From 937e507977cc9e49ce323f8b2933087d0fe52698 Mon Sep 17 00:00:00 2001
From: zhifu gao <zhifu.gzf@alibaba-inc.com>
Date: 星期日, 16 四月 2023 22:29:32 +0800
Subject: [PATCH] Merge pull request #363 from alibaba-damo-academy/main
---
funasr/models/e2e_vad.py | 35 +++++++++++++++++++++++++++++++----
1 files changed, 31 insertions(+), 4 deletions(-)
diff --git a/funasr/models/e2e_vad.py b/funasr/models/e2e_vad.py
index e6cd7c0..50ec475 100644
--- a/funasr/models/e2e_vad.py
+++ b/funasr/models/e2e_vad.py
@@ -35,6 +35,11 @@
class VADXOptions:
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(
self,
sample_rate: int = 16000,
@@ -99,6 +104,11 @@
class E2EVadSpeechBufWithDoa(object):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self):
self.start_ms = 0
self.end_ms = 0
@@ -117,6 +127,11 @@
class E2EVadFrameProb(object):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self):
self.noise_prob = 0.0
self.speech_prob = 0.0
@@ -126,6 +141,11 @@
class WindowDetector(object):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
def __init__(self, window_size_ms: int, sil_to_speech_time: int,
speech_to_sil_time: int, frame_size_ms: int):
self.window_size_ms = window_size_ms
@@ -192,7 +212,12 @@
class E2EVadModel(nn.Module):
- def __init__(self, encoder: FSMN, vad_post_args: Dict[str, Any]):
+ """
+ Author: Speech Lab of DAMO Academy, Alibaba Group
+ Deep-FSMN for Large Vocabulary Continuous Speech Recognition
+ https://arxiv.org/abs/1803.05030
+ """
+ def __init__(self, encoder: FSMN, vad_post_args: Dict[str, Any], frontend=None):
super(E2EVadModel, self).__init__()
self.vad_opts = VADXOptions(**vad_post_args)
self.windows_detector = WindowDetector(self.vad_opts.window_size_ms,
@@ -229,6 +254,7 @@
self.data_buf_all = None
self.waveform = None
self.ResetDetection()
+ self.frontend = frontend
def AllResetDetection(self):
self.is_final = False
@@ -459,8 +485,8 @@
segment_batch = []
if len(self.output_data_buf) > 0:
for i in range(self.output_data_buf_offset, len(self.output_data_buf)):
- if not self.output_data_buf[i].contain_seg_start_point or not self.output_data_buf[
- i].contain_seg_end_point:
+ if not is_final and (not self.output_data_buf[i].contain_seg_start_point or not self.output_data_buf[
+ i].contain_seg_end_point):
continue
segment = [self.output_data_buf[i].start_ms, self.output_data_buf[i].end_ms]
segment_batch.append(segment)
@@ -477,8 +503,9 @@
) -> Tuple[List[List[List[int]]], Dict[str, torch.Tensor]]:
self.max_end_sil_frame_cnt_thresh = max_end_sil - self.vad_opts.speech_to_sil_time_thres
self.waveform = waveform # compute decibel for each frame
- self.ComputeDecibel()
+
self.ComputeScores(feats, in_cache)
+ self.ComputeDecibel()
if not is_final:
self.DetectCommonFrames()
else:
--
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