Is there any way I can process the sound wave that goes to the input of the speaker before it gets played? I want to change the Decibel values for the different frequencies.
Thank you
It depends on what kind of effects you want to apply. You can use SoundPool.setRate to simply change the pitch. If you want to get more complicated effects consider using AudioEffect.
I want to change the Decibel values for the different frequencies.
That's exactly what Equalizer effect is doing. You can retrieve the band for desired frequency using Equalizer.getBand and than change its level with Equalizer.setBandLevel.
If you mean right before the digital-to-analog conversion, then no, you can't do that from an app. What you can do is to process the audio before writing it to your AudioTrack instance, or by using an AudioEffect as Andrei suggested. In both of these cases the audio might still go through additional filters in the platform's audio DSP (e.g. multiband compression, peak limiting, equalization to compensate for the particular speaker component used, etc) before reaching the DAC.
It sounds to me like you want to modify the audio signal in the frequency domain, so you could take a look at e.g. FFTW, which has a C interface as well as a Java wrapper, so you can use it both from native code and Java code depending on what you feel most comfortable with. I've never used it myself so I can't provide any info on how to integrate it into an Android project.
Related
I built a similar app Shazam, however it only works in sending an entire file of 10seconds of audio.
My doubt is: In android, there's any thing to keep like Shazam of while music is playing and the database is searching? Or it's own Shazam service technology?
Shazam developed that audio fingerprint matching technlogy. It's not available in the default Android SDK.
The Shazam technology is proprietary. The base algorithm was documented since by its creator:
The algorithm uses a combinatorially hashed time-frequency constellation analysis of the
audio, yielding unusual properties such as transparency, in which multiple tracks mixed together may each be identified.
This is very novel and efficient, but the principles for fingerprinting audio stay the same. Among which certainly a FTT (fast fourier transform) to at least detect the BPM. Its even possible to convert sound to an image (the simplest being a spectogram), which can be further processed by audio-unrelated software.
If you need an audio analysis library, written in Java you could look into MusicG for example which is said to be simple to use on Android.
In my android application I need to capture the user's speech from the microphone and then pass it to the server. Currently, I use the MediaRecorder class. However, it doesn't satisfy my needs, because I want to make glowing effect, based on the current volume of input sound, so I need an AudioStream, or something like that, I guess. Currently, I use the following:
this.recorder = new MediaRecorder();
this.recorder.setAudioSource(MediaRecorder.AudioSource.MIC);
this.recorder.setOutputFormat(MediaRecorder.OutputFormat.MPEG_4);
this.recorder.setAudioEncoder(MediaRecorder.AudioEncoder.AMR_NB);
this.recorder.setOutputFile(FILENAME);
I am writing using API level 7, so I don't see any other AudioEncoders, but AMR Narrow Band. Maybe that's the reason of awful noise which I hear in my recordings.
The second problem I am facing is poor sound quality, noise, so I want to reduct (cancel, suppress) it, because it is really awful, especially on my noname chinese tablet. This should be server-side, because, as far as I know, requiers a lot of resources, and not all of the modern gadgets (especially noname chinese tablets) can do that as fast as possible. I am free to choose, which platform to use on the server, so it can be ASP.NET, PHP, JSP, or whatever helps me to make the sound better. Speaking about ASP.NET, I have come across a library, called NAudio, may be it can help me in some way. I know, that there is no any noise reduction solution built in the library, but I have found some examples on FFT and auto-corellation using it, so it may help.
To be honest, I have never worked with sound this close before and I have no idea where to start. I have googled a lot about noise reduction techniques, code examples and found nothing. You guys are my last hope.
Thanks in advance.
Have a look at this article.
Long story short, it uses MediaRecorder.AudioSource.VOICE_RECOGNITION instead of AudioSource.MIC, which gave me really good results and noise in the background did reduce very much.
The great thing about this solution is, it can be used with both AudioRecord and MediaRecorder class.
For audio capture you can use the AudioRecord class. This lets you record raw audio, i.e. you are not restricted to "narrow band" and you can also measure the volume.
Many smartphones have two microphones, one is the MIC you are using, the other one is near camera for video shooting, called CAMCORDER. You can get data from both of them to do noise reduction. There are many papers talking about audio noise reduction with multiple microphones.
Ref: http://developer.android.com/reference/android/media/MediaRecorder.AudioSource.html
https://www.google.com/search?q=noise+reduction+algorithm+with+two+mic
I made test application in Delphi that beeps morse code using Windows API Beep function. Then made an application in Android that stores this morse code in WAV file. Now I want Android application to decode the morse code. Is there some tutorials for sound processing or can somebody post some simple code (think there's no simplicity here) for an example? Or maybe steps that I need to do to get it work?
I also downloaded the JTransforms and jfttw libraries but don't really know where to start.
Regards,
evilone
An FFT is overkill for this - you can just use a simple Goertzel filter to isolate the morse code from background noise, then decode the output of this.
I think an older issues of QST magazine had an article on DSP for Morse/CW decoding several years back. Might want to try and search their archives.
Basically, you need DSP code to determine whether or not a tone is present at any given point in time, and an estimate of the onset and off-time of each tone. Then scale the duration of each tone and the gap times between the tones for the expected code speed, and compare against a table of timings for each Morse code letter to estimate the probability of each or any letter being present.
In the simplest case, you might have a dot-dash-space decision tree. In severe noise and fading plus highly personalized fist/timing you might need some sophisticated statistical and/or adaptive audio pattern matching techniques for decent results.
Hello I was wondering if using the android tone generator class would it be possible to create a tone in one device and listen for this same tone in another device. If this is possible I do have a few other questions.
Taking backround noise into consideration is it possible to listen for only this specific tone?
Would this process be resource intensive?
Could I use a tone that would be inaudable to the human ear or close to it?
Lastly could I use a tone that could only be heard with a couple of feet from the sending device?
Thanks very much for yer time guys and girls :)
Edit >
Thanks For adding the audio processing tag sabastian. Much better discription.
It would be CPU intensive, yes.
The way to it is quite simple: you need a permanent recorder which puts the received data into a FFT (fast fourier transform). FFT basically does one thing: splits the audio into a frequency/power-scale. With this "background noise cleaned" result you can check things like "was there a tone with 1000Hz playing for at least 2 seconds" - and act accordingly.
There is a reasonable speed FFT implementation here: http://www.badlogicgames.com/wordpress/?p=449
FFT can also be used (actually, IS used) for detection of dualtone dialing (DTMF) - 2 frequencies at same time is much better than just using one (as the error rate drop significantly and you can go to shorter duration for the tone sending/detecting).
"Inaudible" won't be possible, as (a) the speaker can not produce such sounds (b) you are limited in sampling rate - so also limited in both producing and recording such high frequencies.
"couple of feet" will be naturally imposed (not very loud speaker, not very good microphone).
Have a look at this other question: "Android: Need to record mic input". I think you can modify that for your task, then with sound bytes you can have filtering or FFT.
Hope it helps
I'm trying to build a gadget that detects pistol shots using Android. It's a part of a training aid for pistol shooters that tells how the shots are distributed in time and I use a HTC Tattoo for testing.
I use the MediaRecorder and its getMaxAmplitude method to get the highest amplitude during the last 1/100 s but it does not work as expected; speech gives me values from getMaxAmplitude in the range from 0 to about 25000 while the pistol shots (or shouting!) only reaches about 15000. With a sampling frequency of 8kHz there should be some samples with considerably high level.
Anyone who knows how these things work? Are there filters that are applied before registering the max amplitude. If so, is it hardware or software?
Thanks,
/George
It seems there's an AGC (Automatic Gain Control) filter in place. You should also be able to identify the shot by its frequency characteristics. I would expect it to show up across most of the audible spectrum, but get a spectrum analyzer (there are a few on the app market, like SpectralView) and try identifying the event by its frequency "signature" and amplitude. If you clap your hands what do you get for max amplitude? You could also try covering the phone with something to muffle the sound like a few layers of cloth
It seems like AGC is in the media recorder. When I use AudioRecord I can detect shots using the amplitude even though it sometimes reacts on sounds other than shots. This is not a problem since the shooter usually doesn't make any other noise while shooting.
But I will do some FFT too to get it perfect :-)
Sounds like you figured out your agc problem. One further suggestion: I'm not sure the FFT is the right tool for the job. You might have better detection and lower CPU use with a sliding power estimator.
e.g.
signal => square => moving average => peak detection
All of the above can be implemented very efficiently using fixed point math, which fits well with mobile android platforms.
You can find more info by searching for "Parseval's Theorem" and "CIC filter" (cascaded integrator comb)
Sorry for the late response; I didn't see this question until I started searching for a different problem...
I have started an application to do what I think you're attempting. It's an audio-based lap timer (button to start/stop recording, and loud audio noises for lap setting). It' not finished, but might provide you with a decent base to get started.
Right now, it allows you to monitor the signal volume coming from the mic, and set the ambient noise amount. It's also using the new BSD license, so feel free to check out the code here: http://code.google.com/p/audio-timer/. It's set up to use the 1.5 API to include as many devices as possible.
It's not finished, in that it has two main issues:
The audio capture doesn't currently work for emulated devices because of the unsupported frequency requested
The timer functionality doesn't work yet - was focusing on getting the audio capture first.
I'm looking into the frequency support, but Android doesn't seem to have a way to find out which frequencies are supported without trial and error per-device.
I also have on my local dev machine some extra code to create a layout for the listview items to display "lap" information. Got sidetracked by the frequency problem though. But since the display and audio capture are pretty much done, using the system time to fill in the display values for timing information should be relatively straightforward, and then it shouldn't be too difficult to add the ability to export the data table to a CSV on the SD card.
Let me know if you want to join this project, or if you have any questions.