Then to get hidden layer values for "heart", you just take the 958th row of the embedding matrix. We encode the words as integers, for example "heart" is encoded as 958, "mind" as 18094. Instead of doing the matrix multiplication, we use the weight matrix as a lookup table. We can do this because the multiplication of a one-hot encoded vector with a matrix returns the row of the matrix corresponding the index of the "on" input unit. We skip the multiplication into the embedding layer by instead directly grabbing the hidden layer values from the weight matrix. We call this layer the embedding layer and the weights are embedding weights. ![]() Embeddings are just a fully connected layer like you've seen before. To solve this problem and greatly increase the efficiency of our networks, we use what are called embeddings. The matrix multiplication going into the first hidden layer will have almost all of the resulting values be zero. ![]() Trying to one-hot encode these words is massively inefficient, you'll have one element set to 1 and the other 50,000 set to 0. When you're dealing with words in text, you end up with tens of thousands of classes to predict, one for each word. An implementation of word2vec from Thushan Ganegedara.NIPS paper with improvements for word2vec also from Mikolov et al.First word2vec paper from Mikolov et al. ![]() A really good conceptual overview of word2vec from Chris McCormick.I suggest reading these either beforehand or while you're working on this material. Here are the resources I used to build this notebook. This will come in handy when dealing with things like machine translation. By implementing this, you'll learn about embedding words for use in natural language processing. In this notebook, I'll lead you through using TensorFlow to implement the word2vec algorithm using the skip-gram architecture.
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The thing that really amazed me is the hi-hat controller data sent from my td-6 actually gets interpreted properly by the Battery engine. This is common with most good samplers as it makes it possible to achieve a very realistic simulation of an instrument, in this case drums. Depending on how hard you hit the pad, the software will play a different wav file. In english that means you could have 120 different wav files associated with one drum pad. Plus you can load any wave file into battery for wierd non-drum sounding stuff.ĪNother awesome thing about Battery is for each drum channel, you can have up to 120 layers of velocity. Damn! Just like having a miked drum kit without the pain of miking my acoustic drums. Send each drum to a different track in cubase and add effects, equalize etc. Edit the wav files that make up the kit I am using if I want with envelopes and filters etc. Swap out drums and cymbals after if needed or desired, quantize any mistakes or just go in and edit the performance manually. With cubase set to a latency of a little under 6 ms, I can shred with no noticable delay. ![]() ![]() ![]() but we'll see Yo, whatever happened with this? Did Battery work out for you? I am currently using Battery as a VST instrument in Cubase and it f'n rocks! It even gets the high-hat controller right. I've only got a 266, but I've got something like 192 megs of ram in it, so I'm hoping that'll make up for it. Actually, from what I've read, as a standalone it only needs a 300 mhz and something like 64 megs of ram. |