For about 60 years, the spectrogram has been an excellent visualization tool for observing the acoustic and prosodic features of a speech signal. However, a visual tool has been lacking for information that is typically represented by the speech signal's phase. When a talker is remote from one or more microphones, the times of arrival of the direct wave and those of reflections become important. In this letter, we introduce two visualizations that have proven to be quite useful for us in understanding phasic behaviors of microphone arrays. A time delay versus frequency plot for a window of time is called the time-delay graph, and an ensemble of projected time-delay graphs is called the delayogram. These visualizations are introduced, and simulated and real-speech data examples of both displays are presented. The time-delay graph is compared to the phase transform generalized cross-correlation (GCC-PHAT) for two real-data examples.

Large-aperture microphone arrays have the potential for providing quality speech acquisition from multiple talkers over a large focal area for such applications as teleconferencing and speech-recognition input. The cost of computing is rapidly approaching the point at which these arrays will be practical in many common environments. However, an important issue is the calibration of an array. We discuss procedures to accurately determine both the coordinates in three-dimensions for the position of each microphone and the individual gains of each microphone/microphone channel. For the positions, we found that calibration by direct measurement, using a surveyor's transit, is simply too error prone, time consuming, and difficult for large arrays and is too inaccurate for small arrays. We have also seen that without the careful matching of inexpensive electret microphones, the channel sensitivities vary by as much as 6 dB and performance can be enhanced by suitable compensation. This paper describes new apparatus and techniques for automatic calibration using acoustic signals. Experimental results using both small and large-aperture microphone array systems show the acoustically-determined positions to be more consistent than the ones measured directly. Gain measurements are somewhat more difficult but gains can be found within 1-2 dB with reasonable care.

A large array of microphones is being studied as a possible means of acquiring data in offices, conference rooms, and auditoria without requiring close-talking microphones. An array that surrounds all possible sources has a large aperture and such arrays have attractive properties for accurate spatial resolution and significant signal-to-noise enhancement. For the first time, this paper presents all the details of a real-time, source-location algorithm (LEMSalg) based on time-of-arrival delays derived from a phase transform applied to the generalized cross-power spectrum. It is being used successfully in a representative environment where microphone SNRs are below 0 dB. We have found that many small features are required to make a useful location estimating algorithm work and work well in real-time. We present an experimental evaluation of the current algorithm's performance using data taken with the Huge Microphone Array (HMA) system, which has 448 microphones in a noisy, reverberant environment. Using off-line computation, we also compared the LEMSalg to two alternative methods. The first of these adds local beamforming to the preprocessing of the base algorithm, increasing performance significantly at modest additional computational cost. The second algorithm maximizes the total steered-response power in the same phase transform. While able to derive good position estimates from shorter data runs, this method is two orders of magnitude more computationally expensive and is not yet suitable for real-time use.

We have shown that knowing the orientation of a talker in a large-aperture microphone array system can significantly improve location-estimation and beamforming algorithms. Measurements of a talker in an anechoic chamber have shown significant anisotropy in radiation patterns that may be used to influence the selection, processing, and weighting of microphone signals in such algorithms. We introduce a simple method for determining the orientation of a talker within a large focal area using only acoustic energy data obtained from the array. The mathematical basis for this procedure is presented and computed performance, based solely on acoustical measurements in a real environment, are listed and discussed.

Large-aperture microphone arrays have the potential for providing quality speech acquisition from multiple talkers over a large focal area for such applications as teleconferencing and speech-recognition input. The cost of supporting computing technology is quickly approaching the point in which these arrays will be practical in many common environments. However, an important issue is the calibration of an array that has been instal1ed in some medium-sized to large room. By calibration, we mean the determination of the precise set of coordinates in three-dimensions for the positions of the microphones. Calibration by direct measurement or even by a 'laser transit is simply too error-prone, time-consuming and painful. This paper describes new apparatus and techniques for automatic calibration using acoustic signals. Experimental results using our large-aperture microphone array system show the automatical1y-determined positions to be even more consistent than the ones measured directly. The paradigm for using the apparatus and technique most advantageously is also presented.

Microphone arrays offer the potential of obtaining a high-quality speech signal from a remote talker in a noisy, multi-source environment. In many important applications, sources of interest may be located anywhere within a large focal area and thus it is desirable that an array's performance be uniform over that area. In this paper, simulated and measured results are presented indicating the performances of representative small and large aperture arrays at various points in a large focal area. From these results, it is clear that uniformity over a large focal area is an advantage of large-aperture arrays.

Poor sound pick up by remote microphones in multimedia applications, conference rooms and auditoria has traditionally hampered speech recognition and communication among spatially-separated groups. The problems are reverberation, acoustic noise, and the variability of the radiation pattern of unconstrained talkers. One potential solution that is becoming increasingly practical is to use an array of microphones and sophisticated signal processing. In this paper a brief description of a large, real-time, working system is presented and its measured beamforming performance is compared to what is predicted from a mathematical model. A combination of a synchronized test signal/system and a careful mathematical model results in the performances matching surprisingly well. From this match of theory to practice, we are able to draw some important inferences about future system improvements.