# 1230 meeting note ###### tags: `meeting note` - What did I do in this week - I trained the Bidirectional LSTM - sounds good on irealpro dataset - after transfering to dense_jazz dataset, sounds good, too - the output of inferencing on unseen data is also good - however, there are some interesting thing - there are some unnatural short notes jumping up and down - there are many long notes, because we cannot make pitch repetition in output - I modified some code: - using tf.data.dataset API - I rewrote the cost function to fit the masking - Tasks - try different hyperparameter on BD-LSTM - piece length - width and depth of NN - unit number of LSTM cell - change to GRU cell - some direction of better input/output format - add drums informations into input - add velocity as output - add onset/offset timing correction into output - indicate whether the note is filled in the beat, or start slightly late, or stop early - use regression to predict - ideally, it can solve swing problem and repetition problem at the same time - try new concept of model - one note per output, which is more suitable for encoder-decoder architecture in my opinion - train encoder-decoder rnn with attention - I think it’s a great idea to treat it as a kind of translation problem - perform experiments to prove the previous improvements are not meaningless - train same epochs on LSTM, BD-LSTM and encoder-decoder and compare - use the same model, compare the result of: - training on biggest dataset directly - training on small dataset first, and transfer to larger dataset - How we do our presentation?