From f5aa97f7bff53169a11a1e20ef1ff965438d1bc1 Mon Sep 17 00:00:00 2001
From: shixian.shi <shixian.shi@alibaba-inc.com>
Date: 星期一, 13 三月 2023 17:39:18 +0800
Subject: [PATCH] update params name
---
funasr/utils/timestamp_tools.py | 11 +++++------
1 files changed, 5 insertions(+), 6 deletions(-)
diff --git a/funasr/utils/timestamp_tools.py b/funasr/utils/timestamp_tools.py
index f8adbbc..f5a238e 100644
--- a/funasr/utils/timestamp_tools.py
+++ b/funasr/utils/timestamp_tools.py
@@ -6,10 +6,9 @@
def ts_prediction_lfr6_standard(us_alphas,
- us_cif_peak,
+ us_peaks,
char_list,
vad_offset=0.0,
- end_time=None,
force_time_shift=-1.5
):
if not len(char_list):
@@ -18,17 +17,17 @@
MAX_TOKEN_DURATION = 12
TIME_RATE = 10.0 * 6 / 1000 / 3 # 3 times upsampled
if len(us_alphas.shape) == 2:
- alphas, cif_peak = us_alphas[0], us_cif_peak[0] # support inference batch_size=1 only
+ _, peaks = us_alphas[0], us_peaks[0] # support inference batch_size=1 only
else:
- alphas, cif_peak = us_alphas, us_cif_peak
- num_frames = cif_peak.shape[0]
+ _, peaks = us_alphas, us_peaks
+ num_frames = peaks.shape[0]
if char_list[-1] == '</s>':
char_list = char_list[:-1]
timestamp_list = []
new_char_list = []
# for bicif model trained with large data, cif2 actually fires when a character starts
# so treat the frames between two peaks as the duration of the former token
- fire_place = torch.where(cif_peak>1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset
+ fire_place = torch.where(peaks>1.0-1e-4)[0].cpu().numpy() + force_time_shift # total offset
num_peak = len(fire_place)
assert num_peak == len(char_list) + 1 # number of peaks is supposed to be number of tokens + 1
# begin silence
--
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