Signal processing for in-car communication systems
Introduction
In limousines and vans communication between passengers in the front and in the rear may be difficult—especially if the car is driven at medium or high speed, resulting in a large background noise level. Furthermore, driver and front passengers speak toward the windshield. Thus, they are hardly intelligible for those sitting behind them. To improve the speech intelligibility the passengers start speaking louder and lean or turn toward the listening communication partners. For longer conversations this is usually tiring and uncomfortable.
Another way to improve the speech intelligibility within a passenger compartment is to use an in-car communication system [1], [2]—often shortly called intercom system. Those systems record the speech of the speaking passengers by means of microphones and improve the communication by playing the recorded signals via those loudspeakers located close to the listening passengers. Fig. 1 sketches the structure of a simple car interior communication system aimed to support only front-to-rear conversations with one microphone and one loudspeaker.
As it is clearly visible in Fig. 1, intercom systems operate in a closed electro-acoustic loop. The microphone picks up at least a portion of the loudspeaker signal. If this portion is not sufficiently small sustained oscillations appear—which can be heard as howling or whistling. The howling margin depends on the output gain of the intercom system as well as on the gains of the analog amplifiers and . For this reason all gains within the system need to be adjusted carefully.
To improve the stability margin signal processing, such as beamforming, feedback and echo cancellation, adaptive notch filtering, adaptive gain adjustment, equalization, and nonlinear processing can be applied. A few basic processing units are already depicted in Fig. 1.
Before we will describe the signal processing units in more detail in Section 3, we will discuss the boundary conditions we have to fulfill when designing communication systems for passenger compartments in the next section. In contrast to hands-free telephones or speech recognition engines no methods for evaluating the quality of intercom systems have been standardized or even published yet.1 Thus, evaluation is not as easy as in other speech and audio applications. However, a few measurements (binaural recordings) as well as subjective tests (performed in a car equipped with an intercom system) are presented at the end of this contribution.
Section snippets
Basics
When designing an intercom system a variety of boundary conditions and system demands will appear. In order to understand the origin of these demands a few—mostly physical or psychoacoustic—phenomena will be described within this section. Furthermore, models for all important transmission paths are introduced. This allows to give a first motivation for a few signal processing units, such as feedback cancellation and beamforming.
Signal processing for intercom systems
Fig. 10 sketches the structure of an intercom system aimed to support front-to-rear conversations (for the other direction a similar structure is applied). Compared to the basic system depicted in Fig. 1 now much more details are covered. Since driver and front passenger are located at well defined positions, fixed microphone arrays can point towards each of them requiring fixed beamformers only. This allows to start with the echo and feedback cancellation after the beamformer (and to reduce
A real system
Fig. 21 shows the results—in terms of a binaural recording—of a car interior communication system. The system utilizes eight microphones (two per passenger) and six loudspeaker channels (standard car loudspeakers). To obtain high speech intelligibility the algorithms described in Section 3 were applied. Especially at higher speed (90 km/h or more) a clear improvement of the communication quality could be achieved.
Subjective tests in terms of comparison mean opinion scores (CMOS) indicate a clear
Conclusions and outlook
In this paper the basic signal processing components of an in-car communication system have been described. Even if most algorithms are already known for other applications such as hands-free telephones, public address system, or hearing aids, the specific conditions in which intercom systems have to operate require several modifications of the standard algorithms. For this reason the boundary conditions have been described in detail at the beginning of this contribution.
Undoubtedly, in-car
Acknowledgements
The authors would like to thank Markus Buck, Marcus Hennecke, and Hans-Jörg Köpf from the research division of Harman/Becker/Temic for carefully reading and improving the manuscript.
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