Search Results

The paper presents the concepts and applications regarding Articulation Index (AI) that is widely used in the automotive industry as a powerful parameter to qualify/quantify the middle and high frequency spectra associated to the internal noise of vehicles. We are able to show a short historical review including the today used definitions and calculations based in third octave band spectra through and idealized speech region model like our pioneer Brazilian standard. We show also other applications, where AI can be an excellent tool to evaluate vehicle acoustics. We emphasize the relation of AI to Speech Intelligibility and make considerations concerning other factors influencing Intelligibility. In addition we comment the integration we have produced with an overall noise parameter like dB(A) - (H-index) and the proposition of an AIM - Articulation Index Modified.

The interior noise of automotive vehicles is basically composed by two portions. The structureborne sound through the elastic moutings, which is characterized by the low frequencies and the airbornesound through the divisory between the engine compartment and passenger compartment. This last path is mainly traveled by the high frequencies. We show the low frequencies, specially those related to the explosion order make the composition of the overall sound level, when the noise is evaluated by a weighting curve, trying to simulated the ear response, as for example the curve “A”, from which originates the well familiar dB(A). The highest frequencies, although almost ever, are neglected by the weighting curve “A”, are very important when we see the communication aspect in the passenger compartment. To solve this, we use another parameter, calculated from physical measurements and named Articulation Index (Al). We show its association with the highest frequencies.