语音命令转移学习的准确性太低

Question

当我使用codelabs.developers.google提供的代码进行测试时，我发现准确性太低并且对任何声音都敏感。

此后，我将以下代码添加到函数buildModel()中，但问题仍未解决。

function buildModel() {
    model = tf.sequential();
    model.add(tf.layers.conv2d(
    {filters: 8, kernelSize: [2, 8],strides: [1, 1], activation: 'relu', inputShape: INPUT_SHAPE,}));
    model.add(tf.layers.maxPooling2d({poolSize: [2, 2], strides: [2, 2]}));
    model.add(
    tf.layers.conv2d({filters: 32, kernelSize: [2, 4],strides: [1, 1], activation: 'relu'}));
    model.add(tf.layers.maxPooling2d({poolSize: [2, 2], strides: [2, 2]}));
    model.add(
    tf.layers.conv2d({filters: 32, kernelSize: [2, 4], activation: 'relu'}));
    model.add(tf.layers.maxPooling2d({poolSize: [2, 2], strides: [2, 2]}));
    model.add(
    tf.layers.conv2d({filters: 32, kernelSize: [2, 4], activation: 'relu'}));
    model.add(tf.layers.maxPooling2d({poolSize: [2, 2], strides: [1, 2]}));
    model.add(tf.layers.flatten());
    model.add(tf.layers.dropout({rate: 0.25}));
    model.add(tf.layers.dense({units: 2000, activation: 'relu'}));
    model.add(tf.layers.dropout({rate: 0.5}));
    model.add(tf.layers.dense({units: 3, activation: 'softmax'}));
    const optimizer = tf.train.adam(0.01);
    model.compile({
    optimizer,
    loss: 'categoricalCrossentropy',
    metrics: ['accuracy']
    });
}

还是我的想法错了？因此，我可以从这里得到一些建议，我认为这将为我的下一个方向提供很大的启发。