From 34eeaee58b940aa7a952d209b8d5ed3e1e89ce40 Mon Sep 17 00:00:00 2001
From: Eren <erengolge@gmail.com>
Date: Fri, 21 Sep 2018 17:27:02 +0200
Subject: [PATCH] Make audio folder and save audio with scipy

---
 train.py       | 2 +-
 utils/audio.py | 4 +++-
 2 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/train.py b/train.py
index d8a75b1d..55659a4b 100644
--- a/train.py
+++ b/train.py
@@ -474,7 +474,7 @@ if __name__ == '__main__':
     OUT_PATH = create_experiment_folder(OUT_PATH, c.model_name, args.debug)
     CHECKPOINT_PATH = os.path.join(OUT_PATH, 'checkpoints')
     AUDIO_PATH = os.path.join(OUT_PATH, 'test_audios')
-    os.mkdir(AUDIO_PATH)
+    os.makedirs(AUDIO_PATH, exist_ok=True)
     shutil.copyfile(args.config_path, os.path.join(OUT_PATH, 'config.json'))
 
     # setup tensorboard
diff --git a/utils/audio.py b/utils/audio.py
index 4ea5bfe0..9849cc93 100644
--- a/utils/audio.py
+++ b/utils/audio.py
@@ -3,6 +3,7 @@ import librosa
 import pickle
 import copy
 import numpy as np
+import scipy
 from scipy import signal
 
 _mel_basis = None
@@ -38,7 +39,8 @@ class AudioProcessor(object):
 
     def save_wav(self, wav, path):
         wav_norm = wav * (32767 / max(0.01, np.max(np.abs(wav))))
-        librosa.output.write_wav(path, wav_norm.astype(np.int16), self.sample_rate)
+        # librosa.output.write_wav(path, wav_norm.astype(np.int16), self.sample_rate)
+        scipy.io.wavfile.write(path, self.sample_rate, wav.astype(np.int16))
 
     def _linear_to_mel(self, spectrogram):
         global _mel_basis