From ac86f8bdafe3becd8dc7f326ce04efbc23f82e3d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Grzegorz=20Chrupa=C5=82a?= <pitekus@gmail.com>
Date: Wed, 11 Dec 2019 14:21:41 +0100
Subject: [PATCH] Update datafiles.md

---
 platalea/analysis/datafiles.md | 48 ++++++----------------------------
 1 file changed, 8 insertions(+), 40 deletions(-)

diff --git a/platalea/analysis/datafiles.md b/platalea/analysis/datafiles.md
index 3e6d837..9593c79 100644
--- a/platalea/analysis/datafiles.md
+++ b/platalea/analysis/datafiles.md
@@ -6,49 +6,17 @@ For analyzing the VGS model we are using the data files described below. For eac
 ```
 global_input.pkl
 {'audio_id': <class 'numpy.ndarray'>, 
- 'ipa': <class 'numpy.ndarray'>, 
- 'text': <class 'numpy.ndarray'>, 
- 'audio': <class 'numpy.ndarray'>}
+ 'audio': <class 'numpy.ndarray'>, 
+ 'text': <class 'numpy.ndarray'>}
 
-global_trained.pkl
-{'conv': <class 'numpy.ndarray'>, 
- 'rnn0': <class 'numpy.ndarray'>, 
- 'rnn1': <class 'numpy.ndarray'>, 
- 'rnn2': <class 'numpy.ndarray'>, 
- 'rnn3': <class 'numpy.ndarray'>, 
- 'att': <class 'numpy.ndarray'>}
+global_trained_LAYER.pkl
+{'LAYER': <class 'numpy.ndarray'> }
 
-global_random.pkl
-{'conv': <class 'numpy.ndarray'>, 
- 'rnn0': <class 'numpy.ndarray'>, 
- 'rnn1': <class 'numpy.ndarray'>, 
- 'rnn2': <class 'numpy.ndarray'>, 
- 'rnn3': <class 'numpy.ndarray'>, 
- 'att': <class 'numpy.ndarray'>}
-```
-
-## Local
-
-```
-local_input.pkl
-{'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}
+global_random_LAYER.pkl
+{'LAYER': <class 'numpy.ndarray'> }
 
-local_trained.pkl
-{'conv': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn0': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn1': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn2': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn3': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}}
+downsampling_factors.json
 
-local_random.pkl
-{'conv': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn0': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn1': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn2': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}, 
- 'rnn3': {'features': <class 'numpy.ndarray'>, 'labels': <class 'numpy.ndarray'>}}
+fa.json
 
 ```
-
-
-In these dictionaries 'features' correspond to inputs or activations for a single frame or timestep. The 'labels' array contains the corresponding phoneme labels, based on forced alignment between input audio and its transcription. Note that in this dataset some utterances have been filtered out due to the force alignment failing.
-