104 lines
3.8 KiB
Python
104 lines
3.8 KiB
Python
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import os
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import struct
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from typing import Optional, List
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from platypush.message.response.stt import SpeechDetectedResponse
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from platypush.plugins import action
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from platypush.plugins.stt import SttPlugin
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class SttPicovoicePlugin(SttPlugin):
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"""
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This plugin performs speech-to-text and speech detection using the
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`PicoVoice <https://github.com/Picovoice>`_ speech-to-text integrations.
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Requires:
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* **pvporcupine** (``pip install pvporcupine``) for hotword detection.
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"""
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def __init__(self,
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library_path: Optional[str] = None,
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model_file_path: Optional[str] = None,
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keyword_file_paths: Optional[List[str]] = None,
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sensitivity: float = 0.5,
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sensitivities: Optional[List[float]] = None,
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*args, **kwargs):
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from pvporcupine import Porcupine
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from pvporcupine.resources.util.python.util import LIBRARY_PATH, MODEL_FILE_PATH, KEYWORD_FILE_PATHS
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super().__init__(*args, **kwargs)
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self.hotwords = list(self.hotwords)
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self._hotword_engine: Optional[Porcupine] = None
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self._library_path = os.path.abspath(os.path.expanduser(library_path or LIBRARY_PATH))
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self._model_file_path = os.path.abspath(os.path.expanduser(model_file_path or MODEL_FILE_PATH))
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if not keyword_file_paths:
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hotwords = KEYWORD_FILE_PATHS
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assert all(hotword in hotwords for hotword in self.hotwords), \
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'Not all the hotwords could be found. Available hotwords: {}'.format(list(hotwords.keys()))
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self._keyword_file_paths = [os.path.abspath(os.path.expanduser(hotwords[hotword]))
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for hotword in self.hotwords]
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else:
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self._keyword_file_paths = [
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os.path.abspath(os.path.expanduser(p))
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for p in keyword_file_paths
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]
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self._sensitivities = []
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if sensitivities:
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assert len(self._keyword_file_paths) == len(sensitivities), \
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'Please specify as many sensitivities as the number of configured hotwords'
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self._sensitivities = sensitivities
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else:
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self._sensitivities = [sensitivity] * len(self._keyword_file_paths)
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def convert_frames(self, frames: bytes) -> tuple:
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assert self._hotword_engine, 'The hotword engine is not running'
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return struct.unpack_from("h" * self._hotword_engine.frame_length, frames)
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def on_detection_ended(self) -> None:
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if self._hotword_engine:
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self._hotword_engine.delete()
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self._hotword_engine = None
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def detect_speech(self, frames: tuple) -> str:
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index = self._hotword_engine.process(frames)
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if index < 0:
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return ''
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if index is True:
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index = 0
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return self.hotwords[index]
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@action
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def detect(self, audio_file: str) -> SpeechDetectedResponse:
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"""
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Perform speech-to-text analysis on an audio file.
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:param audio_file: Path to the audio file.
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"""
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pass
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def recording_thread(self, input_device: Optional[str] = None, *args, **kwargs) -> None:
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assert self._hotword_engine, 'The hotword engine has not yet been initialized'
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super().recording_thread(block_size=self._hotword_engine.frame_length, input_device=input_device)
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@action
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def start_detection(self, *args, **kwargs) -> None:
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from pvporcupine import Porcupine
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self._hotword_engine = Porcupine(
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library_path=self._library_path,
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model_file_path=self._model_file_path,
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keyword_file_paths=self._keyword_file_paths,
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sensitivities=self._sensitivities)
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self.rate = self._hotword_engine.sample_rate
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super().start_detection(*args, **kwargs)
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# vim:sw=4:ts=4:et:
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