Question

我正在编写一个需要检测音频流中频率的应用程序。我已经读了大约一百万篇文章，但在跨越终点线时遇到了问题。我通过Apple的AVFoundation Framework通过此功能将音频数据传给我。

我正在使用Swift 4.2，并尝试使用FFT函数，但是目前它们有点烦人。

有什么想法吗？

// get's the data as a call back for the AVFoundation framework.
public func captureOutput(_ output: AVCaptureOutput, didOutput sampleBuffer: CMSampleBuffer, from connection: AVCaptureConnection) {
    // prints the whole sample buffer and tells us alot of information about what's inside
    print(sampleBuffer);

    // create a buffer, ready out the data, and use the CMSampleBufferGetAudioBufferListWithRetainedBlockBuffer method to put
    // it into a buffer
    var buffer: CMBlockBuffer? = nil
    var audioBufferList = AudioBufferList(mNumberBuffers: 1,
                                          mBuffers: AudioBuffer(mNumberChannels: 1, mDataByteSize: 0, mData: nil))
    CMSampleBufferGetAudioBufferListWithRetainedBlockBuffer(sampleBuffer, bufferListSizeNeededOut: nil, bufferListOut: &audioBufferList, bufferListSize: MemoryLayout<AudioBufferList>.size, blockBufferAllocator: nil, blockBufferMemoryAllocator: nil, flags: UInt32(kCMSampleBufferFlag_AudioBufferList_Assure16ByteAlignment), blockBufferOut: &buffer);

    let abl = UnsafeMutableAudioBufferListPointer(&audioBufferList)
    var sum:Int64 = 0
    var count:Int = 0
    var bufs:Int = 0

    var max:Int64 = 0;
    var min:Int64 = 0

    // loop through the samples and check for min's and maxes.
    for buff in abl {
        let samples = UnsafeMutableBufferPointer<Int16>(start: UnsafeMutablePointer(OpaquePointer(buff.mData)),
                                                        count: Int(buff.mDataByteSize)/MemoryLayout<Int16>.size)
        for sample in samples {
            let s = Int64(sample)
            sum = (sum + s*s)
            count += 1

            if(s > max) {
                max = s;
            }

            if(s < min) {
                min = s;
            }

            print(sample)
        }
        bufs += 1
    }

    // debug
    print("min - \(min), max = \(max)");

    // update the interface
    DispatchQueue.main.async {
        self.frequencyDataOutLabel.text = "min - \(min), max = \(max)";
    }

    // stop the capture session
    self.captureSession.stopRunning();
}

Answer 1

经过大量研究，我发现答案是使用FFT方法（快速傅立叶变换）。它从上面的iPhone代码中获取原始输入，并将其转换为代表频带中每个频率幅度的值数组。

此处https://github.com/jscalo/tempi-fft的开放代码有很多支持，这些代码创建了一个可视化工具，用于捕获数据并显示数据。从那里开始，就需要对其进行操作以满足需求。就我而言，我一直在寻找高于人类听力（20kHz范围）的频率。通过在tempi-fft代码中扫描阵列的后半部分，我能够确定我正在寻找的频率是否存在并且足够响亮。

快速4：检测音频流中最强的频率或频率的存在。

1 个答案: