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| # -*- coding:utf-8 -*- | |
| # @FileName :e2e_vad.py | |
| # @Time :2023/4/3 17:02 | |
| # @Author :lovemefan | |
| # @Email :[email protected] | |
| import logging | |
| import math | |
| from enum import Enum | |
| from pathlib import Path | |
| from typing import Any, Dict, List, Tuple | |
| import numpy as np | |
| from paraformer.runtime.python.utils.logger import logger | |
| from paraformer.runtime.python.utils.vadOrtInferRuntimeSession import \ | |
| VadOrtInferRuntimeSession | |
| class VadStateMachine(Enum): | |
| kVadInStateStartPointNotDetected = 1 | |
| kVadInStateInSpeechSegment = 2 | |
| kVadInStateEndPointDetected = 3 | |
| class FrameState(Enum): | |
| kFrameStateInvalid = -1 | |
| kFrameStateSpeech = 1 | |
| kFrameStateSil = 0 | |
| # final voice/unvoice state per frame | |
| class AudioChangeState(Enum): | |
| kChangeStateSpeech2Speech = 0 | |
| kChangeStateSpeech2Sil = 1 | |
| kChangeStateSil2Sil = 2 | |
| kChangeStateSil2Speech = 3 | |
| kChangeStateNoBegin = 4 | |
| kChangeStateInvalid = 5 | |
| class VadDetectMode(Enum): | |
| kVadSingleUtteranceDetectMode = 0 | |
| kVadMutipleUtteranceDetectMode = 1 | |
| class VADXOptions: | |
| def __init__( | |
| self, | |
| sample_rate: int = 16000, | |
| detect_mode: int = VadDetectMode.kVadMutipleUtteranceDetectMode.value, | |
| snr_mode: int = 0, | |
| max_end_silence_time: int = 800, | |
| max_start_silence_time: int = 3000, | |
| do_start_point_detection: bool = True, | |
| do_end_point_detection: bool = True, | |
| window_size_ms: int = 200, | |
| sil_to_speech_time_thres: int = 150, | |
| speech_to_sil_time_thres: int = 150, | |
| speech_2_noise_ratio: float = 1.0, | |
| do_extend: int = 1, | |
| lookback_time_start_point: int = 200, | |
| lookahead_time_end_point: int = 100, | |
| max_single_segment_time: int = 60000, | |
| nn_eval_block_size: int = 8, | |
| dcd_block_size: int = 4, | |
| snr_thres: int = -100.0, | |
| noise_frame_num_used_for_snr: int = 100, | |
| decibel_thres: int = -100.0, | |
| speech_noise_thres: float = 0.6, | |
| fe_prior_thres: float = 1e-4, | |
| silence_pdf_num: int = 1, | |
| sil_pdf_ids: List[int] = [0], | |
| speech_noise_thresh_low: float = -0.1, | |
| speech_noise_thresh_high: float = 0.3, | |
| output_frame_probs: bool = False, | |
| frame_in_ms: int = 10, | |
| frame_length_ms: int = 25, | |
| ): | |
| self.sample_rate = sample_rate | |
| self.detect_mode = detect_mode | |
| self.snr_mode = snr_mode | |
| self.max_end_silence_time = max_end_silence_time | |
| self.max_start_silence_time = max_start_silence_time | |
| self.do_start_point_detection = do_start_point_detection | |
| self.do_end_point_detection = do_end_point_detection | |
| self.window_size_ms = window_size_ms | |
| self.sil_to_speech_time_thres = sil_to_speech_time_thres | |
| self.speech_to_sil_time_thres = speech_to_sil_time_thres | |
| self.speech_2_noise_ratio = speech_2_noise_ratio | |
| self.do_extend = do_extend | |
| self.lookback_time_start_point = lookback_time_start_point | |
| self.lookahead_time_end_point = lookahead_time_end_point | |
| self.max_single_segment_time = max_single_segment_time | |
| self.nn_eval_block_size = nn_eval_block_size | |
| self.dcd_block_size = dcd_block_size | |
| self.snr_thres = snr_thres | |
| self.noise_frame_num_used_for_snr = noise_frame_num_used_for_snr | |
| self.decibel_thres = decibel_thres | |
| self.speech_noise_thres = speech_noise_thres | |
| self.fe_prior_thres = fe_prior_thres | |
| self.silence_pdf_num = silence_pdf_num | |
| self.sil_pdf_ids = sil_pdf_ids | |
| self.speech_noise_thresh_low = speech_noise_thresh_low | |
| self.speech_noise_thresh_high = speech_noise_thresh_high | |
| self.output_frame_probs = output_frame_probs | |
| self.frame_in_ms = frame_in_ms | |
| self.frame_length_ms = frame_length_ms | |
| class E2EVadSpeechBufWithDoa(object): | |
| def __init__(self): | |
| self.start_ms = 0 | |
| self.end_ms = 0 | |
| self.buffer = [] | |
| self.contain_seg_start_point = False | |
| self.contain_seg_end_point = False | |
| self.doa = 0 | |
| def reset(self): | |
| self.start_ms = 0 | |
| self.end_ms = 0 | |
| self.buffer = [] | |
| self.contain_seg_start_point = False | |
| self.contain_seg_end_point = False | |
| self.doa = 0 | |
| class E2EVadFrameProb(object): | |
| def __init__(self): | |
| self.noise_prob = 0.0 | |
| self.speech_prob = 0.0 | |
| self.score = 0.0 | |
| self.frame_id = 0 | |
| self.frm_state = 0 | |
| class WindowDetector(object): | |
| 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 | |
| self.sil_to_speech_time = sil_to_speech_time | |
| self.speech_to_sil_time = speech_to_sil_time | |
| self.frame_size_ms = frame_size_ms | |
| self.win_size_frame = int(window_size_ms / frame_size_ms) | |
| self.win_sum = 0 | |
| self.win_state = [0] * self.win_size_frame # εε§εηͺ | |
| self.cur_win_pos = 0 | |
| self.pre_frame_state = FrameState.kFrameStateSil | |
| self.cur_frame_state = FrameState.kFrameStateSil | |
| self.sil_to_speech_frmcnt_thres = int(sil_to_speech_time / frame_size_ms) | |
| self.speech_to_sil_frmcnt_thres = int(speech_to_sil_time / frame_size_ms) | |
| self.voice_last_frame_count = 0 | |
| self.noise_last_frame_count = 0 | |
| self.hydre_frame_count = 0 | |
| def reset(self) -> None: | |
| self.cur_win_pos = 0 | |
| self.win_sum = 0 | |
| self.win_state = [0] * self.win_size_frame | |
| self.pre_frame_state = FrameState.kFrameStateSil | |
| self.cur_frame_state = FrameState.kFrameStateSil | |
| self.voice_last_frame_count = 0 | |
| self.noise_last_frame_count = 0 | |
| self.hydre_frame_count = 0 | |
| def get_win_size(self) -> int: | |
| return int(self.win_size_frame) | |
| def detect_one_frame( | |
| self, frameState: FrameState, frame_count: int | |
| ) -> AudioChangeState: | |
| cur_frame_state = FrameState.kFrameStateSil | |
| if frameState == FrameState.kFrameStateSpeech: | |
| cur_frame_state = 1 | |
| elif frameState == FrameState.kFrameStateSil: | |
| cur_frame_state = 0 | |
| else: | |
| return AudioChangeState.kChangeStateInvalid | |
| self.win_sum -= self.win_state[self.cur_win_pos] | |
| self.win_sum += cur_frame_state | |
| self.win_state[self.cur_win_pos] = cur_frame_state | |
| self.cur_win_pos = (self.cur_win_pos + 1) % self.win_size_frame | |
| if ( | |
| self.pre_frame_state == FrameState.kFrameStateSil | |
| and self.win_sum >= self.sil_to_speech_frmcnt_thres | |
| ): | |
| self.pre_frame_state = FrameState.kFrameStateSpeech | |
| return AudioChangeState.kChangeStateSil2Speech | |
| if ( | |
| self.pre_frame_state == FrameState.kFrameStateSpeech | |
| and self.win_sum <= self.speech_to_sil_frmcnt_thres | |
| ): | |
| self.pre_frame_state = FrameState.kFrameStateSil | |
| return AudioChangeState.kChangeStateSpeech2Sil | |
| if self.pre_frame_state == FrameState.kFrameStateSil: | |
| return AudioChangeState.kChangeStateSil2Sil | |
| if self.pre_frame_state == FrameState.kFrameStateSpeech: | |
| return AudioChangeState.kChangeStateSpeech2Speech | |
| return AudioChangeState.kChangeStateInvalid | |
| def frame_size_ms(self) -> int: | |
| return int(self.frame_size_ms) | |
| class E2EVadModel: | |
| def __init__(self, config, vad_post_args: Dict[str, Any], root_dir: Path): | |
| super(E2EVadModel, self).__init__() | |
| self.vad_opts = VADXOptions(**vad_post_args) | |
| self.windows_detector = WindowDetector( | |
| self.vad_opts.window_size_ms, | |
| self.vad_opts.sil_to_speech_time_thres, | |
| self.vad_opts.speech_to_sil_time_thres, | |
| self.vad_opts.frame_in_ms, | |
| ) | |
| self.model = VadOrtInferRuntimeSession(config, root_dir) | |
| # init variables | |
| self.is_final = False | |
| self.data_buf_start_frame = 0 | |
| self.frm_cnt = 0 | |
| self.latest_confirmed_speech_frame = 0 | |
| self.lastest_confirmed_silence_frame = -1 | |
| self.continous_silence_frame_count = 0 | |
| self.vad_state_machine = VadStateMachine.kVadInStateStartPointNotDetected | |
| self.confirmed_start_frame = -1 | |
| self.confirmed_end_frame = -1 | |
| self.number_end_time_detected = 0 | |
| self.sil_frame = 0 | |
| self.sil_pdf_ids = self.vad_opts.sil_pdf_ids | |
| self.noise_average_decibel = -100.0 | |
| self.pre_end_silence_detected = False | |
| self.next_seg = True | |
| self.output_data_buf = [] | |
| self.output_data_buf_offset = 0 | |
| self.frame_probs = [] | |
| self.max_end_sil_frame_cnt_thresh = ( | |
| self.vad_opts.max_end_silence_time - self.vad_opts.speech_to_sil_time_thres | |
| ) | |
| self.speech_noise_thres = self.vad_opts.speech_noise_thres | |
| self.scores = None | |
| self.max_time_out = False | |
| self.decibel = [] | |
| self.data_buf_size = 0 | |
| self.data_buf_all_size = 0 | |
| self.waveform = None | |
| self.reset_detection() | |
| def all_reset_detection(self): | |
| self.is_final = False | |
| self.data_buf_start_frame = 0 | |
| self.frm_cnt = 0 | |
| self.latest_confirmed_speech_frame = 0 | |
| self.lastest_confirmed_silence_frame = -1 | |
| self.continous_silence_frame_count = 0 | |
| self.vad_state_machine = VadStateMachine.kVadInStateStartPointNotDetected | |
| self.confirmed_start_frame = -1 | |
| self.confirmed_end_frame = -1 | |
| self.number_end_time_detected = 0 | |
| self.sil_frame = 0 | |
| self.sil_pdf_ids = self.vad_opts.sil_pdf_ids | |
| self.noise_average_decibel = -100.0 | |
| self.pre_end_silence_detected = False | |
| self.next_seg = True | |
| self.output_data_buf = [] | |
| self.output_data_buf_offset = 0 | |
| self.frame_probs = [] | |
| self.max_end_sil_frame_cnt_thresh = ( | |
| self.vad_opts.max_end_silence_time - self.vad_opts.speech_to_sil_time_thres | |
| ) | |
| self.speech_noise_thres = self.vad_opts.speech_noise_thres | |
| self.scores = None | |
| self.max_time_out = False | |
| self.decibel = [] | |
| self.data_buf = 0 | |
| self.data_buf_all = 0 | |
| self.waveform = None | |
| self.reset_detection() | |
| def reset_detection(self): | |
| self.continous_silence_frame_count = 0 | |
| self.latest_confirmed_speech_frame = 0 | |
| self.lastest_confirmed_silence_frame = -1 | |
| self.confirmed_start_frame = -1 | |
| self.confirmed_end_frame = -1 | |
| self.vad_state_machine = VadStateMachine.kVadInStateStartPointNotDetected | |
| self.windows_detector.reset() | |
| self.sil_frame = 0 | |
| self.frame_probs = [] | |
| def compute_decibel(self) -> None: | |
| frame_sample_length = int( | |
| self.vad_opts.frame_length_ms * self.vad_opts.sample_rate / 1000 | |
| ) | |
| frame_shift_length = int( | |
| self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000 | |
| ) | |
| if self.data_buf_all_size == 0: | |
| self.data_buf_all_size = len(self.waveform[0]) | |
| self.data_buf_size = self.data_buf_all_size | |
| else: | |
| self.data_buf_all_size += len(self.waveform[0]) | |
| for offset in range( | |
| 0, self.waveform.shape[1] - frame_sample_length + 1, frame_shift_length | |
| ): | |
| self.decibel.append( | |
| 10 | |
| * np.log10( | |
| np.square( | |
| self.waveform[0][offset : offset + frame_sample_length] | |
| ).sum() | |
| + 1e-6 | |
| ) | |
| ) | |
| def compute_scores(self, feats: np.ndarray) -> None: | |
| scores = self.model(feats) | |
| self.vad_opts.nn_eval_block_size = scores[0].shape[1] | |
| self.frm_cnt += scores[0].shape[1] # count total frames | |
| if isinstance(feats, list): | |
| # return B * T * D | |
| feats = feats[0] | |
| assert ( | |
| scores[0].shape[1] == feats.shape[1] | |
| ), "The shape between feats and scores does not match" | |
| if self.scores is None: | |
| self.scores = scores[0] # the first calculation | |
| else: | |
| self.scores = np.concatenate((self.scores, scores[0]), axis=1) | |
| return scores[1:] | |
| def pop_data_buf_till_frame(self, frame_idx: int) -> None: # need check again | |
| while self.data_buf_start_frame < frame_idx: | |
| if self.data_buf_size >= int( | |
| self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000 | |
| ): | |
| self.data_buf_start_frame += 1 | |
| self.data_buf_size = ( | |
| self.data_buf_all_size | |
| - self.data_buf_start_frame | |
| * int(self.vad_opts.frame_in_ms * self.vad_opts.sample_rate / 1000) | |
| ) | |
| def pop_data_to_output_buf( | |
| self, | |
| 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.pop_data_buf_till_frame(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: | |
| logging.error("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: | |
| logging.error("warning\n") | |
| out_pos = len(cur_seg.buffer) # cur_seg.buffη°ε¨ζ²‘εδ»»δ½ζδ½ | |
| 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: | |
| logging.error("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: | |
| logging.error("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 on_silence_detected(self, valid_frame: int): | |
| self.lastest_confirmed_silence_frame = valid_frame | |
| if self.vad_state_machine == VadStateMachine.kVadInStateStartPointNotDetected: | |
| self.pop_data_buf_till_frame(valid_frame) | |
| # silence_detected_callback_ | |
| # pass | |
| def on_voice_detected(self, valid_frame: int) -> None: | |
| self.latest_confirmed_speech_frame = valid_frame | |
| self.pop_data_to_output_buf(valid_frame, 1, False, False, False) | |
| def on_voice_start(self, start_frame: int, fake_result: bool = False) -> None: | |
| if self.vad_opts.do_start_point_detection: | |
| pass | |
| if self.confirmed_start_frame != -1: | |
| logging.error("not reset vad properly\n") | |
| else: | |
| self.confirmed_start_frame = start_frame | |
| if ( | |
| not fake_result | |
| and self.vad_state_machine | |
| == VadStateMachine.kVadInStateStartPointNotDetected | |
| ): | |
| self.pop_data_to_output_buf( | |
| self.confirmed_start_frame, 1, True, False, False | |
| ) | |
| def on_voice_end( | |
| 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.on_voice_detected(t) | |
| if self.vad_opts.do_end_point_detection: | |
| pass | |
| if self.confirmed_end_frame != -1: | |
| logging.error("not reset vad properly\n") | |
| else: | |
| self.confirmed_end_frame = end_frame | |
| if not fake_result: | |
| self.sil_frame = 0 | |
| self.pop_data_to_output_buf( | |
| self.confirmed_end_frame, 1, False, True, is_last_frame | |
| ) | |
| self.number_end_time_detected += 1 | |
| def maybe_on_voice_end_last_frame( | |
| self, is_final_frame: bool, cur_frm_idx: int | |
| ) -> None: | |
| if is_final_frame: | |
| self.on_voice_end(cur_frm_idx, False, True) | |
| self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected | |
| def get_latency(self) -> int: | |
| return int(self.latency_frm_num_at_start_point() * self.vad_opts.frame_in_ms) | |
| def latency_frm_num_at_start_point(self) -> int: | |
| vad_latency = self.windows_detector.get_win_size() | |
| 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 get_frame_state(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.detect_one_frame(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 # εͺζ―ζbatch_size = 1ηζ΅θ― | |
| sil_pdf_scores = [ | |
| self.scores[0][t][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 infer_offline( | |
| self, | |
| feats: np.ndarray, | |
| waveform: np.ndarray, | |
| in_cache: Dict[str, np.ndarray] = dict(), | |
| is_final: bool = False, | |
| ) -> Tuple[List[List[List[int]]], Dict[str, np.ndarray]]: | |
| self.waveform = waveform | |
| self.compute_decibel() | |
| self.compute_scores(feats) | |
| if not is_final: | |
| self.detect_common_frames() | |
| else: | |
| self.detect_last_frames() | |
| segments = [] | |
| for batch_num in range(0, feats.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 ( | |
| 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) | |
| self.output_data_buf_offset += 1 # need update this parameter | |
| if segment_batch: | |
| segments.append(segment_batch) | |
| if is_final: | |
| # reset class variables and clear the dict for the next query | |
| self.all_reset_detection() | |
| return segments, in_cache | |
| def infer_online( | |
| self, | |
| feats: np.ndarray, | |
| waveform: np.ndarray, | |
| in_cache: list = None, | |
| is_final: bool = False, | |
| max_end_sil: int = 800, | |
| ) -> Tuple[List[List[List[int]]], Dict[str, np.ndarray]]: | |
| feats = [feats] | |
| if in_cache is None: | |
| in_cache = [] | |
| 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 | |
| feats.extend(in_cache) | |
| in_cache = self.compute_scores(feats) | |
| self.compute_decibel() | |
| if is_final: | |
| self.detect_last_frames() | |
| else: | |
| self.detect_common_frames() | |
| segments = [] | |
| # only support batch_size = 1 now | |
| for batch_num in range(0, feats[0].shape[0]): | |
| 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: | |
| 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 | |
| segments.append([start_ms, end_ms]) | |
| return segments, in_cache | |
| def get_frames_state( | |
| self, | |
| feats: np.ndarray, | |
| waveform: np.ndarray, | |
| in_cache: list = None, | |
| is_final: bool = False, | |
| max_end_sil: int = 800, | |
| ): | |
| feats = [feats] | |
| states = [] | |
| if in_cache is None: | |
| in_cache = [] | |
| 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 | |
| feats.extend(in_cache) | |
| in_cache = self.compute_scores(feats) | |
| self.compute_decibel() | |
| if self.vad_state_machine == VadStateMachine.kVadInStateEndPointDetected: | |
| return states | |
| for i in range(self.vad_opts.nn_eval_block_size - 1, -1, -1): | |
| frame_state = FrameState.kFrameStateInvalid | |
| frame_state = self.get_frame_state(self.frm_cnt - 1 - i) | |
| states.append(frame_state) | |
| if i == 0 and is_final: | |
| logger.info("last frame detected") | |
| self.detect_one_frame(frame_state, self.frm_cnt - 1, True) | |
| else: | |
| self.detect_one_frame(frame_state, self.frm_cnt - 1 - i, False) | |
| return states | |
| def detect_common_frames(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.get_frame_state(self.frm_cnt - 1 - i) | |
| # print(f"cur frame: {self.frm_cnt - 1 - i}, state is {frame_state}") | |
| self.detect_one_frame(frame_state, self.frm_cnt - 1 - i, False) | |
| return 0 | |
| def detect_last_frames(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.get_frame_state(self.frm_cnt - 1 - i) | |
| if i != 0: | |
| self.detect_one_frame(frame_state, self.frm_cnt - 1 - i, False) | |
| else: | |
| self.detect_one_frame(frame_state, self.frm_cnt - 1, True) | |
| return 0 | |
| def detect_one_frame( | |
| 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) > float(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.detect_one_frame( | |
| tmp_cur_frm_state, cur_frm_idx | |
| ) | |
| frm_shift_in_ms = self.vad_opts.frame_in_ms | |
| if AudioChangeState.kChangeStateSil2Speech == state_change: | |
| self.continous_silence_frame_count = 0 | |
| self.pre_end_silence_detected = False | |
| if ( | |
| self.vad_state_machine | |
| == VadStateMachine.kVadInStateStartPointNotDetected | |
| ): | |
| start_frame = max( | |
| self.data_buf_start_frame, | |
| cur_frm_idx - self.latency_frm_num_at_start_point(), | |
| ) | |
| self.on_voice_start(start_frame) | |
| self.vad_state_machine = VadStateMachine.kVadInStateInSpeechSegment | |
| for t in range(start_frame + 1, cur_frm_idx + 1): | |
| self.on_voice_detected(t) | |
| elif self.vad_state_machine == VadStateMachine.kVadInStateInSpeechSegment: | |
| for t in range(self.latest_confirmed_speech_frame + 1, cur_frm_idx): | |
| self.on_voice_detected(t) | |
| if ( | |
| cur_frm_idx - self.confirmed_start_frame + 1 | |
| > self.vad_opts.max_single_segment_time / frm_shift_in_ms | |
| ): | |
| self.on_voice_end(cur_frm_idx, False, False) | |
| self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected | |
| elif not is_final_frame: | |
| self.on_voice_detected(cur_frm_idx) | |
| else: | |
| self.maybe_on_voice_end_last_frame(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.on_voice_end(cur_frm_idx, False, False) | |
| self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected | |
| elif not is_final_frame: | |
| self.on_voice_detected(cur_frm_idx) | |
| else: | |
| self.maybe_on_voice_end_last_frame(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.on_voice_end(cur_frm_idx, False, False) | |
| self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected | |
| elif not is_final_frame: | |
| self.on_voice_detected(cur_frm_idx) | |
| else: | |
| self.maybe_on_voice_end_last_frame(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.on_silence_detected(t) | |
| self.on_voice_start(0, True) | |
| self.on_voice_end(0, True, False) | |
| self.vad_state_machine = VadStateMachine.kVadInStateEndPointDetected | |
| else: | |
| if cur_frm_idx >= self.latency_frm_num_at_start_point(): | |
| self.on_silence_detected( | |
| cur_frm_idx - self.latency_frm_num_at_start_point() | |
| ) | |
| 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.on_voice_end(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.on_voice_end(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.on_voice_detected(cur_frm_idx) | |
| else: | |
| self.maybe_on_voice_end_last_frame(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.reset_detection() | |