jack with multiprocessing skips audio frames

Question

It will be hard without having the whole code but I will try my best to explain it in detail. If you need more information please let me know.

So I have a python program with 3 processes (multiprocessing) running in parallel. The first one is a video-preprocessing task. The second is an audio-preprocessing task, and the last is a DNN model call. All processes are written kinda like this:

from multiprocessing import Process

class NameOfTheProcess(Process):
    def __init__(self, queue, videoBuffer, audioBuffer):
        super().__init__()
        # ....

    def run(self):
        while True: # so that the processes run till I stop the program
        # ....
            

The video-preprocessing is a simple face tracking and filling in a queue (which is used so I can share the data between the processes). The audio-preprocessing is a process where I get an audio frame using the jack library. There I downsample the audio and put it in a buffer. After a specific delay of 20 callbacks of jack I start the DNN model process. In the DNN model process, I have currently only 4 simple steps. First I check if the audio queue is empty if not then I get the element of the queue and then I go through a "dummy" for loop in a range of 1000. After that, I take the last x elements of the audio queue and put them in another queue to use it later. The video-preprocessing and audio-preprocessing work fine I have no issues there but when I also start the DNN-process than I get many audio lost and in jack-client I get a lot of 16:00:12.435 XRUN callback (7 skipped). And when I just start the audio-preprocessing and the DNN-process I have the same issue. So in my mind, there is no problem with the video-preprocessing. After a while, I figured out that when I remove this line audioBufferIn = self.audioBuffer.get() in the code below I don't have the audio lost anymore but I need to get the audio queue there somehow so I can work with it.

from multiprocessing import Process

class DnnModelCall(Process):
    def __init__(self, queue, audioBuffer):
        super().__init__()
        print("DnnModelCall: init")
        self.queue = queue
        self.audioBuffer = audioBuffer

    def run(self):
        print("DnnModelCall: run")
        while True:
            if(not self.audioBuffer.empty()):
                k = 0
                audioBufferIn = self.audioBuffer.get()
                # audioBufferIn = self.audioBuffer.get(block=False)
                for i in range(0, 1000):
                    k += 1
                outputDnnBackPart = audioBufferIn[-2560:]
                outputQueue = []
                outputQueue.extend(outputDnnBackPart)
                self.queue.put(outputQueue)

I have also tried it with block=False but I get the same result.

Have anyone an idea? And if you need more information let me know. Thanks in advance.

Answer 1

The problem was that the element in the queue was too big. The solution was to reduce the size. So what I did was that I sent every audio frame which has a size of 128 audio samples to the other process and collect them there in a buffer till I have my desired 40800 audio samples. After the buffer is full I start the process.