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#!/usr/bin/env python3
import copy
import fileinput
import os
import osc_ctrl
# python3 -m pip install pyaudio
import pyaudio
import threading
import time
import wave
# python3 -m pip install git+https://github.com/openai/whisper.git
# python3 -m pip install torch -f https://download.pytorch.org/whl/torch_stable.html
import whisper
class AudioState:
CHUNK = 1024
FORMAT = pyaudio.paInt16
CHANNELS = 1
# This matches the framerate expected by whisper.
RATE = 16000
# The maximum length that recordAudio() will put into frames before it
# starts dropping from the start.
MAX_LENGTH_S = 90
# The minimum length that recordAudio() will wait for before saving audio.
MIN_LENGTH_S = 3
# PyAudio object
p = None
# PyAudio stream object
stream = None
frames = []
frames_lock = threading.Lock()
text = ""
text_lock = threading.Lock()
record_audio = True
transcribe_audio = True
send_audio = True
def getMicStream():
audio_state = AudioState()
audio_state.p = pyaudio.PyAudio()
info = audio_state.p.get_host_api_info_by_index(0)
numdevices = info.get('deviceCount')
print("Finding index mic...")
got_match = False
device_index = -1
mic_str = "Focusrite"
index_str = "Digital Audio Interface"
target_str = mic_str
while got_match == False:
for i in range(0, numdevices):
if (audio_state.p.get_device_info_by_host_api_device_index(0, i).get('maxInputChannels')) > 0:
device_name = audio_state.p.get_device_info_by_host_api_device_index(0, i).get('name')
print("Input Device id ", i, " - ", device_name)
if target_str in device_name:
print("Got match: {}".format(device_name))
device_index = i
got_match = True
break
if got_match == False:
print("No match, sleeping")
time.sleep(3)
audio_state.stream = audio_state.p.open(format=audio_state.FORMAT,
channels=audio_state.CHANNELS, rate=audio_state.RATE,
input=True, frames_per_buffer=audio_state.CHUNK,
input_device_index=device_index)
return audio_state
# Continuously records audio as long as audio_state.record_audio is set.
def recordAudio(audio_state):
print("Recording audio")
while audio_state.record_audio:
data = audio_state.stream.read(audio_state.CHUNK)
audio_state.frames_lock.acquire()
audio_state.frames.append(data)
max_frames = int(audio_state.RATE * audio_state.MAX_LENGTH_S / audio_state.CHUNK)
if len(audio_state.frames) > max_frames:
audio_state.frames = audio_state.frames[-1 * max_frames :]
audio_state.frames_lock.release()
print("Done recording")
# Saves audio. recordAudio() may continue running while this takes place.
def saveAudio(audio_state, filename):
min_frames = int(audio_state.RATE * audio_state.MIN_LENGTH_S / audio_state.CHUNK)
if len(audio_state.frames) < min_frames:
return
wf = wave.open(filename, 'wb')
wf.setnchannels(audio_state.CHANNELS)
wf.setsampwidth(audio_state.p.get_sample_size(audio_state.FORMAT))
wf.setframerate(audio_state.RATE)
audio_state.frames_lock.acquire()
frames = copy.deepcopy(audio_state.frames)
audio_state.frames_lock.release()
wf.writeframes(b''.join(frames))
wf.close()
def resetAudio(audio_state):
audio_state.frames_lock.acquire()
audio_state.frames = []
audio_state.frames_lock.release()
# Transcribe the audio recorded in a file.
def transcribe(model, filename):
result = whisper.transcribe(model=model, audio=filename, language="en")
return result["text"]
def transcribeAudio(audio_state, model):
while audio_state.transcribe_audio == True:
saveAudio(audio_state, "audio.wav")
if not os.path.isfile("audio.wav"):
time.sleep(0.1)
continue
print("Beginning transcription")
text = transcribe(model, "audio.wav")
audio_state.text_lock.acquire()
audio_state.text = text
audio_state.text_lock.release()
print("Transcription: {}".format(audio_state.text))
# Pace this out
time.sleep(0.2)
def sendAudio(audio_state):
tx_state = osc_ctrl.OscTxState()
while audio_state.send_audio == True:
audio_state.text_lock.acquire()
text = copy.deepcopy(audio_state.text)
audio_state.text_lock.release()
osc_ctrl.sendMessageLazy(text, tx_state)
# Pace this out
time.sleep(0.05)
if __name__ == "__main__":
if os.path.isfile("audio.wav"):
os.remove("audio.wav")
audio_state = getMicStream()
record_audio_thd = threading.Thread(target = recordAudio, args = [audio_state])
record_audio_thd.daemon = True
record_audio_thd.start()
print("Safe to start talking")
model = whisper.load_model("base")
transcribe_audio_thd = threading.Thread(target = transcribeAudio, args = [audio_state, model])
transcribe_audio_thd.daemon = True
transcribe_audio_thd.start()
#send_audio_thd = threading.Thread(target = sendAudio, args = [audio_state])
#send_audio_thd.daemon = True
#send_audio_thd.start()
print("Press enter to start a new message")
for line in fileinput.input():
resetAudio(audio_state)
if "exit" in line or "quit" in line:
break
print("Joining threads")
audio_state.record_audio = False
audio_state.transcribe_audio = False
record_audio_thd.join()
transcribe_audio_thd.join()
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