stt.picovoice.hotword

class platypush.plugins.stt.picovoice.hotword.SttPicovoiceHotwordPlugin(library_path: Optional[str] = None, model_file_path: Optional[str] = None, keyword_file_paths: Optional[List[str]] = None, sensitivity: float = 0.5, sensitivities: Optional[List[float]] = None, *args, **kwargs)[source]

This plugin performs hotword detection using PicoVoice.

Requires:

  • pvporcupine (pip install pvporcupine) for hotword detection.

__init__(library_path: Optional[str] = None, model_file_path: Optional[str] = None, keyword_file_paths: Optional[List[str]] = None, sensitivity: float = 0.5, sensitivities: Optional[List[float]] = None, *args, **kwargs)[source]
Parameters
  • input_device – PortAudio device index or name that will be used for recording speech (default: default system audio input device).

  • hotword – When this word is detected, the plugin will trigger a platypush.message.event.stt.HotwordDetectedEvent instead of a platypush.message.event.stt.SpeechDetectedEvent event. You can use these events for hooking other assistants.

  • hotwords – Use a list of hotwords instead of a single one.

  • conversation_timeout – If hotword or hotwords are set and conversation_timeout is set, the next speech detected event will trigger a platypush.message.event.stt.ConversationDetectedEvent instead of a platypush.message.event.stt.SpeechDetectedEvent event. You can hook custom hooks here to run any logic depending on the detected speech - it can emulate a kind of “OK, Google. Turn on the lights” interaction without using an external assistant (default: 10 seconds).

  • block_duration – Duration of the acquired audio blocks (default: 1 second).

convert_frames(frames: bytes) tuple[source]

Conversion method for raw audio frames. It just returns the input frames as bytes. Override it if required by your logic.

Parameters

frames – Input audio frames, as bytes.

Returns

The audio frames as passed on the input. Override if required.

detect(audio_file: str) platypush.message.response.stt.SpeechDetectedResponse[source]

Perform speech-to-text analysis on an audio file.

Parameters

audio_file – Path to the audio file.

detect_speech(frames: tuple) str[source]

Method called within the detection_thread when new audio frames have been captured. Must be implemented by the derived classes.

Parameters

frames – Audio frames, as returned by convert_frames.

Returns

Detected text, as a string. Returns an empty string if no text has been detected.

on_detection_ended() None[source]

Method called when the detection_thread stops. Clean up your context variables and models here.

recording_thread(input_device: Optional[str] = None, *args, **kwargs) None[source]

Recording thread. It reads raw frames from the audio device and dispatches them to detection_thread.

Parameters
  • block_duration – Audio blocks duration. Specify either block_duration or block_size.

  • block_size – Size of the audio blocks. Specify either block_duration or block_size.

  • input_device – Input device

start_detection(*args, **kwargs) None[source]

Start the speech detection engine.

Parameters
  • input_device – Audio input device name/index override

  • seconds – If set, then the detection engine will stop after this many seconds, otherwise it’ll start running until stop_detection is called or application stop.

  • block_durationblock_duration override.