import pyarrow as pa import whisper from pynput import keyboard from pynput.keyboard import Key, Events from dora import Node import torch import numpy as np import pyarrow as pa import sounddevice as sd import gc # garbage collect library model = whisper.load_model("base") SAMPLE_RATE = 16000 MAX_DURATION = 30 policy_init = True node = Node() for dora_event in node: if dora_event["type"] == "INPUT": ## Check for keyboard event with keyboard.Events() as events: event = events.get(1.0) if ( event is not None and event.key == Key.alt_r and isinstance(event, Events.Press) ): ## Microphone audio_data = sd.rec( int(SAMPLE_RATE * MAX_DURATION), samplerate=SAMPLE_RATE, channels=1, dtype=np.int16, blocking=False, ) elif ( event is not None and event.key == Key.alt_r and isinstance(event, Events.Release) ): sd.stop() audio = audio_data.ravel().astype(np.float32) / 32768.0 ## Speech to text audio = whisper.pad_or_trim(audio) result = model.transcribe(audio, language="en") node.send_output( "text", pa.array([result["text"]]), dora_event["metadata"] ) # send_output("led", pa.array([0, 0, 255])) gc.collect() torch.cuda.empty_cache()