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Hourly Rate: Not Sure   |  Duration: Not Sure  |  Posted: Jul 04, 2015  |  Ends: 12d, 13h  |   4 Proposals
We are going to use OpenSL to listen from device microphone and put raw data to a circular buffer. Our goal is to do some signal processing on the raw data, we need to do calculation for few functions simultaneously, for example we need to do FFT with different window sizes at same time, calculating SPL, SIL, EQ and other acoustic functions while we save raw data (saving cloud be done on NDK or Java side) for further analysis. The job is to write an OpenSL library that opens device microphone(s), and start recording raw data into a circular buffer where other native threads could read from there. Also it should returns complete status about device, such as maximum sampling rate, OpenSL low level events, etc. Raw data in circular buffer should has time stamp label, in order to detect missed frames or buffer overflow. Your deliverable project should be in sample Android app which one native thread reads from circular buffer and save it on the disk or do a very simple calculation ov...
Category: Software Application       
Skills: Android NDK, OpenSL       

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| C****ing
|    Norway
Fixed Price: Not Sure   |  Posted: Jun 30, 2015  |  Ends: 8d, 11h  |   7 Proposals
Hello all bidders, We are looking for a developer to join our team and help create a small but interesting sound FFT code that will be integrated into our system. The code eventually needs to be written in C,C++, objective-C or anything else that can be integrated into iOS/Android. Our electronic device will send ultrasound tones (17-20khz), you will need to filter out the surrounding noise and identify the tone frequency. For the development process we will provide the sample WAV file. A very rough method to do this would be to maintain a rolling average of the values for certain frequencies (FFT bins), and if a new value is much larger than the average, it's likely to be a tone. There are better ways however, that involve more precise measurement of the background noise, and calculate the signal to noise ratio. The end result should be a small API/BlackBox for 5-10 different pre selected identified frequencies. The logic: we take the ultrasonic ranges of 17000hz-19500hz and de...
Category: Mobile Applications       
Skills: Android, iPhone App Development       
Preferred Location: North America, Western Europe, Eastern Europe

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| s****dea
|    Israel
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