我如何分析一辆汽车的音量、音高和速度。Java中的wav文件？

Question

所以，我正在尝试重新制作Vib Ribbon:http://www.youtube.com/watch?v=ehdymXc0epY 输入将是一个。wav文件，我一点也不知道如何分析它，如何为音量和音高创建阈值，这会造成不同的障碍-我被指向傅里叶变换，我不明白。有人能给我指出一门波形分析课，这门课适合这种情况，并给我一个如何开始的想法吗？我还没有找到AudioSurf和音乐可视化工具的源代码

你可能会问，为什么是java？我正在学习一门Java入门课程，所以没有其他语言可以使用

Answer 1

我最终使用了Sound Viewer Tool来实现这一点，尽管是在另一种语言（Python）和另一个类项目中。如果将以下内容添加到svt中。py:

def processWav(filename, channel):
    """
    filename: path to a wav file
    Channel: 1 for left, 2 for right
    Returns centroids, frequencies, volumes
    """
    #open file
    audio_file = audiolab.sndfile(filename, 'read')
    #should be length of audiofile in seconds * 60. will fix this later
    import contextlib
    import wave
    with contextlib.closing(wave.open(filename, 'r')) as f:
        frames = f.getnframes()
        rate = f.getframerate()
        duration = frames / float(rate)
    duration *= 30 #30 data points for every second of audio yay
    duration = int(duration) #can only return an integer number of frames so yeah
    #print duration
    #Not really samples per pixel but I'll let that slide
    samples_per_pixel = audio_file.get_nframes() / float(duration)
    #some rule says this frequency has to be half of the sample rate
    nyquist_freq = (audio_file.get_samplerate() / 2) + 0.0
    #fft_size stays 4096
    processor = AudioProcessor(audio_file, 2048, channel, numpy.hanning)

    centroids = []
    frequencies = []
    volumes = []

    for x in range(duration):
        seek_point = int(x * samples_per_pixel)
        next_seek_point = int((x + 1) * samples_per_pixel)
        (spectral_centroid, db_spectrum) = processor.spectral_centroid(seek_point)
        peaks = processor.peaks(seek_point, next_seek_point)      
        centroids.append(spectral_centroid)
        frequencies.append(db_spectrum)
        volumes.append(peaks)

    #print "Centroids:" + str(centroids)
    #print "Frequencies:" + str(frequencies)
    #print "Volumes:" + str(volumes)

    #convert volumes[] from peaks to actual volumes
    for i in range(len(volumes)):
        volumes[i] = abs(volumes[i][0]) + abs(volumes[i][1])
    #round frequencies to save resources
    for i in range(len(frequencies)):
        for j in range(len(frequencies[i])):
            frequencies[i][j] = round(frequencies[i][j], 4)
    return centroids, frequencies, volumes

使用wav文件可以轻松地进行分析。质心代表音乐的音色——频率的加权平均值，它们表示任何时间点的整体亮度

第一个答案{a2}对我理解FFT/信号处理/数字声音表示有很大帮助

Answer 2

您可以编写一个Praat脚本（Praat可供下载here），生成包含所需信息的输出文件，然后用java程序读取该txt文件

可能还有外部图书馆，如@Gareth所说