Remove scorer after it's been used but only if it was generated

align/align.py

@@ -420,6 +420,7 @@ def main():
     output_graph_path = None
     for audio_path, tlog_path, script_path, aligned_path in to_prepare:
         if not exists(tlog_path):
+            generated_scorer = False
             if output_graph_path is None:
                 logging.debug('Looking for model files in "{}"...'.format(model_dir))
                 output_graph_path = glob(model_dir + "/*.pbmm")[0]
@@ -453,6 +454,8 @@ def main():
                     create_bundle(alphabet_path, scorer_path + '.' + 'lm.binary', scorer_path + '.' + 'vocab-500000.txt', scorer_path, False, 0.931289039105002, 1.1834137581510284)
                     os.remove(scorer_path + '.' + 'lm.binary')
                     os.remove(scorer_path + '.' + 'vocab-500000.txt')
+
+                    generated_scorer = True
             else:
                 scorer_path = lang_scorer_path
 
@@ -506,6 +509,10 @@ def main():
             logging.debug('Writing transcription log to file "{}"...'.format(tlog_path))
             with open(tlog_path, 'w', encoding='utf-8') as tlog_file:
                 tlog_file.write(json.dumps(fragments, indent=4 if args.output_pretty else None, ensure_ascii=False))
+
+            # Remove scorer if generated
+            if generated_scorer:
+                os.remove(scorer_path)
         if not path.isfile(tlog_path):
             fail('Problem loading transcript from "{}"'.format(tlog_path))
         to_align.append((tlog_path, script_path, aligned_path))
@@ -584,13 +591,13 @@ def parse_args():
     stt_group.add_argument('--stt-model-rate', type=int, default=DEFAULT_RATE,
                            help='Supported sample rate of the acoustic model')
     stt_group.add_argument('--stt-model-dir', required=False,
-                           help='Path to a directory with output_graph, lm, trie and (optional) alphabet file ' +
-                                '(default: "data/en"')
+                           help='Path to a directory with output_graph, scorer and (optional) alphabet file ' +
+                                '(default: "models/en"')
     stt_group.add_argument('--stt-no-own-lm', action="store_true",
                            help='Deactivates creation of individual language models per document.' +
                                 'Uses the one from model dir instead.')
     stt_group.add_argument('--stt-workers', type=int, required=False, default=1,
-                           help='Number of parallel STT workers - should 1 for GPU based DeepSpeech')
+                           help='Number of parallel STT workers - should be 1 for GPU based DeepSpeech')
     stt_group.add_argument('--stt-min-duration', type=int, required=False, default=100,
                            help='Minimum speech fragment duration in milliseconds to translate (default: 100)')
     stt_group.add_argument('--stt-max-duration', type=int, required=False,