如何获取wav文件中的频率列表

2024-03-28 21:12:41 发布

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我试图解码一些音频,基本上是两个频率(0为200hz,1为800hz),直接转换成二进制。 A sample of the audio

此示例翻译为“1001011”。 第三个频率为1600hz,作为位之间的分频器

我找不到任何有效的东西,我确实找到了一些东西,但要么是过时的,要么就是直接不起作用,我真的很失望

我制作了一个示例代码,可以为这种编码生成音频(用于测试解码器):

import math
import wave
import struct

audio = []
sample_rate = 44100.0

def split(word):
    return [char for char in word]

def append_sinewave(
        freq=440.0,
        duration_milliseconds=10,
        volume=1.0):
    global audio
    num_samples = duration_milliseconds * (sample_rate / 1000.0)
    for x in range(int(num_samples)):
        audio.append(volume * math.sin(2 * math.pi * freq * ( x / sample_rate )))
    return
def save_wav(file_name):
    wav_file=wave.open(file_name,"w")
    nchannels = 1
    sampwidth = 2
    nframes = len(audio)
    comptype = "NONE"
    compname = "not compressed"
    wav_file.setparams((nchannels, sampwidth, sample_rate, nframes, comptype, compname))
    for sample in audio:
        wav_file.writeframes(struct.pack('h', int( sample * 32767.0 )))
    wav_file.close()
    return
print("Input data!\n(binary)")
data=input(">> ")
dataL = []
dataL = split(data)
for x in dataL:
    if x == "0":
        append_sinewave(freq=200)
    elif x == "1":
        append_sinewave(freq=800)
    append_sinewave(freq=1600,duration_milliseconds=5)
    print("Making "+str(x)+" beep")


print("\nWriting to file this may take a while!")
save_wav("output.wav")

谢谢你的帮助


Tags: sampleinimportforreturnratedefmath
1条回答
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1楼 · 发布于 2024-03-28 21:12:41

我想我理解你的企图。根据编码器脚本,我假设wave文件中的每个bit转换为10毫秒,以5ms 1600hz的音调作为一种分隔符。如果这些持续时间是固定的,您可以简单地使用scipynumpy对音频进行分段并对每个分段进行解码

鉴于上面的编码器脚本为bytestring生成105ms(7*15ms)单声道:output.wav,如果要忽略定界频率,我们应该返回一个表示每个bit频率的列表:

[800, 200, 200, 800, 200, 800, 800]

我们可以使用scipy读取音频,并使用numpy对音频段执行FFT,以获得每个段的频率:

from scipy.io import wavfile as wav

import numpy as np

rate, data = wav.read('./output.wav')

# 15ms chunk includes delimiting 5ms 1600hz tone
duration = 0.015

# calculate the length of our chunk in the np.array using sample rate
chunk = int(rate * duration)

# length of delimiting 1600hz tone
offset = int(rate * 0.005)

# number of bits in the audio data to decode
bits = int(len(data) / chunk)

def get_freq(bit):
    # start position of the current bit
    strt = (chunk * bit) 
    
    # remove the delimiting 1600hz tone
    end = (strt + chunk) - offset
    
    # slice the array for each bit
    sliced = data[strt:end]

    w = np.fft.fft(sliced)
    freqs = np.fft.fftfreq(len(w))

    # Find the peak in the coefficients
    idx = np.argmax(np.abs(w))
    freq = freqs[idx]
    freq_in_hertz = abs(freq * rate)
    return freq_in_hertz

decoded_freqs = [get_freq(bit) for bit in range(bits)]

屈服

[800.0, 200.0, 200.0, 800.0, 200.0, 800.0, 800.0]

要转换为位/字节,请执行以下操作:

bitsarr = [1 if freq == 800 else 0 for freq in decoded_freqs]

byte_array = bytearray(bitsarr)
decoded = bytes(a_byte_array)
print(decoded, type(decoded))

屈服

b'\x01\x00\x00\x01\x00\x01\x01' <class 'bytes'>

关于推导峰值频率的更多信息,请参见this question

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