-AA recommendations. The setup includes:

SoundCheck audio test system: Used for analysis and control.
AmpConnect 621 audio interface: Converts microphone signals for the software.
BQC-4149 Bluetooth interface: Transmits test signals to the car’s head unit.

Calibration: Accurate calibration is crucial for reliable results. This involves measuring microphone sensitivity with a calibrator and calibrating the audio interface for precise frequency and level responses.

The paper concludes by highlighting the increasing complexity of modern car audio systems and the need for standardized measurements. The TC-AA White Paper aims to establish a foundation for objectively evaluating these systems, facilitating comparisons and driving industry-wide improvements. The authors encourage feedback from the automotive audio community to refine the proposed methodologies and ultimately lead to a standardized industry approach.

Enhanced Perceptual Rub & Buzz Measurement for Testing Automotive Loudspeakers

July 6, 2022/in Algorithm Papers, Automotive Papers, Papers/by Zarina

Loudspeaker Rub & Buzz faults are a problem for automotive manufacturers as they sound harsh and immediately give the perception of poor quality. There are two places such faults can occur – during speaker manufacturing and installation of the speaker in the car. A buzzing loudspeaker in a car is disappointing to a customer and is costly to replace. It is also challenging for a service center to determine exactly where the buzzing is coming from and whether it is caused by a faulty loudspeaker or bad installation. Perceptual distortion measurements are often considered the holy grail of end-of-line testing because rejecting speakers with only audible faults increases yield. Although such measurements have been around since 2011, production line adoption has been slow because until now, sensitivity to background noise has made limit-setting challenging. In this paper, a new algorithm is introduced that uses advanced technology to reduce the impact of background noise on the measurement and offer more repeatable results. This facilitates limit setting on the production line and makes it a truly viable production line metric for increasing yield. This same metric may also be used for end-of-line automotive quality control tests. Results from various algorithms will be shown, and their correlation to subjective and other non-perceptual distortion metrics explained.

Author: Steve Temme, Listen, Inc.
Presented at 2022 AES Automotive Conference, Dearborn, MI

Full Paper

Introduction

The automotive industry’s stringent quality expectations make end-of-line quality testing on automotive speakers and drivers absolutely critical. End-of-line tests typically measure a range of parameters including frequency response, THD, and polarity. Manufacturing-introduced defects such as Rub & Buzz and Loose Particles are also measured. Reliable, automated testing has been available for decades now, and most large manufacturers rely on these software-based systems for identification and rejection of defective products. While these tests do an excellent job of identifying defective units, there is always a certain level of false rejection where units with some distortion fail even though it is completely inaudible to the human ear. From a manufacturing perspective, higher yields and therefore greater profitability is always desirable.

Perceptual Distortion Measurements

This has driven the development of perceptual distortion measurements – automated measurements that replicate the human hearing to detect only audible distortion defects. Such metrics increase production line yield by passing products with inaudible distortion, as the product will still sound exactly as the manufacturer intended. Perceptual methods are very simple to configure for production line use. Since they return a result in Phons, an absolute measurement that can be easily correlated to the listener’s threshold of hearing, the operator can set a fixed limit across the board, regardless of product. Naturally, the price point and quality expectations for the product may influence the level of distortion that is deemed acceptable.

Perceptual Distortion Algorithms

Our algorithm, introduced in 2011, was the first commercial perceptual distortion metric, although in the past couple of years, other test system manufacturers have also started to offer perceptual distortion tests. It offers excellent correlation with human hearing and performs well in laboratory tests. However, like the human ear, repeatability decreases in the presence of background noise. This is not a failure of the algorithm as such, but an indication that the algorithm performs just like a human listener; when background noise is high, audible distortion is masked. This limitation restricts the value of such algorithms on the production line, as with today’s high-volume manufacturing, there is only time for one fast test sweep. If this sweep gets a different result under changing background noise conditions, limit setting becomes challenging, and repeatability and reliability is decreased. Similar algorithms from other test system manufacturers also suffer from the same problems.

New Perceptual Distortion Algorithm Development

This paper details efforts to create an algorithm that hears like a human in quiet conditions, e.g. in a living room or passenger automotive cabin, under the less-than-perfect conditions of a manufacturing environment where considerable and varying background noise may be present. In other words, a perceptual model that is more independent and reliable than the human ear when it comes to noisy environments. The resulting new algorithm overcomes these limitations to offer repeatable end-of-line test results, even in noisy environments. It incorporates noise reduction techniques and enhanced perceptual filters to overcome the reliability and high frequency masking issues of earlier versions. In short, the algorithm offers the performance of an ‘enhanced’ human ear – it detects distortion like an ear in a quiet environment, even when there is background noise. This makes it a viable solution for production line use.

In this paper we explain how the algorithm works, demonstrate how the results compare with earlier perceptual algorithms and show its correlation with human hearing and conventional distortion algorithms. We also compare its performance in the presence of background noise to other perceptual algorithms by adding recorded factory background noise to the signal before passing it through the algorithms.

More about Listen’s enhanced Perceptual Rub & Buzz algorithm

More about in-car measurement of impulsive distortion / Buzz, Squeak and Rattle.

Testing Voice-Controlled & Smartphone Integrated Infotainment Systems

September 20, 2019/in Automotive Papers, Papers, Smart Device Papers/by Zarina

A tutorial and accompanying paper on testing infotainment systems that was presented at the AES Automotive Conference, Sept 11-13, 2019, Neuburg an der Donau, Germany.

Voice-controlled and smartphone integrated vehicle infotainment systems are notoriously complex to test. They have numerous connections from wired to wireless and contain much signal processing, both on the record and on the playback side. This means that their characteristics change according to ‘real world’ conditions of the vehicle’s environment, including cabin acoustics and background noises from road, wind and motors. Furthermore, their multifunctional nature means that there are many aspects of the device that may need to be tested, ranging from voice recognition to music playback and operation as a hands-free telephone. Due to their complex non-linear use cases, these devices often need to be tested at different levels and different environmental conditions.

This tutorial offers practical hands-on advice on how to test such devices, including test configurations, what to measure, the challenges of making open-loop measurements, and how to select a test system.

Download presentation (slides)

Download accompanying paper

Paper Introduction

Audio Tests for Infotainment Systems

Infotainment systems have become increasingly challenging to test. They have many possible interfaces; hard-wired or auxiliary input, radio, CD, memory card, hard drive, USB, Bluetooth, smartphone (including Apple CarPlay and Android Auto) and even voice. They contain much signal processing, both on the record side (e.g. beamforming, background noise filtering, voice activity detection, and on the playback side (e.g.loudness, compression, equalization, and active noise cancellation). Some even have wake word detection, e.g. “Hey Siri”, “OK Google”, and “Alexa”. Due to their complex non-linear use cases, these devices often need to be tested at different levels and in different environmental conditions, for example with different background noises and different test signals. To further complicate matters, the test signal may need to be in the cloud to enable playback for testing voice recognition systems. Each manufacturer’s ecosystem is different in how it plays and records.

Smartphone integrated infotainment systems usually require an internet connection with voice services in order to process commands. On the playback side, some enable you to upload your own recordings such as iTunes (although bear in mind that these will probably be compressed). Others require them to be on a media streaming platform such as Spotify. For microphone testing, some systems such as Alexa allow access to recordings made; others do not for security and privacy reasons, which makes microphone testing challenging. Although the actual physical testing setup is very similar from vehicle to vehicle, for each it is necessary to understand how to wirelessly route the signal. Furthermore, each device needs activating with a different wake word, needs different delay compensation, and records for a different amount of time after it hears the wake word. This needs figuring out (largely by trial and error) for each infotainment system that you need to test.

Infotainment System Testing Standards

Although, there are currently no standards for testing infotainment systems with smartphone integration, principles and test configurations can be borrowed from many other audio devices and use existing standards such as IEC for loudspeakers, IEEE/TIA/ITU for speakerphones, and ETSI for background noise. Flexibility of the test system and experience with testing a wide range of acoustic devices is critical to enable a device to be completely characterized. This paper focuses on how to implement basic acoustic tests and some of the more complex real-world tests along with the techniques and standards that may be used.

The rest of the paper covers:

Basic Acoustic Tests

Advanced or ‘Real World’ Testing of Infotainment Systems

Speech Recognition

Background Noise

Voice Quality

Measurement System Requirements

Full Paper

More about testing infotainment systems.

Evaluation of Audio Test Methods and Measurements for End-of-Line Automotive Loudspeaker Quality Control

May 23, 2017/in Automotive Papers, Loudspeaker Papers, Papers, Production Papers/by Zarina

In order to minimize costly warranty repairs, automotive manufacturers impose tight specifications and a “total quality” requirement on their part suppliers. At the same time, they also require low prices. This makes it important for automotive manufacturers to work with automotive loudspeaker suppliers to define reasonable specifications and tolerances, and to understand both how the loudspeaker manufacturers are testing and also how to implement their own measurements for incoming QC purposes.

Specifying and testing automotive loudspeakers can be tricky since loudspeakers are inherently nonlinear, time variant and affected by their working conditions & environment which can be change dramatically and rapidly in a vehicle. This paper examines the loudspeaker characteristics that can be measured, and discusses common pitfalls and how to avoid them on a loudspeaker production line. Several different audio test methods and measurements for end-of-the-line automotive speaker quality control are evaluated, and the most relevant ones identified. Speed, statistics, and full traceability are also discussed.

Authors: Steve Temme, Listen, Inc. and Viktor Dobos, Harman/Becker Automotive Systems Kft.
Presented at the 142nd AES Convention, Berlin, Germany

Full Paper

In-Vehicle Audio System Distortion Audibility versus Level and Its Impact on Perceived Sound Quality

December 15, 2016/in Automotive Papers, Distortion Papers, Papers/by Zarina

As in-vehicle audio system output level increases, so too does audio distortion. At what level is distortion audible and how is sound quality perceived as level increases? Binaural recordings of musical excerpts played through the in-vehicle audio system at various volume levels were made in the driver’s position. These were adjusted to equal loudness and played through a low distortion reference headphone. Listeners ranked both distortion audibility and perceived sound quality. The distortion at each volume level was also measured objectively using a commercial audio test system. The correlation between perceived sound quality and objective distortion measurements is discussed.

Authors: Steve Temme, Listen, Inc. and Patrick Dennis, Nissan Technical Center North America, Inc.,
Presented at the 141st AES Convention, Los Angeles, CA 2015

Full Paper