From 2f933cb101e56c3c12c76c38d368b94111b52f64 Mon Sep 17 00:00:00 2001
From: speech_asr <wangjiaming.wjm@alibaba-inc.com>
Date: 星期三, 15 三月 2023 15:23:08 +0800
Subject: [PATCH] update
---
funasr/bin/eend_ola_inference.py | 8 ++++----
1 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/funasr/bin/eend_ola_inference.py b/funasr/bin/eend_ola_inference.py
index d191877..fbcfc7d 100755
--- a/funasr/bin/eend_ola_inference.py
+++ b/funasr/bin/eend_ola_inference.py
@@ -27,7 +27,6 @@
from funasr.utils.types import str2triple_str
from funasr.utils.types import str_or_none
-
class Speech2Diarization:
"""Speech2Diarlization class
@@ -121,7 +120,7 @@
Currently, the tags of espnet_model_zoo are supported.
Returns:
- Speech2Xvector: Speech2Xvector instance.
+ Speech2Diarization: Speech2Diarization instance.
"""
if model_tag is not None:
@@ -179,7 +178,6 @@
diar_model_file=diar_model_file,
device=device,
dtype=dtype,
- streaming=streaming,
)
logging.info("speech2diarization_kwargs: {}".format(speech2diar_kwargs))
speech2diar = Speech2Diarization.from_pretrained(
@@ -209,7 +207,7 @@
if data_path_and_name_and_type is None and raw_inputs is not None:
if isinstance(raw_inputs, torch.Tensor):
raw_inputs = raw_inputs.numpy()
- data_path_and_name_and_type = [raw_inputs, "speech", "waveform"]
+ data_path_and_name_and_type = [raw_inputs[0], "speech", "bytes"]
loader = EENDOLADiarTask.build_streaming_iterator(
data_path_and_name_and_type,
dtype=dtype,
@@ -229,6 +227,8 @@
output_writer = open("{}/result.txt".format(output_path), "w")
result_list = []
for keys, batch in loader:
+ logger.info("keys: {}".format(keys))
+ logger.info("batch: {}".format(batch))
assert isinstance(batch, dict), type(batch)
assert all(isinstance(s, str) for s in keys), keys
_bs = len(next(iter(batch.values())))
--
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