705 lines
29 KiB
Python
705 lines
29 KiB
Python
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# -*- encoding: utf-8 -*-
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# Copyright FunASR (https://github.com/alibaba-damo-academy/FunASR). All Rights Reserved.
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# MIT License (https://opensource.org/licenses/MIT)
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from enum import Enum
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from typing import List, Tuple, Dict, Any
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import math
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import numpy as np
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class VadStateMachine(Enum):
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kVadInStateStartPointNotDetected = 1
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kVadInStateInSpeechSegment = 2
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kVadInStateEndPointDetected = 3
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class FrameState(Enum):
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kFrameStateInvalid = -1
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kFrameStateSpeech = 1
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kFrameStateSil = 0
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# final voice/unvoice state per frame
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class AudioChangeState(Enum):
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kChangeStateSpeech2Speech = 0
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kChangeStateSpeech2Sil = 1
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kChangeStateSil2Sil = 2
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kChangeStateSil2Speech = 3
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kChangeStateNoBegin = 4
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kChangeStateInvalid = 5
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class VadDetectMode(Enum):
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kVadSingleUtteranceDetectMode = 0
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kVadMutipleUtteranceDetectMode = 1
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class VADXOptions:
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def __init__(
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self,
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sample_rate: int = 16000,
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detect_mode: int = VadDetectMode.kVadMutipleUtteranceDetectMode.value,
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snr_mode: int = 0,
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max_end_silence_time: int = 800,
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max_start_silence_time: int = 3000,
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do_start_point_detection: bool = True,
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do_end_point_detection: bool = True,
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window_size_ms: int = 200,
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sil_to_speech_time_thres: int = 150,
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speech_to_sil_time_thres: int = 150,
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speech_2_noise_ratio: float = 1.0,
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do_extend: int = 1,
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lookback_time_start_point: int = 200,
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lookahead_time_end_point: int = 100,
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max_single_segment_time: int = 60000,
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nn_eval_block_size: int = 8,
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dcd_block_size: int = 4,
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snr_thres: int = -100.0,
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noise_frame_num_used_for_snr: int = 100,
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decibel_thres: int = -100.0,
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speech_noise_thres: float = 0.6,
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fe_prior_thres: float = 1e-4,
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silence_pdf_num: int = 1,
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sil_pdf_ids: List[int] = [0],
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speech_noise_thresh_low: float = -0.1,
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speech_noise_thresh_high: float = 0.3,
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output_frame_probs: bool = False,
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frame_in_ms: int = 10,
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frame_length_ms: int = 25,
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):
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self.sample_rate = sample_rate
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self.detect_mode = detect_mode
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self.snr_mode = snr_mode
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self.max_end_silence_time = max_end_silence_time
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self.max_start_silence_time = max_start_silence_time
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self.do_start_point_detection = do_start_point_detection
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self.do_end_point_detection = do_end_point_detection
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self.window_size_ms = window_size_ms
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self.sil_to_speech_time_thres = sil_to_speech_time_thres
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self.speech_to_sil_time_thres = speech_to_sil_time_thres
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self.speech_2_noise_ratio = speech_2_noise_ratio
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self.do_extend = do_extend
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self.lookback_time_start_point = lookback_time_start_point
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self.lookahead_time_end_point = lookahead_time_end_point
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self.max_single_segment_time = max_single_segment_time
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self.nn_eval_block_size = nn_eval_block_size
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self.dcd_block_size = dcd_block_size
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self.snr_thres = snr_thres
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self.noise_frame_num_used_for_snr = noise_frame_num_used_for_snr
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self.decibel_thres = decibel_thres
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self.speech_noise_thres = speech_noise_thres
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self.fe_prior_thres = fe_prior_thres
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self.silence_pdf_num = silence_pdf_num
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self.sil_pdf_ids = sil_pdf_ids
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self.speech_noise_thresh_low = speech_noise_thresh_low
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self.speech_noise_thresh_high = speech_noise_thresh_high
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self.output_frame_probs = output_frame_probs
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self.frame_in_ms = frame_in_ms
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self.frame_length_ms = frame_length_ms
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class E2EVadSpeechBufWithDoa(object):
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def __init__(self):
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self.start_ms = 0
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self.end_ms = 0
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self.buffer = []
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self.contain_seg_start_point = False
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self.contain_seg_end_point = False
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self.doa = 0
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def Reset(self):
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self.start_ms = 0
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self.end_ms = 0
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self.buffer = []
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self.contain_seg_start_point = False
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self.contain_seg_end_point = False
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self.doa = 0
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class E2EVadFrameProb(object):
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def __init__(self):
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self.noise_prob = 0.0
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self.speech_prob = 0.0
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self.score = 0.0
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self.frame_id = 0
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self.frm_state = 0
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class WindowDetector(object):
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def __init__(
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self,
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window_size_ms: int,
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sil_to_speech_time: int,
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speech_to_sil_time: int,
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frame_size_ms: int,
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):
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self.window_size_ms = window_size_ms
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self.sil_to_speech_time = sil_to_speech_time
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self.speech_to_sil_time = speech_to_sil_time
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self.frame_size_ms = frame_size_ms
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self.win_size_frame = int(window_size_ms / frame_size_ms)
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self.win_sum = 0
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self.win_state = [0] * self.win_size_frame # 初始化窗
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self.cur_win_pos = 0
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self.pre_frame_state = FrameState.kFrameStateSil
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self.cur_frame_state = FrameState.kFrameStateSil
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self.sil_to_speech_frmcnt_thres = int(sil_to_speech_time / frame_size_ms)
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self.speech_to_sil_frmcnt_thres = int(speech_to_sil_time / frame_size_ms)
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self.voice_last_frame_count = 0
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self.noise_last_frame_count = 0
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self.hydre_frame_count = 0
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def Reset(self) -> None:
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self.cur_win_pos = 0
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self.win_sum = 0
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self.win_state = [0] * self.win_size_frame
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self.pre_frame_state = FrameState.kFrameStateSil
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self.cur_frame_state = FrameState.kFrameStateSil
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self.voice_last_frame_count = 0
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self.noise_last_frame_count = 0
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self.hydre_frame_count = 0
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def GetWinSize(self) -> int:
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return int(self.win_size_frame)
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def DetectOneFrame(self, frameState: FrameState, frame_count: int) -> AudioChangeState:
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cur_frame_state = FrameState.kFrameStateSil
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if frameState == FrameState.kFrameStateSpeech:
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cur_frame_state = 1
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elif frameState == FrameState.kFrameStateSil:
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cur_frame_state = 0
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else:
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return AudioChangeState.kChangeStateInvalid
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self.win_sum -= self.win_state[self.cur_win_pos]
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self.win_sum += cur_frame_state
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self.win_state[self.cur_win_pos] = cur_frame_state
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self.cur_win_pos = (self.cur_win_pos + 1) % self.win_size_frame
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if (
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self.pre_frame_state == FrameState.kFrameStateSil
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and self.win_sum >= self.sil_to_speech_frmcnt_thres
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):
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self.pre_frame_state = FrameState.kFrameStateSpeech
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return AudioChangeState.kChangeStateSil2Speech
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if (
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self.pre_frame_state == FrameState.kFrameStateSpeech
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and self.win_sum <= self.speech_to_sil_frmcnt_thres
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):
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self.pre_frame_state = FrameState.kFrameStateSil
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return AudioChangeState.kChangeStateSpeech2Sil
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if self.pre_frame_state == FrameState.kFrameStateSil:
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return AudioChangeState.kChangeStateSil2Sil
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if self.pre_frame_state == FrameState.kFrameStateSpeech:
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return AudioChangeState.kChangeStateSpeech2Speech
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return AudioChangeState.kChangeStateInvalid
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def FrameSizeMs(self) -> int:
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return int(self.frame_size_ms)
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class E2EVadModel:
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"""
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Author: Speech Lab of DAMO Academy, Alibaba Group
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Deep-FSMN for Large Vocabulary Continuous Speech Recognition
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https://arxiv.org/abs/1803.05030
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"""
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def __init__(self, vad_post_args: Dict[str, Any]):
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super(E2EVadModel, self).__init__()
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self.vad_opts = VADXOptions(**vad_post_args)
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self.windows_detector = WindowDetector(
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self.vad_opts.window_size_ms,
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self.vad_opts.sil_to_speech_time_thres,
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self.vad_opts.speech_to_sil_time_thres,
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self.vad_opts.frame_in_ms,
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)
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# self.encoder = encoder
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# init variables
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self.is_final = False
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self.data_buf_start_frame = 0
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self.frm_cnt = 0
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self.latest_confirmed_speech_frame = 0
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self.lastest_confirmed_silence_frame = -1
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self.continous_silence_frame_count = 0
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self.vad_state_machine = VadStateMachine.kVadInStateStartPointNotDetected
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self.confirmed_start_frame = -1
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self.confirmed_end_frame = -1
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self.number_end_time_detected = 0
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self.sil_frame = 0
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self.sil_pdf_ids = self.vad_opts.sil_pdf_ids
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self.noise_average_decibel = -100.0
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self.pre_end_silence_detected = False
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self.next_seg = True
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self.output_data_buf = []
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self.output_data_buf_offset = 0
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self.frame_probs = []
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self.max_end_sil_frame_cnt_thresh = (
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self.vad_opts.max_end_silence_time - self.vad_opts.speech_to_sil_time_thres
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)
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self.speech_noise_thres = self.vad_opts.speech_noise_thres
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self.scores = None
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self.idx_pre_chunk = 0
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self.max_time_out = False
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self.decibel = []
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self.data_buf_size = 0
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self.data_buf_all_size = 0
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self.waveform = None
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self.ResetDetection()
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def AllResetDetection(self):
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self.is_final = False
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self.data_buf_start_frame = 0
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self.frm_cnt = 0
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self.latest_confirmed_speech_frame = 0
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self.lastest_confirmed_silence_frame = -1
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self.continous_silence_frame_count = 0
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self.vad_state_machine = VadStateMachine.kVadInStateStartPointNotDetected
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self.confirmed_start_frame = -1
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self.confirmed_end_frame = -1
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self.number_end_time_detected = 0
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self.sil_frame = 0
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self.sil_pdf_ids = self.vad_opts.sil_pdf_ids
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self.noise_average_decibel = -100.0
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self.pre_end_silence_detected = False
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self.next_seg = True
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self.output_data_buf = []
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self.output_data_buf_offset = 0
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self.frame_probs = []
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self.max_end_sil_frame_cnt_thresh = (
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self.vad_opts.max_end_silence_time - self.vad_opts.speech_to_sil_time_thres
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)
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self.speech_noise_thres = self.vad_opts.speech_noise_thres
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self.scores = None
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self.idx_pre_chunk = 0
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self.max_time_out = False
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self.decibel = []
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self.data_buf_size = 0
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self.data_buf_all_size = 0
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self.waveform = None
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self.ResetDetection()
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def ResetDetection(self):
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self.continous_silence_frame_count = 0
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self.latest_confirmed_speech_frame = 0
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self.lastest_confirmed_silence_frame = -1
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self.confirmed_start_frame = -1
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self.confirmed_end_frame = -1
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self.vad_state_machine = VadStateMachine.kVadInStateStartPointNotDetected
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self.windows_detector.Reset()
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self.sil_frame = 0
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self.frame_probs = []
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def ComputeDecibel(self) -> None:
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frame_sample_length = int(self.vad_opts.frame_length_ms * self.vad_opts.sample_rate / 1000)
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frame_shift_length = int(self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000)
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if self.data_buf_all_size == 0:
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self.data_buf_all_size = len(self.waveform[0])
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self.data_buf_size = self.data_buf_all_size
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else:
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self.data_buf_all_size += len(self.waveform[0])
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for offset in range(
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0, self.waveform.shape[1] - frame_sample_length + 1, frame_shift_length
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):
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self.decibel.append(
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10
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* math.log10(
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np.square((self.waveform[0][offset : offset + frame_sample_length])).sum()
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+ 0.000001
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)
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)
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def ComputeScores(self, scores: np.ndarray) -> None:
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# scores = self.encoder(feats, in_cache) # return B * T * D
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self.vad_opts.nn_eval_block_size = scores.shape[1]
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self.frm_cnt += scores.shape[1] # count total frames
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self.scores = scores
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def PopDataBufTillFrame(self, frame_idx: int) -> None: # need check again
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while self.data_buf_start_frame < frame_idx:
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if self.data_buf_size >= int(
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self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000
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):
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self.data_buf_start_frame += 1
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self.data_buf_size = self.data_buf_all_size - self.data_buf_start_frame * int(
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self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000
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)
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def PopDataToOutputBuf(
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self,
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start_frm: int,
|
||
|
|
frm_cnt: int,
|
||
|
|
first_frm_is_start_point: bool,
|
||
|
|
last_frm_is_end_point: bool,
|
||
|
|
end_point_is_sent_end: bool,
|
||
|
|
) -> None:
|
||
|
|
self.PopDataBufTillFrame(start_frm)
|
||
|
|
expected_sample_number = int(
|
||
|
|
frm_cnt * self.vad_opts.sample_rate * self.vad_opts.frame_in_ms / 1000
|
||
|
|
)
|
||
|
|
if last_frm_is_end_point:
|
||
|
|
extra_sample = max(
|
||
|
|
0,
|
||
|
|
int(
|
||
|
|
self.vad_opts.frame_length_ms * self.vad_opts.sample_rate / 1000
|
||
|
|
- self.vad_opts.sample_rate * self.vad_opts.frame_in_ms / 1000
|
||
|
|
),
|
||
|
|
)
|
||
|
|
expected_sample_number += int(extra_sample)
|
||
|
|
if end_point_is_sent_end:
|
||
|
|
expected_sample_number = max(expected_sample_number, self.data_buf_size)
|
||
|
|
if self.data_buf_size < expected_sample_number:
|
||
|
|
print("error in calling pop data_buf\n")
|
||
|
|
|
||
|
|
if len(self.output_data_buf) == 0 or first_frm_is_start_point:
|
||
|
|
self.output_data_buf.append(E2EVadSpeechBufWithDoa())
|
||
|
|
self.output_data_buf[-1].Reset()
|
||
|
|
self.output_data_buf[-1].start_ms = start_frm * self.vad_opts.frame_in_ms
|
||
|
|
self.output_data_buf[-1].end_ms = self.output_data_buf[-1].start_ms
|
||
|
|
self.output_data_buf[-1].doa = 0
|
||
|
|
cur_seg = self.output_data_buf[-1]
|
||
|
|
if cur_seg.end_ms != start_frm * self.vad_opts.frame_in_ms:
|
||
|
|
print("warning\n")
|
||
|
|
out_pos = len(cur_seg.buffer) # cur_seg.buff现在没做任何操作
|
||
|
|
data_to_pop = 0
|
||
|
|
if end_point_is_sent_end:
|
||
|
|
data_to_pop = expected_sample_number
|
||
|
|
else:
|
||
|
|
data_to_pop = int(
|
||
|
|
frm_cnt * self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000
|
||
|
|
)
|
||
|
|
if data_to_pop > self.data_buf_size:
|
||
|
|
print("VAD data_to_pop is bigger than self.data_buf_size!!!\n")
|
||
|
|
data_to_pop = self.data_buf_size
|
||
|
|
expected_sample_number = self.data_buf_size
|
||
|
|
|
||
|
|
cur_seg.doa = 0
|
||
|
|
for sample_cpy_out in range(0, data_to_pop):
|
||
|
|
# cur_seg.buffer[out_pos ++] = data_buf_.back();
|
||
|
|
out_pos += 1
|
||
|
|
for sample_cpy_out in range(data_to_pop, expected_sample_number):
|
||
|
|
# cur_seg.buffer[out_pos++] = data_buf_.back()
|
||
|
|
out_pos += 1
|
||
|
|
if cur_seg.end_ms != start_frm * self.vad_opts.frame_in_ms:
|
||
|
|
print("Something wrong with the VAD algorithm\n")
|
||
|
|
self.data_buf_start_frame += frm_cnt
|
||
|
|
cur_seg.end_ms = (start_frm + frm_cnt) * self.vad_opts.frame_in_ms
|
||
|
|
if first_frm_is_start_point:
|
||
|
|
cur_seg.contain_seg_start_point = True
|
||
|
|
if last_frm_is_end_point:
|
||
|
|
cur_seg.contain_seg_end_point = True
|
||
|
|
|
||
|
|
def OnSilenceDetected(self, valid_frame: int):
|
||
|
|
self.lastest_confirmed_silence_frame = valid_frame
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateStartPointNotDetected:
|
||
|
|
self.PopDataBufTillFrame(valid_frame)
|
||
|
|
# silence_detected_callback_
|
||
|
|
# pass
|
||
|
|
|
||
|
|
def OnVoiceDetected(self, valid_frame: int) -> None:
|
||
|
|
self.latest_confirmed_speech_frame = valid_frame
|
||
|
|
self.PopDataToOutputBuf(valid_frame, 1, False, False, False)
|
||
|
|
|
||
|
|
def OnVoiceStart(self, start_frame: int, fake_result: bool = False) -> None:
|
||
|
|
if self.vad_opts.do_start_point_detection:
|
||
|
|
pass
|
||
|
|
if self.confirmed_start_frame != -1:
|
||
|
|
print("not reset vad properly\n")
|
||
|
|
else:
|
||
|
|
self.confirmed_start_frame = start_frame
|
||
|
|
|
||
|
|
if (
|
||
|
|
not fake_result
|
||
|
|
and self.vad_state_machine == VadStateMachine.kVadInStateStartPointNotDetected
|
||
|
|
):
|
||
|
|
self.PopDataToOutputBuf(self.confirmed_start_frame, 1, True, False, False)
|
||
|
|
|
||
|
|
def OnVoiceEnd(self, end_frame: int, fake_result: bool, is_last_frame: bool) -> None:
|
||
|
|
for t in range(self.latest_confirmed_speech_frame + 1, end_frame):
|
||
|
|
self.OnVoiceDetected(t)
|
||
|
|
if self.vad_opts.do_end_point_detection:
|
||
|
|
pass
|
||
|
|
if self.confirmed_end_frame != -1:
|
||
|
|
print("not reset vad properly\n")
|
||
|
|
else:
|
||
|
|
self.confirmed_end_frame = end_frame
|
||
|
|
if not fake_result:
|
||
|
|
self.sil_frame = 0
|
||
|
|
self.PopDataToOutputBuf(self.confirmed_end_frame, 1, False, True, is_last_frame)
|
||
|
|
self.number_end_time_detected += 1
|
||
|
|
|
||
|
|
def MaybeOnVoiceEndIfLastFrame(self, is_final_frame: bool, cur_frm_idx: int) -> None:
|
||
|
|
if is_final_frame:
|
||
|
|
self.OnVoiceEnd(cur_frm_idx, False, True)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
|
||
|
|
def GetLatency(self) -> int:
|
||
|
|
return int(self.LatencyFrmNumAtStartPoint() * self.vad_opts.frame_in_ms)
|
||
|
|
|
||
|
|
def LatencyFrmNumAtStartPoint(self) -> int:
|
||
|
|
vad_latency = self.windows_detector.GetWinSize()
|
||
|
|
if self.vad_opts.do_extend:
|
||
|
|
vad_latency += int(self.vad_opts.lookback_time_start_point / self.vad_opts.frame_in_ms)
|
||
|
|
return vad_latency
|
||
|
|
|
||
|
|
def GetFrameState(self, t: int) -> FrameState:
|
||
|
|
frame_state = FrameState.kFrameStateInvalid
|
||
|
|
cur_decibel = self.decibel[t]
|
||
|
|
cur_snr = cur_decibel - self.noise_average_decibel
|
||
|
|
# for each frame, calc log posterior probability of each state
|
||
|
|
if cur_decibel < self.vad_opts.decibel_thres:
|
||
|
|
frame_state = FrameState.kFrameStateSil
|
||
|
|
self.DetectOneFrame(frame_state, t, False)
|
||
|
|
return frame_state
|
||
|
|
|
||
|
|
sum_score = 0.0
|
||
|
|
noise_prob = 0.0
|
||
|
|
assert len(self.sil_pdf_ids) == self.vad_opts.silence_pdf_num
|
||
|
|
if len(self.sil_pdf_ids) > 0:
|
||
|
|
assert len(self.scores) == 1 # 只支持batch_size = 1的测试
|
||
|
|
sil_pdf_scores = [
|
||
|
|
self.scores[0][t - self.idx_pre_chunk][sil_pdf_id]
|
||
|
|
for sil_pdf_id in self.sil_pdf_ids
|
||
|
|
]
|
||
|
|
sum_score = sum(sil_pdf_scores)
|
||
|
|
noise_prob = math.log(sum_score) * self.vad_opts.speech_2_noise_ratio
|
||
|
|
total_score = 1.0
|
||
|
|
sum_score = total_score - sum_score
|
||
|
|
speech_prob = math.log(sum_score)
|
||
|
|
if self.vad_opts.output_frame_probs:
|
||
|
|
frame_prob = E2EVadFrameProb()
|
||
|
|
frame_prob.noise_prob = noise_prob
|
||
|
|
frame_prob.speech_prob = speech_prob
|
||
|
|
frame_prob.score = sum_score
|
||
|
|
frame_prob.frame_id = t
|
||
|
|
self.frame_probs.append(frame_prob)
|
||
|
|
if math.exp(speech_prob) >= math.exp(noise_prob) + self.speech_noise_thres:
|
||
|
|
if cur_snr >= self.vad_opts.snr_thres and cur_decibel >= self.vad_opts.decibel_thres:
|
||
|
|
frame_state = FrameState.kFrameStateSpeech
|
||
|
|
else:
|
||
|
|
frame_state = FrameState.kFrameStateSil
|
||
|
|
else:
|
||
|
|
frame_state = FrameState.kFrameStateSil
|
||
|
|
if self.noise_average_decibel < -99.9:
|
||
|
|
self.noise_average_decibel = cur_decibel
|
||
|
|
else:
|
||
|
|
self.noise_average_decibel = (
|
||
|
|
cur_decibel
|
||
|
|
+ self.noise_average_decibel * (self.vad_opts.noise_frame_num_used_for_snr - 1)
|
||
|
|
) / self.vad_opts.noise_frame_num_used_for_snr
|
||
|
|
|
||
|
|
return frame_state
|
||
|
|
|
||
|
|
def __call__(
|
||
|
|
self,
|
||
|
|
score: np.ndarray,
|
||
|
|
waveform: np.ndarray,
|
||
|
|
is_final: bool = False,
|
||
|
|
max_end_sil: int = 800,
|
||
|
|
online: bool = False,
|
||
|
|
):
|
||
|
|
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(score)
|
||
|
|
if not is_final:
|
||
|
|
self.DetectCommonFrames()
|
||
|
|
else:
|
||
|
|
self.DetectLastFrames()
|
||
|
|
segments = []
|
||
|
|
for batch_num in range(0, score.shape[0]): # only support batch_size = 1 now
|
||
|
|
segment_batch = []
|
||
|
|
if len(self.output_data_buf) > 0:
|
||
|
|
for i in range(self.output_data_buf_offset, len(self.output_data_buf)):
|
||
|
|
if online:
|
||
|
|
if not self.output_data_buf[i].contain_seg_start_point:
|
||
|
|
continue
|
||
|
|
if not self.next_seg and not self.output_data_buf[i].contain_seg_end_point:
|
||
|
|
continue
|
||
|
|
start_ms = self.output_data_buf[i].start_ms if self.next_seg else -1
|
||
|
|
if self.output_data_buf[i].contain_seg_end_point:
|
||
|
|
end_ms = self.output_data_buf[i].end_ms
|
||
|
|
self.next_seg = True
|
||
|
|
self.output_data_buf_offset += 1
|
||
|
|
else:
|
||
|
|
end_ms = -1
|
||
|
|
self.next_seg = False
|
||
|
|
else:
|
||
|
|
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
|
||
|
|
start_ms = self.output_data_buf[i].start_ms
|
||
|
|
end_ms = self.output_data_buf[i].end_ms
|
||
|
|
self.output_data_buf_offset += 1
|
||
|
|
segment = [start_ms, end_ms]
|
||
|
|
segment_batch.append(segment)
|
||
|
|
|
||
|
|
if segment_batch:
|
||
|
|
segments.append(segment_batch)
|
||
|
|
if is_final:
|
||
|
|
# reset class variables and clear the dict for the next query
|
||
|
|
self.AllResetDetection()
|
||
|
|
return segments
|
||
|
|
|
||
|
|
def DetectCommonFrames(self) -> int:
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateEndPointDetected:
|
||
|
|
return 0
|
||
|
|
for i in range(self.vad_opts.nn_eval_block_size - 1, -1, -1):
|
||
|
|
frame_state = FrameState.kFrameStateInvalid
|
||
|
|
frame_state = self.GetFrameState(self.frm_cnt - 1 - i)
|
||
|
|
self.DetectOneFrame(frame_state, self.frm_cnt - 1 - i, False)
|
||
|
|
self.idx_pre_chunk += self.scores.shape[1]
|
||
|
|
return 0
|
||
|
|
|
||
|
|
def DetectLastFrames(self) -> int:
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateEndPointDetected:
|
||
|
|
return 0
|
||
|
|
for i in range(self.vad_opts.nn_eval_block_size - 1, -1, -1):
|
||
|
|
frame_state = FrameState.kFrameStateInvalid
|
||
|
|
frame_state = self.GetFrameState(self.frm_cnt - 1 - i)
|
||
|
|
if i != 0:
|
||
|
|
self.DetectOneFrame(frame_state, self.frm_cnt - 1 - i, False)
|
||
|
|
else:
|
||
|
|
self.DetectOneFrame(frame_state, self.frm_cnt - 1, True)
|
||
|
|
|
||
|
|
return 0
|
||
|
|
|
||
|
|
def DetectOneFrame(
|
||
|
|
self, cur_frm_state: FrameState, cur_frm_idx: int, is_final_frame: bool
|
||
|
|
) -> None:
|
||
|
|
tmp_cur_frm_state = FrameState.kFrameStateInvalid
|
||
|
|
if cur_frm_state == FrameState.kFrameStateSpeech:
|
||
|
|
if math.fabs(1.0) > self.vad_opts.fe_prior_thres:
|
||
|
|
tmp_cur_frm_state = FrameState.kFrameStateSpeech
|
||
|
|
else:
|
||
|
|
tmp_cur_frm_state = FrameState.kFrameStateSil
|
||
|
|
elif cur_frm_state == FrameState.kFrameStateSil:
|
||
|
|
tmp_cur_frm_state = FrameState.kFrameStateSil
|
||
|
|
state_change = self.windows_detector.DetectOneFrame(tmp_cur_frm_state, cur_frm_idx)
|
||
|
|
frm_shift_in_ms = self.vad_opts.frame_in_ms
|
||
|
|
if AudioChangeState.kChangeStateSil2Speech == state_change:
|
||
|
|
silence_frame_count = self.continous_silence_frame_count
|
||
|
|
self.continous_silence_frame_count = 0
|
||
|
|
self.pre_end_silence_detected = False
|
||
|
|
start_frame = 0
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateStartPointNotDetected:
|
||
|
|
start_frame = max(
|
||
|
|
self.data_buf_start_frame, cur_frm_idx - self.LatencyFrmNumAtStartPoint()
|
||
|
|
)
|
||
|
|
self.OnVoiceStart(start_frame)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateInSpeechSegment
|
||
|
|
for t in range(start_frame + 1, cur_frm_idx + 1):
|
||
|
|
self.OnVoiceDetected(t)
|
||
|
|
elif self.vad_state_machine == VadStateMachine.kVadInStateInSpeechSegment:
|
||
|
|
for t in range(self.latest_confirmed_speech_frame + 1, cur_frm_idx):
|
||
|
|
self.OnVoiceDetected(t)
|
||
|
|
if (
|
||
|
|
cur_frm_idx - self.confirmed_start_frame + 1
|
||
|
|
> self.vad_opts.max_single_segment_time / frm_shift_in_ms
|
||
|
|
):
|
||
|
|
self.OnVoiceEnd(cur_frm_idx, False, False)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
elif not is_final_frame:
|
||
|
|
self.OnVoiceDetected(cur_frm_idx)
|
||
|
|
else:
|
||
|
|
self.MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx)
|
||
|
|
else:
|
||
|
|
pass
|
||
|
|
elif AudioChangeState.kChangeStateSpeech2Sil == state_change:
|
||
|
|
self.continous_silence_frame_count = 0
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateStartPointNotDetected:
|
||
|
|
pass
|
||
|
|
elif self.vad_state_machine == VadStateMachine.kVadInStateInSpeechSegment:
|
||
|
|
if (
|
||
|
|
cur_frm_idx - self.confirmed_start_frame + 1
|
||
|
|
> self.vad_opts.max_single_segment_time / frm_shift_in_ms
|
||
|
|
):
|
||
|
|
self.OnVoiceEnd(cur_frm_idx, False, False)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
elif not is_final_frame:
|
||
|
|
self.OnVoiceDetected(cur_frm_idx)
|
||
|
|
else:
|
||
|
|
self.MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx)
|
||
|
|
else:
|
||
|
|
pass
|
||
|
|
elif AudioChangeState.kChangeStateSpeech2Speech == state_change:
|
||
|
|
self.continous_silence_frame_count = 0
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateInSpeechSegment:
|
||
|
|
if (
|
||
|
|
cur_frm_idx - self.confirmed_start_frame + 1
|
||
|
|
> self.vad_opts.max_single_segment_time / frm_shift_in_ms
|
||
|
|
):
|
||
|
|
self.max_time_out = True
|
||
|
|
self.OnVoiceEnd(cur_frm_idx, False, False)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
elif not is_final_frame:
|
||
|
|
self.OnVoiceDetected(cur_frm_idx)
|
||
|
|
else:
|
||
|
|
self.MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx)
|
||
|
|
else:
|
||
|
|
pass
|
||
|
|
elif AudioChangeState.kChangeStateSil2Sil == state_change:
|
||
|
|
self.continous_silence_frame_count += 1
|
||
|
|
if self.vad_state_machine == VadStateMachine.kVadInStateStartPointNotDetected:
|
||
|
|
# silence timeout, return zero length decision
|
||
|
|
if (
|
||
|
|
(self.vad_opts.detect_mode == VadDetectMode.kVadSingleUtteranceDetectMode.value)
|
||
|
|
and (
|
||
|
|
self.continous_silence_frame_count * frm_shift_in_ms
|
||
|
|
> self.vad_opts.max_start_silence_time
|
||
|
|
)
|
||
|
|
) or (is_final_frame and self.number_end_time_detected == 0):
|
||
|
|
for t in range(self.lastest_confirmed_silence_frame + 1, cur_frm_idx):
|
||
|
|
self.OnSilenceDetected(t)
|
||
|
|
self.OnVoiceStart(0, True)
|
||
|
|
self.OnVoiceEnd(0, True, False)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
else:
|
||
|
|
if cur_frm_idx >= self.LatencyFrmNumAtStartPoint():
|
||
|
|
self.OnSilenceDetected(cur_frm_idx - self.LatencyFrmNumAtStartPoint())
|
||
|
|
elif self.vad_state_machine == VadStateMachine.kVadInStateInSpeechSegment:
|
||
|
|
if (
|
||
|
|
self.continous_silence_frame_count * frm_shift_in_ms
|
||
|
|
>= self.max_end_sil_frame_cnt_thresh
|
||
|
|
):
|
||
|
|
lookback_frame = int(self.max_end_sil_frame_cnt_thresh / frm_shift_in_ms)
|
||
|
|
if self.vad_opts.do_extend:
|
||
|
|
lookback_frame -= int(
|
||
|
|
self.vad_opts.lookahead_time_end_point / frm_shift_in_ms
|
||
|
|
)
|
||
|
|
lookback_frame -= 1
|
||
|
|
lookback_frame = max(0, lookback_frame)
|
||
|
|
self.OnVoiceEnd(cur_frm_idx - lookback_frame, False, False)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
elif (
|
||
|
|
cur_frm_idx - self.confirmed_start_frame + 1
|
||
|
|
> self.vad_opts.max_single_segment_time / frm_shift_in_ms
|
||
|
|
):
|
||
|
|
self.OnVoiceEnd(cur_frm_idx, False, False)
|
||
|
|
self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
elif self.vad_opts.do_extend and not is_final_frame:
|
||
|
|
if self.continous_silence_frame_count <= int(
|
||
|
|
self.vad_opts.lookahead_time_end_point / frm_shift_in_ms
|
||
|
|
):
|
||
|
|
self.OnVoiceDetected(cur_frm_idx)
|
||
|
|
else:
|
||
|
|
self.MaybeOnVoiceEndIfLastFrame(is_final_frame, cur_frm_idx)
|
||
|
|
else:
|
||
|
|
pass
|
||
|
|
|
||
|
|
if (
|
||
|
|
self.vad_state_machine == VadStateMachine.kVadInStateEndPointDetected
|
||
|
|
and self.vad_opts.detect_mode == VadDetectMode.kVadMutipleUtteranceDetectMode.value
|
||
|
|
):
|
||
|
|
self.ResetDetection()
|