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Transient automotive sounds often possess a complex internal structure resulting from one or more impacts combined with mechanical and acoustic cavity resonances. This structure can be revealed by a new technique for obtaining translation-invariant scalograms from orthogonal discrete wavelet transforms. These scalograms are particularly well suited to the visualization of complex sound transients which span a wide dynamic range in time (ms to s) and frequency (∼100Hz to ∼10kHz). As examples, scalograms and spectrograms of door latch closing events from a variety of automotive platforms are discussed and compared in light of the subjective rankings of the sounds.

In this paper, an approach to analyze voice recognition data to understand how customers use voice recognition systems is explored. The analysis will help identify ASR failures and usability related issues that customers encounter while using the voice recognition system. This paper also examines the impact of these failures on the individual speech domains (media control, phone, navigation, etc.). Such information can be used to improve the current voice recognition system and direct the design of future systems. Infotainment system logs, audio recordings of the voice interactions, their transcriptions and CAN bus data were identified to be rich sources of data to analyze voice recognition usage. Infotainment logs help understand how the system interpreted or responded to customer commands and at what confidence level.

The work presented here is part of the research done in the field of voice biometrics. This paper helps to understand the state-of-the-art in speaker recognition technology potentially capable of solving challenges related to speaker identification (to identify a speaker among multiple speakers) and speaker verification/authentication (to recognize the current speaking person at a pre-defined access level and authenticate accordingly). The research was focused on performing an unbiased evaluation of two individual voice biometric services. The level of accuracy in identifying and authenticating individuals using these services provides an insight into the current state of technology and the state of what other dual authentication methods could be used to achieve a desired True Acceptance Rate (TAR) and False Acceptance Rates (FAR).

The following document is a set of guidelines intended to be used as a reference for the practicing automotive sound quality (SQ) engineer with the potential for application to the field of general consumer product sound quality. Practicing automotive sound quality engineers are those individuals responsible for understanding and/or conducting the physical and perceptual measurement of automotive sound. This document draws upon the experience of the four authors and thus contains many “rules-of-thumb” which the authors have found to work well in their many automotive related sound quality projects over the past years. When necessary, more detailed publications are referenced. The intent of publication of this document is to provide a reference to assist in automotive sound quality work efforts and to solicit feedback from the general sound quality community as to the completeness of the material presented.

Customer annoyance of steady-state wind noise correlates well with loudness. A common objective metric to capture average loudness is the ISO532B or Zwicker method. However, it has been shown previously that time-varying wind noise can also significantly affect customer annoyance, independent of average loudness. Causes of time-varying wind noise include wind buffeting generated by other vehicles, and also wind gusting. This paper summarizes the development of an objective metric that correlates well with subjective impressions of wind gusting/buffeting. The model is based on a general impulsive noise model with parameters tuned specifically for time-varying wind characteristics. The model consists of a psychoacoustic processing stage followed by a gusting detection stage, where the psychoacoustic stage is extracted from a time-varying loudness model. The output of the gusting model is a time series that indicates the location and “intensity” of wind gusts.

Transient road disturbances excite complex vehicle responses involving the interaction of suspension/chassis, powertrain, and body systems. Typical ones are due to the interactions between tires and road expansion joints, railway crossings and other road discontinuities. Such transient disturbances are generally perceived as “impact harshness” due to the harshness perception as sensed by drivers through both sound and vibration. This paper presents a study of quantifying the effects of sound, steering wheel and seat/floorpan vibrations on the overall perception of the “impact harshness” during impact transient events. The Vehicle Vibration Simulator (VVS) of the Ford Research Laboratory was used to conduct this study. The results of the study show that sound and vibration have approximately equal impact on the overall perception of impact harshness. There is no evidence of interaction between sound and vibration.