- use native speech detector
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48743574ad
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0bf8134feb
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@ -36,8 +36,8 @@ class AgentConfig:
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# Should the first task run immediately ?
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ForceRun = False
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# Use silence eraser or not (speech detector is used in this case)
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UseSilenceEraser = True
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# Use external speech detector if needed
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UseSpeechDetector = False
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# Path to log file
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LogPath : Path = None
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@ -90,7 +90,7 @@ class AgentConfig:
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if 'speech_detector' in config:
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if config['speech_detector']:
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self.UseSilenceEraser = False
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self.UseSpeechDetector = True
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if 'audio' in config:
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audio = config['audio']
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@ -68,6 +68,9 @@ def detect_degraded_signal(file_test: Path, file_reference: Path) -> SignalBound
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# Seems some problem with recording, return zero boundaries
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return SignalBoundaries()
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if CONFIG.UseSpeechDetector:
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r = bt_signal.find_reference_signal_via_speechdetector(file_test)
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else:
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r = bt_signal.find_reference_signal(file_test)
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if r.offset_start == 0.0 and is_caller:
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@ -78,6 +81,9 @@ def detect_degraded_signal(file_test: Path, file_reference: Path) -> SignalBound
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def detect_reference_signal(file_reference: Path) -> SignalBoundaries:
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# Run silence eraser on reference file as well
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if CONFIG.UseSpeechDetector:
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result = bt_signal.find_reference_signal_via_speechdetector(file_reference)
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else:
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result = bt_signal.find_reference_signal(file_reference)
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return result
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@ -3,33 +3,22 @@
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import sys
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import os
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import pathlib
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from utils_types import SignalBoundaries
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from utils_sevana import speech_detector
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from pydub import silence, AudioSegment
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class SignalBoundaries:
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# Offset from start (in seconds)
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offset_start: float
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# Offset from finish (in seconds)
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offset_finish: float
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def __init__(self, offset_start = 0.0, offset_finish = 0.0) -> None:
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self.offset_start = offset_start
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self.offset_finish = offset_finish
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def __repr__(self) -> str:
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return f'[offset_start: {round(self.offset_start, 3)}, offset_finish : {round(self.offset_finish, 3)}]'
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SILENCE_DELTA = 16
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def find_reference_signal(input_file: pathlib.Path, output_file: pathlib.Path = None, use_end_offset: bool = True) -> SignalBoundaries:
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myaudio = AudioSegment.from_wav(str(input_file))
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dBFS = myaudio.dBFS
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# Find silence intervals
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intervals = silence.detect_nonsilent(myaudio, min_silence_len=1000, silence_thresh=dBFS-17, seek_step=50)
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intervals = silence.detect_nonsilent(myaudio, min_silence_len=1000, silence_thresh=dBFS-SILENCE_DELTA, seek_step=50)
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# Translate to seconds
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intervals = [((start/1000),(stop/1000)) for start,stop in intervals] #in sec
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intervals = [((start/1000),(stop/1000)) for start,stop in intervals] # in sec
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# print(intervals)
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@ -48,6 +37,12 @@ def find_reference_signal(input_file: pathlib.Path, output_file: pathlib.Path =
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return SignalBoundaries()
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def find_reference_signal_via_speechdetector(input_file: pathlib.Path) -> SignalBoundaries:
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bounds = speech_detector(str(input_file))
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r = SignalBoundaries(bounds[0], bounds[1])
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return bounds
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if __name__ == '__main__':
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if len(sys.argv) < 2:
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print(f'Please specify input filename.')
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@ -6,12 +6,25 @@ import utils
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import json
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from crontab import CronTab
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# Exit codes
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EXIT_OK = 0
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EXIT_ERROR = 1
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class SignalBoundaries:
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# Offset from start (in seconds)
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offset_start: float
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# Offset from finish (in seconds)
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offset_finish: float
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def __init__(self, offset_start = 0.0, offset_finish = 0.0) -> None:
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self.offset_start = offset_start
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self.offset_finish = offset_finish
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def __repr__(self) -> str:
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return f'[offset_start: {round(self.offset_start, 3)}, offset_finish : {round(self.offset_finish, 3)}]'
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class Phone:
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identifier: int = 0
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name: str = ""
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