FIx vectorizing invalid files

precise/train_data.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 import json
 from argparse import ArgumentParser
+from contextlib import suppress
 from hashlib import md5
 from os.path import join, isfile, dirname
 from typing import *
@@ -178,8 +179,12 @@ class TrainData:
         outputs = []
 
         def add(filenames, output):
-            inputs.extend(load_vector(f, vectorizer) for f in filenames)
-            outputs.extend(np.array([output]) for _ in filenames)
+            for f in filenames:
+                try:
+                    inputs.append(load_vector(f, vectorizer))
+                    outputs.append(np.array([output]))
+                except ValueError:
+                    print('Skipping invalid file:', f)
 
         print('Loading wake-word...')
         add(kw_files, 1.0)

precise/vectorization.py

@@ -26,6 +26,8 @@ inhibit_hop_t = 0.1
 def vectorize_raw(audio: np.ndarray) -> np.ndarray:
     """Turns audio into feature vectors, without clipping for length"""
     from speechpy.feature import mfcc
+    if len(audio) == 0:
+        raise ValueError('Cannot vectorize empty audio!')
     return mfcc(audio, pr.sample_rate, pr.window_t, pr.hop_t, pr.n_mfcc, pr.n_filt, pr.n_fft)