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IFT6266 | William's Blog | twuilliam.wordpress.com Reviews
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William's Blog
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Some (late) initial thoughts | IFT6266
https://twuilliam.wordpress.com/2014/02/10/some-late-initial-thoughts
Some (late) initial thoughts. This year the project in IFT6266 course will focus on a unified approach to speech synthesis based on deep learning algorithms. Speech synthesis consists of mapping a text to the corresponding acoustic signals. This process is also called a text-to-speech system. According to Wikipedia. These systems first appeared in the late 50’s, which is quite old! As explained by David Krueger. Speech can be defined as an acoustic signal with melody, rhythm and harmony that is why a uni...
About | IFT6266
https://twuilliam.wordpress.com/about
Final final experiment — MLP for each phoneme. Last Experiment — Extracting features with SdA. Third experiment Adding hidden layers. Second Experiment — Say ‘aa’ vanilla MLP. Quick Experiment – Breaking the sine in one line. Final final experime…. On Last Experiment — Extrac…. On Quick Experiment – Break…. TIMIT – FCJF0…. On First experiment — Vanil…. Second MLP architect…. On Quick Experiment – Break…. On Quick Experiment – Break…. Blog at WordPress.com.
Quick Experiment – Breaking the sine in one line | IFT6266
https://twuilliam.wordpress.com/2014/02/27/quick-experiment-breaking-the-sin-in-one-line/comment-page-1
Quick Experiment – Breaking the sine in one line. As we discussed today in class and as mentioned by Laurent in his post. Adding gaussian noise is important to prevent convergence to a constant. In my last post. I found this kind of behaviour which results in a flatline. Recall Laurent’s post. Is the size of the window. The estimator of the variance is the mean square error (MSE):. Is the number of training examples. Compared to my previous post. Script (go to line 380). To the .wav file):. Second Experi...
First experiment — Vanilla MLP with Theano | IFT6266
https://twuilliam.wordpress.com/2014/02/18/first-experiment-vanilla-mlp-with-theano
First experiment — Vanilla MLP with Theano. As a first experiment, I will try to predict the next acoustic sample given a specific number of previous samples. A feedforward neural network (NN) with one hidden layer will be used to perform this task. You will find all my scripts under this repository. To generate the dataset ( generate dataset.py. And train a NN ( mlp.py. The work that I will present is mainly inspired by Hubert. The activation function of the output layer is linear instead of a softmax.
Quick Experiment – Breaking the sine in one line | IFT6266
https://twuilliam.wordpress.com/2014/02/27/quick-experiment-breaking-the-sin-in-one-line
Quick Experiment – Breaking the sine in one line. As we discussed today in class and as mentioned by Laurent in his post. Adding gaussian noise is important to prevent convergence to a constant. In my last post. I found this kind of behaviour which results in a flatline. Recall Laurent’s post. Is the size of the window. The estimator of the variance is the mean square error (MSE):. Is the number of training examples. Compared to my previous post. Script (go to line 380). To the .wav file):. Second Experi...
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Lengths of phones | DAVIDTOB
https://davidtob.wordpress.com/2014/02/04/lengths-of-phonemes
This blog records my experiments for the course ift6266h14 at Université de Montréal. February 4, 2014. I was curious about the typical lengths of. Symbols in the training set, so I made a boxplot:. There seems to be. Median duration of phonemes varies from tens to hundreds of milliseconds. Also, the variation in duration for each individual phoneme is from tens to hundreds of milliseconds. The “outliers” are usually much longer than the median duration rather than much shorter. February 4, 2014 at 8:51 ...
About this blog | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/01/28/about-this-blog
You’re at the best WordPress.com site ever. This blog will be a logbook of experiments for the speech synthesis project made under Yoshua Bengio’s course at Université de Montréal. Project details and course material. January 28, 2014. First understanding →. Leave a Reply Cancel reply. Enter your comment here. Fill in your details below or click an icon to log in:. Address never made public). You are commenting using your WordPress.com account. ( Log Out. Notify me of new comments via email.
First experiment | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/02/27/first-experiment
You’re at the best WordPress.com site ever. As I said in my previous post, a long time ago, I tried what Hubert. Did: a small neural network with one hidden layer, tanh activation function and linear output with the mean squared error as loss function. So, I trained this model on the firsts sentences contained in the TIMIT dataset (FCJF0) by dividing acoustics samples in frames containing 240 acoustics samples plus one as a target. The goal is still to predict acoustics samples from previous one! I’...
First understanding | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/02/10/first-understanding
You’re at the best WordPress.com site ever. I never studied speech signal at all and didn’t know the composition of a signal. I never played with sounds or music, I don’t even play music! What is the format of a sequence? What do we need to match with what? What is in a .wav file? What to do with it? What are our inputs? As you can understand, I was completely lost and I didn’t manage to focus on what I had to do to move forward, despite the very good explanations provided by. February 10, 2014. You are ...
TIMIT – FCJF0 Comparisons | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/03/20/timit-fcjf0-comparisons/comment-page-1
You’re at the best WordPress.com site ever. TIMIT – FCJF0 Comparisons. This post will be like a comparison for the different posts I saw on the data of the first speaker (. As we need a standard way to compare our result, I will divide by the standard deviation too (of the whole dataset, that is 560). We also need to “rescale” our MSE by multiplying it by this standard deviation. I tried to match match William’s results. That’s why a standardized way to compare our work is essential. Provided a solution ...
February | 2014 | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/02
You’re at the best WordPress.com site ever. Monthly Archives: February 2014. As I said in my previous post, a long time ago, I tried what Hubert. Did: a small neural network with one hidden layer, tanh activation function and linear output with the mean squared error as loss function. This leads to 382 721 frames or examples to train on. I divided it as follow: 80% for train set, 10% for valid and test sets. Learning rate: 0.001. Some acoustics samples generated by the model:. I’ll try Theano, mayb...
March | 2014 | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/03
You’re at the best WordPress.com site ever. Monthly Archives: March 2014. TIMIT – FCJF0 Comparisons. This post will be like a comparison for the different posts I saw on the data of the first speaker (. As we need a standard way to compare our result, I will divide by the standard deviation too (of the whole dataset, that is 560). We also need to “rescale” our MSE by multiplying it by this standard deviation. I tried to match match William’s results. Learning rate: 0.01. Provided a solution for this....
Sparse-coded TIMIT | Speech synthesis experiments
https://ift6266tr.wordpress.com/2014/05/01/sparse-coded-timit
You’re at the best WordPress.com site ever. The plan, at this point, is to use a gammatone dictionary and sparse coding to train more efficiently on the TIMIT dataset. Gammatone functions are filters applied on frequencies. The goal is to keep frequencies processed by our ears. Joao explains this greatly in his blog. The idea is to use this sparse-coded version as input of a spike and slab RBM segmented by frames of 160 samples and with the previous, current and next phones. I kept the parameters use...
Thomas Rohée | Speech synthesis experiments
https://ift6266tr.wordpress.com/author/mennerve
You’re at the best WordPress.com site ever. Author Archives: Thomas Rohée. The plan, at this point, is to use a gammatone dictionary and sparse coding to train more efficiently on the TIMIT dataset. Gammatone functions are filters applied on frequencies. The goal is to keep frequencies processed by our ears. Joao explains this greatly in his blog. The idea is to use this sparse-coded version as input of a spike and slab RBM segmented by frames of 160 samples and with the previous, current and next phones...
Mar13 | Representation Learning - ift6266h14
https://ift6266h14.wordpress.com/2014/03/11/mar13/comment-page-1
Representation Learning – ift6266h14. Yoshua Bengio's graduate class on representation learning and deep learning. Final Exam →. Posted by Yoshua Bengio. Please study the following material in preparation for the March 13th class:. Of book draft on Deep Learning. Directory includes bibliography) by Y. Bengio, I. Goodfellow and A. Courville. Please put up your questions below, as replies to this post. 33 thoughts on “ Mar13. March 11, 2014 at 10:03. March 11, 2014 at 11:10. March 11, 2014 at 23:39. You ca...
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Mot de passe :. J'ai oublié mon mot de passe. Mise à jour :. Abonne-toi à mon blog! Ma Grande Maxi Moi en Moin Pir. J'ai des relations étranges. Très étranges. Je ne suis pas sociable. Je déteste parler de solidarité. Chacun sa merde. Le meilleur moyen d'aider les autres et de leur laisser leur nez dans leur merde comme ça ils apprennent à pas compter sur nous. Je suis très attachante. (Sisi, faut juste un énorme effort de rien du tout ;). Je ne suis pas vraiment belle. Mais ça, osef! Ou poster avec :.
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IFT6266 | William's Blog
Final final experiment — MLP for each phoneme. In my previous post. I proposed to use the implementation composed of a SdA and a MLP of 2 hidden layers for each phoneme. I will present in this last post the results of this proposal. The objective is to generate that sentence:. 8220;dont’ask me to carry an oily rag like that”. Https:/ dl.dropboxusercontent.com/u/43075537/final/test sentence.wav%20. The hyperparameters of the implementation are almost the same as the ones used in my final experiment post.
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TWUinTanzania
Tuesday, October 20, 2009. Watch a slideshow of some pictures from last years' trip. Click HERE. Tuesday, October 13, 2009. Exciting plans are unfolding! To learn more about Food for the Hungry Canada's IMED program check out their website HERE. We would appreciate prayer during this next process of fundraising and getting organized. . Tuesday, August 18, 2009. Where we've been, where we are headed. 8220;I lift up my eyes to the hills—where does my help come from? Both Trinity and Tanzanian students invo...
Blog de twuiny - Blog de twuiny - Skyrock.com
Mot de passe :. J'ai oublié mon mot de passe. Si la terre ne tourne plus rond c'est que je tourne dans l'autre sens. Mise à jour :. Abonne-toi à mon blog! Prendre son avenir en mains c'est possible.travaillez depuis votre domicil. Changez le cours de votre vie c'est simple. Faites des sous rapidement! Ou poster avec :. Retape dans le champ ci-dessous la suite de chiffres et de lettres qui apparaissent dans le cadre ci-contre. Posté le dimanche 09 novembre 2008 16:19. Jouez, Votez et Gagnez! N'oublie pas ...
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