AST: Audio Spectrogram Transformer
时间: 2023-10-17 09:06:34 浏览: 49
AST: Audio Spectrogram Transformer是一种无卷积、纯基于注意力机制的模型,它于处理音频频谱图,并能够获取长距离的全局上下文。AST模型是从用于图像分类的ViT模型进行迁移学习得到的。AST模型的架构包括谱图分割、线性投影层、Transformer Encoder和线性层等组件。谱图分割后,输入到线性投影层得到patch embedding。为了捕获输入patch的顺序信息,作者在patch embedding中添加了position embedding,并将它们一起输入到Transformer Encoder中。在每个序列的开始部分加上[CLS],并使用[CLS]对应的最终隐藏状态作为分类任务的序列表示。通过Transformer Encoder后,输出和输入的形状保持一致。最后,通过线性层得到最终的分类结果。
相关问题
Audio Spectrogram Transformer
好的,我明白了。关于 "Audio Spectrogram Transformer",我可以告诉你,它是一种基于Transformer架构的音频处理模型,用于将音频信号转换为其对应的频谱图。这种模型通常用于语音识别、音乐分类和声音分割等任务。
在这种模型中,输入音频信号首先被转换为其对应的频谱图,然后通过多层Transformer编码器进行处理,最终输出相应的预测结果。这种模型的优点是可以处理变长的音频信号,并且在一些任务上取得了很好的效果。
matlab spectrogram
Matlab has a built-in function spectrogram that can be used to generate a spectrogram of a signal. The syntax for using the spectrogram function is as follows:
`[S,F,T] = spectrogram(x,window,noverlap,nfft,fs)`
where:
- `x`: the signal to be analyzed
- `window`: the length of the window used for the analysis (in samples)
- `noverlap`: the number of samples that overlap between adjacent windows
- `nfft`: the number of points used in the FFT
- `fs`: the sampling frequency of the signal
The output of the spectrogram function is:
- `S`: the spectrogram matrix
- `F`: the frequency vector
- `T`: the time vector
Here is an example code that generates a spectrogram of a signal:
```matlab
% Generate a signal
fs = 1000; % Sampling frequency
t = 0:1/fs:1-1/fs; % Time vector
f = [10 20 30 40 50]; % Frequencies of the sinusoids
x = sin(2*pi*f.'*t); % Signal
% Calculate spectrogram
window = 256; % Window length
noverlap = window/2; % Overlap between windows
nfft = 1024; % FFT length
[S,F,T] = spectrogram(x,window,noverlap,nfft,fs);
% Plot spectrogram
imagesc(T,F,20*log10(abs(S)));
axis xy;
xlabel('Time (s)');
ylabel('Frequency (Hz)');
colorbar;
```
This code generates a spectrogram of a signal that consists of five sinusoids with frequencies 10, 20, 30, 40, and 50 Hz. The resulting spectrogram shows the frequency content of the signal over time.