From 13c2af5de44d2ac4cb09677ab4fb07f37ade2b98 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期三, 06 九月 2023 11:51:46 +0800
Subject: [PATCH] fix empty timestamp list inference
---
funasr/bin/asr_inference_launch.py | 20 ++++++++++++--------
1 files changed, 12 insertions(+), 8 deletions(-)
diff --git a/funasr/bin/asr_inference_launch.py b/funasr/bin/asr_inference_launch.py
index 36c6d76..ffb0b26 100644
--- a/funasr/bin/asr_inference_launch.py
+++ b/funasr/bin/asr_inference_launch.py
@@ -260,8 +260,6 @@
hotword_list_or_file = None
clas_scale = 1.0
- if kwargs.get("device", None) == "cpu":
- ngpu = 0
if ngpu >= 1 and torch.cuda.is_available():
device = "cuda"
else:
@@ -411,7 +409,7 @@
ibest_writer["rtf"][key] = rtf_cur
if text is not None:
- if use_timestamp and timestamp is not None:
+ if use_timestamp and timestamp is not None and len(timestamp):
postprocessed_result = postprocess_utils.sentence_postprocess(token, timestamp)
else:
postprocessed_result = postprocess_utils.sentence_postprocess(token)
@@ -423,7 +421,7 @@
else:
text_postprocessed, word_lists = postprocessed_result[0], postprocessed_result[1]
item = {'key': key, 'value': text_postprocessed}
- if timestamp_postprocessed != "":
+ if timestamp_postprocessed != "" or len(timestamp) == 0:
item['timestamp'] = timestamp_postprocessed
asr_result_list.append(item)
finish_count += 1
@@ -566,6 +564,7 @@
hotword_list_or_file = kwargs['hotword']
speech2vadsegment.vad_model.vad_opts.max_single_segment_time = kwargs.get("max_single_segment_time", 60000)
+ batch_size_token_threshold_s = kwargs.get("batch_size_token_threshold_s", int(speech2vadsegment.vad_model.vad_opts.max_single_segment_time*0.67/1000)) * 1000
batch_size_token = kwargs.get("batch_size_token", 6000)
print("batch_size_token: ", batch_size_token)
@@ -648,7 +647,7 @@
beg_idx = 0
for j, _ in enumerate(range(0, n)):
batch_size_token_ms_cum += (sorted_data[j][0][1] - sorted_data[j][0][0])
- if j < n - 1 and (batch_size_token_ms_cum + sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0]) < batch_size_token_ms and (sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0]) < speech2vadsegment.vad_model.vad_opts.max_single_segment_time:
+ if j < n - 1 and (batch_size_token_ms_cum + sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0]) < batch_size_token_ms and (sorted_data[j + 1][0][1] - sorted_data[j + 1][0][0]) < batch_size_token_threshold_s:
continue
batch_size_token_ms_cum = 0
end_idx = j + 1
@@ -687,7 +686,7 @@
text, token, token_int = result[0], result[1], result[2]
time_stamp = result[4] if len(result[4]) > 0 else None
- if use_timestamp and time_stamp is not None:
+ if use_timestamp and time_stamp is not None and len(time_stamp):
postprocessed_result = postprocess_utils.sentence_postprocess(token, time_stamp)
else:
postprocessed_result = postprocess_utils.sentence_postprocess(token)
@@ -712,7 +711,7 @@
item = {'key': key, 'value': text_postprocessed_punc}
if text_postprocessed != "":
item['text_postprocessed'] = text_postprocessed
- if time_stamp_postprocessed != "":
+ if time_stamp_postprocessed != "" or len(time_stamp) == 0:
item['time_stamp'] = time_stamp_postprocessed
item['sentences'] = time_stamp_sentence(punc_id_list, time_stamp_postprocessed, text_postprocessed)
@@ -1291,6 +1290,7 @@
quantize_dtype: Optional[str] = "float16",
streaming: Optional[bool] = False,
simu_streaming: Optional[bool] = False,
+ full_utt: Optional[bool] = False,
chunk_size: Optional[int] = 16,
left_context: Optional[int] = 16,
right_context: Optional[int] = 0,
@@ -1367,6 +1367,7 @@
quantize_dtype=quantize_dtype,
streaming=streaming,
simu_streaming=simu_streaming,
+ full_utt=full_utt,
chunk_size=chunk_size,
left_context=left_context,
right_context=right_context,
@@ -1417,7 +1418,7 @@
_end = (i + 1) * speech2text._ctx
speech2text.streaming_decode(
- speech[i * speech2text._ctx: _end], is_final=False
+ speech[i * speech2text._ctx: _end + speech2text._right_ctx], is_final=False
)
final_hyps = speech2text.streaming_decode(
@@ -1425,6 +1426,8 @@
)
elif speech2text.simu_streaming:
final_hyps = speech2text.simu_streaming_decode(**batch)
+ elif speech2text.full_utt:
+ final_hyps = speech2text.full_utt_decode(**batch)
else:
final_hyps = speech2text(**batch)
@@ -1813,6 +1816,7 @@
group.add_argument("--ngram_weight", type=float, default=0.9, help="ngram weight")
group.add_argument("--streaming", type=str2bool, default=False)
group.add_argument("--simu_streaming", type=str2bool, default=False)
+ group.add_argument("--full_utt", type=str2bool, default=False)
group.add_argument("--chunk_size", type=int, default=16)
group.add_argument("--left_context", type=int, default=16)
group.add_argument("--right_context", type=int, default=0)
--
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