Microphone Array and Beamforming - Forward麦克风阵列波束形成了

1、Microphone Array and BeamformingBy Pattarapong RojanasthienECE 5525Dr. KepuskaDecember 8th, 2008OverviewIntroductionBackgroundMicrophone ArraysBeamformingSignal to Noise RatioSolution and ApproachResultsConclusionIntroductionThe goals for the project are the followingLearn the basic concept of micro

2、phone arrayBecome familiar and learn how to use a program that perform BeamformingShow that Beamforming will enhance the signal quality based on SNRMicrophone ArrayMultiple microphones set up in certain formation depend on the application.LineCircleRectangleEach microphone will capture the sound fro

3、m the source at the different time due to distance from the source.Therefore, there is a time delay in each signal.Microphone ArrayMulti-Channel Signal ComparisonTime DelayNote that the distance between another microphone (not the reference) to the source, which denote as g, can be compute with trig

4、onometry cos = d/g = d = g cos. The distance from source to Ref Mic: d = 30 in.The distance from source to Mic x: g = 34.73 in.The distance between mic: N = 17.5 in.Sampling Frequency: fs = 22050 samples/sec.Speed of sound: c = 345 m/sec.Find d = 34.73 30 = 4.73.Find Sample/meter = 22050/345 = 63.91

5、3 samples/m.Turn into inches = 63.913 x 0.0254 = 1.62To find time delay, we need distance d x = 4.73 x 1.62 = 7.7 samples, round up to be 8 samples.Example of Microphone ArrayBeamformingA technique that rearrange the mixture signals from the microphone array, so that the signals from the source that

6、 we want are lined up before combine them all up into one signalSince signals from the specified source are on the same phase, they will add each other up.The noise signals may either add each other up or cancel each other out. The general form of the beamforming output based on delay and sumBeamfor

7、ming PatternSignal to Noise RatioThe measurement of the signal qualityBasically, it is the magnitude of One way to calculate it is to find noise from voice activity detection1.Measure the mean of the energy during the last t1 seconds = E12.Measure the mean of the energy during the last t2 seconds =

8、E23.Calculate the speech threshold T2 = E2 + Ex4.If E1 Ts, speech is detected. (speech onset) 5.Freeze E2 and calculate the noise threshold Tn = E2 + En6.Measure the mean of the energy of recent t1 seconds = E17.IF E1 Tn, noise is detected. (speech offset)signalnoiseVoice Activity DetectionUse the a

9、verage energy compute from two windows size. One windows is smaller than another another.ExperimentUse the microphone array data recorded by Tom Sullivan at Carnegie Mellon University.The data will be converted into wavefiles for each channel using MATLAB.Put the wavefiles into BeamformIt to perform

10、 beamforming. The output is in form of NIST .sph file. Convert it back to .wav using the program sox.Take the result back into MATLAB and compare the SNR with the signals from microphone array.Resultsan102-mtms-arr4A.adc Source of SignalSNRMic 121.00937389Mic 222.48577961Mic 322.80745788Mic 425.4994

11、5084Mic 523.06647821Mic 626.87451164Mic 724.8231068Mic 821.54103218Mic 920.9528169Mic 1023.69206855Mic 1124.28739145Mic 1223.09365172Mic 1320.78050523Mic 1420.96611645Mic 1520.77844073Result from Beamforming46.79534715Results (contd)The average SNR of 15 microphone is about 22.84 dB, which the beamf

12、orming result is roughly twice higher than that.Also look at the spectrogram of the the raw data and beamforming data respectively.Note that the noise energy is reduced.ConclusionBy beamforming the signals from the microphone array, we can enhance the quality of the signal that we want by rearrange

13、the microphone array signals together and combine up into one signal.The most difficult part of this project is rather on the technicality (convert and compile the programs) rather than understanding the general concepts behind it.Special ThanksDr. Kepuska and Za Hniang Za for guidance on the concep

14、ts and MATLABReferencesAcoustic Beamforming for Signal Enhancement, Localization, and Separation. Kung Yao. DARPA Air-Coupled Acoustic Sensors Workshop Aug 24. 1999. /mto/archives/workshops/sono/presentations/ucla_yao.pdfAudio and Speech Processing. Geert Van Meerbergen, et al. http:/homes.esat.kuleuven.be/gvanmeer/s&a/oefenzittingen/opgave2/node3.htmlBeamformit (Fast and Robust Acoustic Beamformer). Xavier Anguera. Nov 11 2008. /xanguera/beamformit/LOUD: A 1020-Node Microphone Array and Acoustic Beamformer. Eugene Weinstein