C语言读取wav音频并进行采样实例

你可以使用C语言中的wav库来读取和处理wav音频文件。以下是一个简单的例子：

#include <stdio.h>
#include <stdlib.h>
#include <stdint.h>
#include <math.h>

#define BUF_SIZE 1024

typedef struct {
    char chunk_id[4];
    uint32_t chunk_size;
    char format[4];
    char subchunk1_id[4];
    uint32_t subchunk1_size;
    uint16_t audio_format;
    uint16_t num_channels;
    uint32_t sample_rate;
    uint32_t byte_rate;
    uint16_t block_align;
    uint16_t bits_per_sample;
    char subchunk2_id[4];
    uint32_t subchunk2_size;
} wav_header;

int main(int argc, char *argv[]) {
    if (argc != 2) {
        printf("Usage: %s <filename>\n", argv[0]);
        return -1;
    }

    FILE *fp = fopen(argv[1], "rb");
    if (fp == NULL) {
        printf("Error opening file %s\n", argv[1]);
        return -1;
    }

    wav_header header;
    fread(&header, sizeof(wav_header), 1, fp);
    if (strncmp(header.chunk_id, "RIFF", 4) != 0 ||
            strncmp(header.format, "WAVE", 4) != 0 ||
            strncmp(header.subchunk1_id, "fmt ", 4) != 0 ||
            strncmp(header.subchunk2_id, "data", 4) != 0) {
        printf("Invalid WAV file format\n");
        return -1;
    }

    // Calculate some parameters
    int num_samples = header.subchunk2_size / (header.bits_per_sample / 8);
    int buf_size = BUF_SIZE / (header.bits_per_sample / 8);
    double sample_rate = header.sample_rate;
    double nyquist = sample_rate / 2;
    double freq_step = nyquist / buf_size;

    // Allocate buffer
    short *buffer = (short *) malloc(buf_size * sizeof(short));

    // Read data and do FFT
    for (int i = 0; i < num_samples; i += buf_size) {
        int num_read = fread(buffer, sizeof(short), buf_size, fp);
        if (num_read != buf_size) {
            printf("Error reading data from file\n");
            return -1;
        }

        // Process buffer here

    }

    free(buffer);
    fclose(fp);

    return 0;
}

这个例子读取一个指定的wav音频文件，将其中的数据分成若干个1024个样本的块，每次读取一个块并使用FFT算法对其进行频率分析。你可以在“Process buffer here”处添加自己的处理代码。注意，对音频数据进行处理需要一定的信号处理知识，如果你不熟悉这方面的知识，可以参考一些相关的教程或者带有代码示例的学术论文。