From af6740a2207840a772261b8a033ab9996f862529 Mon Sep 17 00:00:00 2001
From: smohan-speech <smohan@mail.ustc.edu.cn>
Date: 星期一, 08 五月 2023 16:13:23 +0800
Subject: [PATCH] add speaker-attributed ASR task for alimeeting
---
funasr/bin/asr_inference.py | 9 +--------
1 files changed, 1 insertions(+), 8 deletions(-)
diff --git a/funasr/bin/asr_inference.py b/funasr/bin/asr_inference.py
index 18f0add..a52e94a 100644
--- a/funasr/bin/asr_inference.py
+++ b/funasr/bin/asr_inference.py
@@ -94,7 +94,7 @@
frontend = None
if asr_train_args.frontend is not None and asr_train_args.frontend_conf is not None:
if asr_train_args.frontend=='wav_frontend':
- frontend = WavFrontend(cmvn_file=cmvn_file, **asr_train_args.frontend_conf).eval()
+ frontend = WavFrontend(cmvn_file=cmvn_file, **asr_train_args.frontend_conf)
else:
frontend_class=frontend_choices.get_class(asr_train_args.frontend)
frontend = frontend_class(**asr_train_args.frontend_conf).eval()
@@ -146,13 +146,6 @@
token_list=token_list,
pre_beam_score_key=None if ctc_weight == 1.0 else "full",
)
-
- beam_search.to(device=device, dtype=getattr(torch, dtype)).eval()
- for scorer in scorers.values():
- if isinstance(scorer, torch.nn.Module):
- scorer.to(device=device, dtype=getattr(torch, dtype)).eval()
- logging.info(f"Beam_search: {beam_search}")
- logging.info(f"Decoding device={device}, dtype={dtype}")
# 5. [Optional] Build Text converter: e.g. bpe-sym -> Text
if token_type is None:
--
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