From 0e523aa3f40c5e84aa60d70eea1a5fc4a9ff46c8 Mon Sep 17 00:00:00 2001
From: Jean-Marc Valin <jmvalin@amazon.com>
Date: Wed, 20 Oct 2021 23:05:58 -0400
Subject: [PATCH] controllable look-ahead
---
dnn/training_tf2/train_lpcnet.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/dnn/training_tf2/train_lpcnet.py b/dnn/training_tf2/train_lpcnet.py
index f80663edf..b6802fc72 100755
--- a/dnn/training_tf2/train_lpcnet.py
+++ b/dnn/training_tf2/train_lpcnet.py
@@ -52,6 +52,7 @@ parser.add_argument('--end2end', dest='flag_e2e', action='store_true', help='Ena
parser.add_argument('--lr', metavar='<learning rate>', type=float, help='learning rate')
parser.add_argument('--decay', metavar='<decay>', type=float, help='learning rate decay')
parser.add_argument('--gamma', metavar='<gamma>', type=float, help='adjust u-law compensation (default 2.0, should not be less than 1.0)')
+parser.add_argument('--lookahead', metavar='<nb frames>', default=2, type=int, help='Number of look-ahead frames (default 2)')
parser.add_argument('--logdir', metavar='<log dir>', help='directory for tensorboard log files')
@@ -148,7 +149,7 @@ nb_frames = (len(data)//(2*pcm_chunk_size)-1)//batch_size*batch_size
features = np.memmap(feature_file, dtype='float32', mode='r')
# limit to discrete number of frames
-data = data[2*2*frame_size:]
+data = data[(4-args.lookahead)*2*frame_size:]
data = data[:nb_frames*2*pcm_chunk_size]
--
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