diff --git a/training/rnn_train.py b/training/rnn_train.py
index 06d7e1a4..d2b51ca3 100755
--- a/training/rnn_train.py
+++ b/training/rnn_train.py
@@ -62,13 +62,13 @@ def get_config(self):
 print('Build model...')
 main_input = Input(shape=(None, 42), name='main_input')
 tmp = Dense(24, activation='tanh', name='input_dense', kernel_constraint=constraint, bias_constraint=constraint)(main_input)
-vad_gru = GRU(24, activation='tanh', recurrent_activation='sigmoid', return_sequences=True, name='vad_gru', kernel_regularizer=regularizers.l2(reg), recurrent_regularizer=regularizers.l2(reg), kernel_constraint=constraint, recurrent_constraint=constraint, bias_constraint=constraint)(tmp)
+vad_gru = GRU(24, activation='relu', recurrent_activation='sigmoid', return_sequences=True, name='vad_gru', kernel_regularizer=regularizers.l2(reg), recurrent_regularizer=regularizers.l2(reg), kernel_constraint=constraint, recurrent_constraint=constraint, bias_constraint=constraint)(tmp)
 vad_output = Dense(1, activation='sigmoid', name='vad_output', kernel_constraint=constraint, bias_constraint=constraint)(vad_gru)
 noise_input = keras.layers.concatenate([tmp, vad_gru, main_input])
 noise_gru = GRU(48, activation='relu', recurrent_activation='sigmoid', return_sequences=True, name='noise_gru', kernel_regularizer=regularizers.l2(reg), recurrent_regularizer=regularizers.l2(reg), kernel_constraint=constraint, recurrent_constraint=constraint, bias_constraint=constraint)(noise_input)
 denoise_input = keras.layers.concatenate([vad_gru, noise_gru, main_input])
 
-denoise_gru = GRU(96, activation='tanh', recurrent_activation='sigmoid', return_sequences=True, name='denoise_gru', kernel_regularizer=regularizers.l2(reg), recurrent_regularizer=regularizers.l2(reg), kernel_constraint=constraint, recurrent_constraint=constraint, bias_constraint=constraint)(denoise_input)
+denoise_gru = GRU(96, activation='relu', recurrent_activation='sigmoid', return_sequences=True, name='denoise_gru', kernel_regularizer=regularizers.l2(reg), recurrent_regularizer=regularizers.l2(reg), kernel_constraint=constraint, recurrent_constraint=constraint, bias_constraint=constraint)(denoise_input)
 
 denoise_output = Dense(22, activation='sigmoid', name='denoise_output', kernel_constraint=constraint, bias_constraint=constraint)(denoise_gru)