有没有办法可视化从WAV2VEC 2.0获得的嵌入？
我想从头开始训练Word2Vec 2.0模型，但我对该领域有些新。至关重要的是，我想使用大型非人类语音（即鲸类声音）进行训练，以捕获基础结构。
一旦执行了预训练，是否可以以类似的方式可视化模型创建的嵌入，以便在使用EG CNN时如何在图像处理中可视化的潜在特征？还是说明太抽象而无法映射到频谱图？
我想做的是查看网络作为语音单位学习的功能。
事先感谢您的帮助！
I'm looking to train a word2vec 2.0 model from scratch, but I am a bit new to the field. Crucially, I would like to train it using a large dataset of non-human speech (i.e. cetacean sounds) in order to capture the underlying structure.
Once the pre-training is performed, is it possible to visualize the embeddings the model creates, in a similar way to how latent features are visualized in image processing when using e.g. CNNs? Or are the representations too abstract to be mapped to a spectrogram?
What I would like to do is to see what features the network is learning as the units of speech.
Thanks in advance for the help!
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