| | |
| | | |
| | | def build_diar_model(args): |
| | | # token_list |
| | | if isinstance(args.token_list, str): |
| | | with open(args.token_list, encoding="utf-8") as f: |
| | | token_list = [line.rstrip() for line in f] |
| | | if args.token_list is not None: |
| | | if isinstance(args.token_list, str): |
| | | with open(args.token_list, encoding="utf-8") as f: |
| | | token_list = [line.rstrip() for line in f] |
| | | |
| | | # Overwriting token_list to keep it as "portable". |
| | | args.token_list = list(token_list) |
| | | elif isinstance(args.token_list, (tuple, list)): |
| | | token_list = list(args.token_list) |
| | | # Overwriting token_list to keep it as "portable". |
| | | args.token_list = list(token_list) |
| | | elif isinstance(args.token_list, (tuple, list)): |
| | | token_list = list(args.token_list) |
| | | else: |
| | | raise RuntimeError("token_list must be str or list") |
| | | vocab_size = len(token_list) |
| | | logging.info(f"Vocabulary size: {vocab_size}") |
| | | else: |
| | | raise RuntimeError("token_list must be str or list") |
| | | vocab_size = len(token_list) |
| | | logging.info(f"Vocabulary size: {vocab_size}") |
| | | token_list = None |
| | | vocab_size = None |
| | | |
| | | # frontend |
| | | if args.input_size is None: |
| | |
| | | frontend = frontend_class(cmvn_file=args.cmvn_file, **args.frontend_conf) |
| | | else: |
| | | frontend = frontend_class(**args.frontend_conf) |
| | | input_size = frontend.output_size() |
| | | else: |
| | | args.frontend = None |
| | | args.frontend_conf = {} |
| | | frontend = None |
| | | input_size = args.input_size |
| | | |
| | | # encoder |
| | | encoder_class = encoder_choices.get_class(args.encoder) |
| | | encoder = encoder_class(input_size=input_size, **args.encoder_conf) |
| | | encoder = encoder_class(**args.encoder_conf) |
| | | |
| | | if args.model == "sond": |
| | | # data augmentation for spectrogram |
| | |
| | | **args.model_conf, |
| | | ) |
| | | |
| | | elif args.model_name == "eend_ola": |
| | | elif args.model == "eend_ola": |
| | | # encoder-decoder attractor |
| | | encoder_decoder_attractor_class = encoder_decoder_attractor_choices.get_class(args.encoder_decoder_attractor) |
| | | encoder_decoder_attractor = encoder_decoder_attractor_class(**args.encoder_decoder_attractor_conf) |