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

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depend on the application. Line Circle Rectangle
Each microphone will capture the sound from the
source at the different time due to distance from the source.
Microphone Array and Beamforming
By Pattarapong Rojanasthien ECE 5525 Dr. Kepuska December 8th, 2008
Overview
Introduction Background
Microphone Arrays Beamforming Signal to Noise Ratio
Therefore, there is a time delay in each signal.
Microphone Array
Multi-Channel Signal Comparison
Time Delay

Note that the distance between another microphone (not the reference) to the source, which denote as g, can be compute with trigonometry cos = d/g => d = g cos.
Solution and Approach
Results
Conclusion
Introduction
The goals for the project are the following
Learn the basic concept of microphone array Become familiar and learn how to use a program that
来自百度文库
Since 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.
Voice Activity Detection
The general form of the beamforming output based on
delay and sum
Beamforming Pattern
Signal to Noise Ratio
The measurement of the signal quality
Basically, it is the magnitude of


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 = 63.913 samples/m. Turn into inches => 63.913 x 0.0254 = 1.62 To find time delay, we need distance d’ x = 4.73 x 1.62 = 7.7 samples, round up to be 8 samples.
perform Beamforming Show that Beamforming will enhance the signal quality based on SNR
Microphone Array
Multiple microphones set up in certain formation


Example of Microphone Array
Beamforming
A technique that rearrange the mixture signals from the
microphone array, so that the signals from the source that we want are lined up before combine them all up into one signal
signal noise
One way to calculate it is to find noise from voice activity detection 1. Measure the mean of the energy during the last t1 seconds => E1 2. Measure the mean of the energy during the last t2 seconds => E2 3. Calculate the speech threshold T2 = E2 + Ex 4. If E1 > Ts, speech is detected. (speech onset) 5. Freeze E2 and calculate the noise threshold Tn = E2 + En 6. Measure the mean of the energy of recent t1 seconds => E1 7. IF E1 < Tn, noise is detected. (speech offset)
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