I want to write an app on Android to record snoring sounds of a sleeper and analyze it afterwards (i.e., not in real-time) for signs of a medical condition called obstructive sleep apnea.
The Android devices I've experimented with have voice recorders that produce a file format called .3ga. I want to programmatically read in the audio file and look at the amplitude for each individual time-sample. Then I can analyze that for patterns. Would this be easier if I converted this to a different format, e.g., MP3, and if so how can I do that programmatically?
I did a Google search on this and most of the hits seemed to be related to audio recording or playback which are unrelated to what I'm trying to do. I haven't coded anything yet because I don't know how to get started.
You are looking to do sample-based analysis on a raw audio signal, but the formats you mention are compressed. You will need to either deal with raw samples directly, or decompress the audio and then analyze.
Since you said you can do this work after-the-fact, why not upload to a server and analyze there?
Related
I've got a rather complicated problem that I need to solve at work. It's pretty far out of my remit of "Android App Developer" - I would class it as a very specialized audio engineering problem.
I am tasked with developing an application, which needs to be able to stream either a local audio file or audio from streaming service apps such as, but not limited to, Spotify, to another device over Bluetooth.
In addition, the app needs to be able to estimate the BPM of the streamed audio (it is assumed all audio will be musical) and use this BPM value to control the playback speed of a lighting sequence.
This question is about how to estimate the BPM of the streamed music.
For the case where the audio file is local, I can think of some solutions for this, such as hardcoding the BPM into the app, in a map against the audio resources URL.
I have also investigated and experimented with "static" library (aubio) than can estimate BPM from an audio file, but not on the fly. It assumes .wav format. This won't be sufficient for what we are trying to achieve here.
However, given the requirement for streaming external audio from streaming service apps such as Spotify, a static analysis solution is pointless as the solution wouldn't work for the streaming service case, and the streaming service case solution will work for both cases.
Therefore, I have come to the conclusion that somehow, I need to on the fly analyze the streamed audio, perhaps with FFT or peak detection algorithms.
This question isn't about the actual BPM estimation algorithm itself (or the implementation details of how I would get there) and is about the basic starting point of such a solution:
How might I go about getting A) the raw bytes of streamed audio for both the local file case and the external streaming service app case and B) how might I process these bytes into a data structure representing the audio stream in a way amenable to running audio analysis algorithms on it.
I realize this is very open ended, quite vague question, but this is so far out of my comfort zone I've no idea how to even formulate a more coherent question.
Any help would be greatly appreciated!
I'd start by creating some separate, more tightly defined questions for the different pieces. For example, ask how to get access to the raw bytes when streaming local file, or streaming URL-sourced audio. Android has some nice support for streaming, including the ability to stream PCM, so I'd be pretty surprised if getting a hook for access to the byte stream were not possible.
Once you have a hooking point, to convert the bytes to "something useful" I'd look at using the audio format to tell you how to read the incoming bytes. The format should tell you how many channels (mono or stereo), the encoding (e.g., signed PCM is common, might be normalized floats), the number of bits per value (16 is common) and the order of the bytes (big-endian vs little endian).
I know that there are posts that will explain how to convert the raw audio bytes to PCM values based on this info, including some on stackoverflow. They should be reachable via search. I think signed normalized floats is the most common data representation used for processing audio signals.
I'm writing an android app that plays an audio file and records what the phone is outputting simultaneously. When the recording is done, it would compare the recording against the original audio played and return whether they match and to what certainty.
I searched a lot and I found some libraries for audio fingerprinting, but they're mostly for music identification purposes.
Is there any libraries out there that I could use for this purpose? Would it make sense to write a custom algorithm for this?
You could compare the sound waves sample to sample (as numbers), then compute maximal, minimal, average difference, etc..
I'm writing an android app that lets user record his voice through microphone & save it in storage & link it to a specific content (like a Contact). Later, user call that voice again & the app should compare it with saved audio files & find the one that matches the voice.
I searched a lot & found some libraries that do this online, like EchoPrint that generates fingerprint from recorded audio & sends it to opensource server & returns the result. But I need to do this offline.
Has anybody know such library?
If you are aiming to compare an old recording of a user with a new call as it comes in, audio fingerprinting solutions like Dejavu in Python on a server or Echoprint in C++ won't help you. They are for doing recognition and retrieval on recorded audio segments plus noise.
They cannot deal with the variabilites in human voice. See an explanation here.
If that's the case, what you are referring to is speaker recognition, which is much harder and involves quite a bit of machine learning. It would be tough to do this for a large corpus of users (especially offline on a phone), but for determining between a couple users, it might be doable.
Below is a good Library. Which is Easy to use. But you need to convert your Audio Files to Wave Format prior to this.
https://code.google.com/p/musicg/
I would like to write an app the records audio continuously and analyze it in real time. I already know how to record file once and play it back, but I don't know how to make it continuous. I suppose there is some sort of circular buffer file in Java API, but I am quite new to Java and I didn't get my head around the APIs yet. Also can I keep this file entirely in memory, not to introduce overhead of writing to external storage? Any ideas?
I am developing Recording App that includes Pause/Play option.
I tried with both Media Recorder and AudioRecord
In case of AudioRecord , the recorded audio consumes larger size, so if the recording size increases say for eg: if i record 1 min audio it consumes 40 to 50MB an it really paining to combine by converting it to .raw file and send to php server.
So i tried with Media Recorder, it consumes less size,but not able to combine using the previous way handled in Audio Record.
Next step i tried with Android NDK- really paining for even Set up process.
Now my question is that which is the best way to combine recorded audio files
Using Android NDk
Reading the byte data from Audio and combining -If i use this there is problem with Headers of Recording format say amr,wav like that.
Also if i try with this , i am not able to get javax.sound package , So i tried with Plugins but no luck..
Please Suggest best way to do this. Also i tried with all this following links
Audio Link 1
Audio Link 2
Audio Link 3
Audio Link 4
Provide me Good tutorial or samples or links.Thanks.
For something like this your best bet would be to develop native C++ code using the NDK.