forked from platypush/platypush
Implemented PicoVoice speech-to-text integration [closes #130]
This commit is contained in:
Fabio Manganiello
parent
a5c08ed3e4
commit
ce0f3227ec
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@ -243,6 +243,7 @@ autodoc_mock_imports = ['googlesamples.assistant.grpc.audio_helpers',
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'deepspeech',
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'wave',
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'pvporcupine ',
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'pvcheetah',
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]
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sys.path.insert(0, os.path.abspath('../..'))
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@ -1,21 +0,0 @@
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from platypush.backend.stt import SttBackend
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class SttPicovoiceBackend(SttBackend):
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"""
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Backend for the PicoVoice speech-to-text engine plugin. Set this plugin to ``enabled`` if you
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want to run the speech-to-text engine continuously instead of programmatically using
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``start_detection`` and ``stop_detection``.
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Requires:
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- The :class:`platypush.plugins.stt.deepspeech.SttPicovoicePlugin` plugin configured and its dependencies
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installed.
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"""
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def __init__(self, *args, **kwargs):
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super().__init__('stt.picovoice', *args, **kwargs)
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# vim:sw=4:ts=4:et:
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@ -0,0 +1,21 @@
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from platypush.backend.stt import SttBackend
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class SttPicovoiceHotwordBackend(SttBackend):
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"""
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Backend for the PicoVoice hotword detection plugin. Set this plugin to ``enabled`` if you
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want to run the hotword engine continuously instead of programmatically using
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``start_detection`` and ``stop_detection``.
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Requires:
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- The :class:`platypush.plugins.stt.deepspeech.SttPicovoiceHotwordPlugin` plugin configured and its dependencies
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installed.
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"""
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def __init__(self, *args, **kwargs):
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super().__init__('stt.picovoice.hotword', *args, **kwargs)
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# vim:sw=4:ts=4:et:
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@ -0,0 +1,21 @@
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from platypush.backend.stt import SttBackend
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class SttPicovoiceSpeechBackend(SttBackend):
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"""
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Backend for the PicoVoice speech detection plugin. Set this plugin to ``enabled`` if you
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want to run the speech engine continuously instead of programmatically using
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``start_detection`` and ``stop_detection``.
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Requires:
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- The :class:`platypush.plugins.stt.deepspeech.SttPicovoiceSpeechPlugin` plugin configured and its dependencies
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installed.
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"""
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def __init__(self, *args, **kwargs):
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super().__init__('stt.picovoice.speech', *args, **kwargs)
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# vim:sw=4:ts=4:et:
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@ -7,10 +7,10 @@ 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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class SttPicovoiceHotwordPlugin(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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This plugin performs hotword detection using
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`PicoVoice <https://github.com/Picovoice>`_.
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Requires:
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@ -0,0 +1,135 @@
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import inspect
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import os
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import platform
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import struct
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import threading
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from typing import Optional
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from platypush.message.event.stt import SpeechStartedEvent
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from platypush.context import get_bus
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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 SttPicovoiceSpeechPlugin(SttPlugin):
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"""
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This plugin performs speech detection using `PicoVoice <https://github.com/Picovoice>`_.
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Requires:
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* **cheetah** (``pip install git+https://github.com/BlackLight/cheetah``)
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"""
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def __init__(self,
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library_path: Optional[str] = None,
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acoustic_model_path: Optional[str] = None,
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language_model_path: Optional[str] = None,
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license_path: Optional[str] = None,
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end_of_speech_timeout: int = 1,
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*args, **kwargs):
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"""
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:param library_path: Path to the Cheetah binary library for your OS
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(default: ``CHEETAH_INSTALL_DIR/lib/OS/ARCH/libpv_cheetah.EXT``).
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:param acoustic_model_path: Path to the acoustic speech model
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(default: ``CHEETAH_INSTALL_DIR/lib/common/acoustic_model.pv``).
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:param language_model_path: Path to the language model
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(default: ``CHEETAH_INSTALL_DIR/lib/common/language_model.pv``).
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:param license_path: Path to your PicoVoice license
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(default: ``CHEETAH_INSTALL_DIR/resources/license/cheetah_eval_linux_public.lic``).
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:param end_of_speech_timeout: Number of seconds of silence during speech recognition before considering
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a phrase over (default: 1).
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"""
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from pvcheetah import Cheetah
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super().__init__(*args, **kwargs)
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self._basedir = os.path.abspath(os.path.join(inspect.getfile(Cheetah), '..', '..', '..'))
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if not library_path:
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library_path = self._get_library_path()
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if not language_model_path:
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language_model_path = os.path.join(self._basedir, 'lib', 'common', 'language_model.pv')
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if not acoustic_model_path:
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acoustic_model_path = os.path.join(self._basedir, 'lib', 'common', 'acoustic_model.pv')
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if not license_path:
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license_path = os.path.join(self._basedir, 'resources', 'license', 'cheetah_eval_linux_public.lic')
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self._library_path = library_path
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self._language_model_path = language_model_path
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self._acoustic_model_path = acoustic_model_path
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self._license_path = license_path
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self._end_of_speech_timeout = end_of_speech_timeout
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self._stt_engine: Optional[Cheetah] = None
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self._speech_in_progress = threading.Event()
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def _get_library_path(self) -> str:
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path = os.path.join(self._basedir, 'lib', platform.system().lower(), platform.machine())
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return os.path.join(path, [f for f in os.listdir(path) if f.startswith('libpv_cheetah.')][0])
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def convert_frames(self, frames: bytes) -> tuple:
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assert self._stt_engine, 'The speech engine is not running'
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return struct.unpack_from("h" * self._stt_engine.frame_length, frames)
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def on_detection_ended(self) -> None:
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if self._stt_engine:
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self._stt_engine.delete()
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self._stt_engine = None
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def detect_speech(self, frames: tuple) -> str:
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text, is_endpoint = self._stt_engine.process(frames)
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text = text.strip()
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if text:
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if not self._speech_in_progress.is_set():
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self._speech_in_progress.set()
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get_bus().post(SpeechStartedEvent())
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self._current_text += ' ' + text.strip()
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if is_endpoint:
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text = self._stt_engine.flush().strip().strip()
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if text:
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self._current_text += ' ' + text
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self._speech_in_progress.clear()
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if self._current_text:
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self.on_speech_detected(self._current_text)
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self._current_text = ''
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return self._current_text
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def process_text(self, text: str) -> None:
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pass
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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._stt_engine, 'The hotword engine has not yet been initialized'
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super().recording_thread(block_size=self._stt_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 pvcheetah import Cheetah
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self._stt_engine = Cheetah(
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library_path=self._library_path,
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acoustic_model_path=self._acoustic_model_path,
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language_model_path=self._language_model_path,
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license_path=self._license_path,
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endpoint_duration_sec=self._end_of_speech_timeout,
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)
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self.rate = self._stt_engine.sample_rate
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self._speech_in_progress.clear()
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super().start_detection(*args, **kwargs)
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# vim:sw=4:ts=4:et:
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@ -235,5 +235,8 @@ croniter
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# numpy
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# sounddevice
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# Support for PicoVoice speech-to-text engine
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# Support for PicoVoice hotword engine
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# pvporcupine
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# Support for PicoVoice speech-to-text engine
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# pvcheetah
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4
setup.py
4
setup.py
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@ -285,7 +285,9 @@ setup(
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'zwave': ['python-openzwave'],
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# Support for Mozilla DeepSpeech speech-to-text engine
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'deepspeech': ['deepspeech', 'numpy','sounddevice'],
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# Support for PicoVoice hotword detection engine
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'picovoice-hotword': ['pvporcupine'],
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# Support for PicoVoice speech-to-text engine
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'picovoice': ['pvporcupine'],
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'picovoice-speech': ['pvcheetah @ git+https://github.com/BlackLight/cheetah'],
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},
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)
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