mirror of
https://github.com/wassname/BitLit_test1.git
synced 2026-06-27 16:43:35 +08:00
use speechrecognition look and calibrate mic
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wassname
@@ -1,56 +0,0 @@
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#### RUNNING THE MODEL
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# cd documents/pmlg/wake/decoder
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# python demo.py resources/HiBitLit.pmdl
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from __future__ import print_function
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import os
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import sys
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import snowboydecoder
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from snowboydecoder import play_ding, play_dong
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import signal
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import time
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import numpy as np
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import BitLit_main
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t0 = time.time() ## Time counter
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interrupted = False
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def signal_handler(signal, frame):
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global interrupted
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interrupted = True
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def interrupt_callback():
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global interrupted
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return interrupted
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if len(sys.argv) == 1:
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print("Error: need to specify model name")
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print("Usage: python demo.py your.model")
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sys.exit(-1)
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model = sys.argv[1]
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# capture SIGINT signal, e.g., Ctrl+C
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signal.signal(signal.SIGINT, signal_handler)
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play_ding()
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detector = snowboydecoder.HotwordDetector(model, sensitivity=0.5)
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print("Listening... Press Ctrl+C to exit")
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detector.start(
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detected_callback=BitLit_main.generate_poem,
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interrupt_check=interrupt_callback,
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sleep_time=0.03,
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)
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detector.terminate()
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t1 = time.time()
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total = t1 - t0
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print(("Time spent is about:", np.round(total), "seconds"))
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+59
-50
@@ -32,6 +32,8 @@ for index, name in enumerate(sr.Microphone.list_microphone_names()):
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from poem_generator import poem
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snowboy_configuration = ('./snowboy', os.listdir('hotwords'))
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# Load credentials
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try:
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GOOGLE_CLOUD_SPEECH_CREDENTIALS = open("secrets/google_cloud_credentials.json").read()
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@@ -45,7 +47,7 @@ def play_mp3(mp3_file):
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source = pyglet.media.load(filename=mp3_file, streaming=False)
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source.play()
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print(mp3_file, source.duration)
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time.sleep(source.duration + 4) # must be a better way to wait untill the media has played
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time.sleep(source.duration + 2) # must be a better way to wait untill the media has played
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print(mp3_file, source.duration)
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def cache_gtts(text, lang="en-nz", cache_file=None):
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@@ -80,6 +82,10 @@ def cache_gtts(text, lang="en-nz", cache_file=None):
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tts.save(cache_file)
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return cache_file
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def speak(text):
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mp3_file = cache_gtts(text)
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play_mp3(mp3_file)
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def generate_poem():
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@@ -89,67 +95,70 @@ def generate_poem():
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t0 = time.time()
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r = sr.Recognizer()
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with sr.Microphone() as source:
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# print(r.energy_threshold)
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# r.adjust_for_ambient_noise(source)
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# print('energy_threshold', r.energy_threshold)
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r.energy_threshold=50
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print('mic', source)
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outfile1 = cache_gtts(text="Hi! My Name is BIT-LIT. PLEASE SPEAK SOME IDEAS FOR A POEM AFTER THE BEEP.")
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play_mp3(outfile1)
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speak('please be quiet while I calibrate the microphones. I will ding when I am finished')
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time.sleep(5)
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r.pause_threshold = 5
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r.adjust_for_ambient_noise(source)
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print('calibrate mic energy_threshold to', r.energy_threshold)
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speak('Thanks. When you want to talk to me say "Hi BitLit"')
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play_ding()
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print('speak now', time.time())
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audio = r.listen(source)
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logger.debug('done recording %s', time.time())
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logger.info('recorded %s s', len(audio.frame_data)/audio.sample_rate)
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while True:
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print('waiting for hotword "Hi BitLit" or Alexa or SnowBoy')
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audio_null = r.listen(source, snowboy_configuration=snowboy_configuration)
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play_dong()
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play_dong()
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outfile2 = cache_gtts(text="BEEP. THANK YOU! GIVE ME A MINUTE TO GENERATE AND READ YOUR POEM")
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play_mp3(outfile2)
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speak(text="Hi! My Name is BIT-LIT. PLEASE SPEAK SOME IDEAS FOR A POEM AFTER THE DING.")
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play_ding()
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t1 = time.time()
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logger.debug('listen took %s', t1 - t0)
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print('speak now', time.time())
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try:
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audio = r.listen(source, timeout=30, phrase_time_limit=30)
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except sr.WaitTimeoutError as e:
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print('WaitTimeoutError', e)
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continue
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logger.debug('done recording %s', time.time())
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logger.info('recorded %s s', len(audio.frame_data)/audio.sample_rate)
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try:
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logger.debug("using google speech to text...")
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USER_INPUT = r.recognize_google_cloud(audio, credentials_json=GOOGLE_CLOUD_SPEECH_CREDENTIALS)
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logger.info("Google thinks you said: " + USER_INPUT)
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except sr.UnknownValueError as e:
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logger.error("Could not understand audio. {}".format(e))
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return
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except sr.RequestError as e:
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logger.error("Could not request results; {0}".format(e))
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return
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play_dong()
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speak(text="BEEP. THANK YOU! GIVE ME A MINUTE TO GENERATE AND READ YOUR POEM")
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t1b = time.time()
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logger.debug('transcribe took %s', t1b - t1)
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t1 = time.time()
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logger.debug('listen took %s', t1 - t0)
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return
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try:
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logger.debug("using google speech to text...")
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USER_INPUT = r.recognize_google_cloud(audio, credentials_json=GOOGLE_CLOUD_SPEECH_CREDENTIALS)
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logger.info("Google thinks you said: " + USER_INPUT)
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except sr.UnknownValueError as e:
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logger.error("Could not understand audio. {}".format(e))
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return
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except sr.RequestError as e:
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logger.error("Could not request results; {0}".format(e))
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return
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# Generate poem from user seed
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text_generated = poem(USER_INPUT)
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t2 = time.time()
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logger.info("ML POEM is: %s", text_generated)
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logger.debug('poem and rhyme generation took %s', t2 - t1)
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t1b = time.time()
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logger.debug('transcribe took %s', t1b - t1)
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# TEXT CONVERSION IN AUDIO
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# FEED POEM TO TRANSCRIBER
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tts = gTTS(text=text_generated)
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ts = datetime.datetime.utcnow().strftime('%Y%m%d_%H-%M-%S')
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poem_mp3 = "outputs/BitLit_{}.mp3".format(ts)
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tts.save(poem_mp3)
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play_mp3(poem_mp3)
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# Generate poem from user seed
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text_generated = poem(USER_INPUT)
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t2 = time.time()
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logger.info("ML POEM is: %s", text_generated)
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logger.debug('poem and rhyme generation took %s', t2 - t1)
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outfile = cache_gtts(text="THANK YOU! BEEP.")
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play_mp3(outfile)
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# FEED POEM TO TRANSCRIBER
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tts = gTTS(text=text_generated)
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poem_mp3 = "outputs/BitLit_poem.mp3"
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tts.save(poem_mp3)
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play_mp3(poem_mp3)
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######
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t3 = time.time()
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logger.debug('Poem to speech took %s', t3 - t2)
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logger.debug("Total time spent is about: %s seconds", np.round(t3 - t0))
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speak(text="THANK YOU! BEEP.")
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######
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t3 = time.time()
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logger.debug('Poem to speech took %s', t3 - t2)
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logger.debug("Total time spent is about: %s seconds", np.round(t3 - t0))
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if __name__ == "__main__":
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+1
-1
@@ -145,7 +145,7 @@ def poem(USER_INPUT):
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input_eval = tf.expand_dims([predicted_id], 0)
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rhymes += [idx2word_rhymes[predicted_id]]
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logger.info("rhymes:", rhymes)
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logger.info("rhymes: %s", rhymes)
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####################
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# POEM GENERATION #
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