def record_and_test(textbox, button, filename="test_files/test.wav"): # Buton on button.configure(state="disabled") textbox.configure(state="normal") textbox.delete("1.0", END) textbox.insert(INSERT, "Recording") textbox.tag_add("recording", "1.0", END) textbox.configure(state="disabled") # Record to test record_to_file(filename) # Feed into ANN testNet = testInit() inputArray = extractFeature(filename) print(len(inputArray)) outStr = feedToNetwork(inputArray, testNet) # Button of textbox.configure(state="normal") textbox.delete("1.0", END) textbox.tag_remove("recording", "1.0") textbox.insert(INSERT, outStr) textbox.tag_add("success", "1.0", END) textbox.configure(state="disabled") button.configure(state="normal")
def record_and_test(textbox, button, filename="test_files/test.wav"): # Disable button and change text button.configure(state="disabled") textbox.configure(state="normal") textbox.delete("1.0", END) textbox.insert(INSERT, "Recording") textbox.tag_add("recording", "1.0", END) textbox.configure(state="disabled") # Record to file record_to_file(filename) # Feed into ANN testNet = testInit() inputArray = extractFeature(filename) print len(inputArray) outStr = feedToNetwork(inputArray,testNet) # Change text and re-enable button textbox.configure(state="normal") textbox.delete("1.0", END) textbox.tag_remove("recording", "1.0") textbox.insert(INSERT, outStr) textbox.tag_add("success", "1.0", END) textbox.configure(state="disabled") button.configure(state="normal")
def record_and_train(textbox, button): # button on button.configure(state="disabled") textbox.configure(state="normal") textbox.delete("1.0", END) textbox.insert(INSERT, "Recording") textbox.tag_add("recording", "1.0", END) textbox.configure(state="disabled") words = ['down', 'eat', 'sleep', 'up'] for i in range(len(words)): # WORD loop for j in range(10): # REPEAT loop # record to train record_to_file("training_sets/" + words[i] + "-" + str(j + 1) + ".wav") print("repeat", words[i]) if (len(words) != i + 1): print("next word", words[i + 1]) else: print("finish") # Button of textbox.configure(state="normal") textbox.delete("1.0", END) textbox.tag_remove("recording", "1.0") textbox.tag_add("success", "1.0", END) textbox.configure(state="disabled") button.configure(state="normal") # MFCC calculation and TRAIN mfcc_apply() print("train start..") TRAIN()
def test_with_recording(): import wave from record import record_to_file, play_sound_file test_audio_file = f"{current_dir}/tmp/api_test.wav" if not os.path.isfile(test_audio_file): record_to_file(test_audio_file, sampling_freq=10000) play_sound_file(test_audio_file) result = send_to_speech_api(test_audio_file) print(result)
def main(): import wave from record import record_to_file, play_sound_file test_audio_file = f"{current_dir}/tmp/api_test.wav" if not os.path.isfile(test_audio_file): record_to_file(test_audio_file, sampling_freq=16000) play_sound_file(test_audio_file) result = transcribe_file(f"{current_dir}/tmp/api_test.wav") print(result)
def record_some_words(): sleep(2) speak("Bitte sprechen Sie nach dem Piepston") beep = Beep() beep.play(1000) record_to_file('demo.wav') speak("Danke! Sie haben folgende Nachricht aufgenommen:") play_from_file('demo.wav') speak("... und noch einmal:") play_from_file('demo.wav')
def test_with_live_recording(duration=1, sampling_rate=10000): """ Test the API by recording a digit using the microphone and then preprocessing it, sending the spectrogram and awaiting the result. """ from time import sleep from make_spectrograms import make_spectrogram_from_wav_file from record import record_to_file, play_sound_file, record, write_to_file test_audio_file = f"{current_dir}/tmp/api_test.wav" test_img_path = f"{current_dir}/tmp/api_test.png" # do a quick countdown before recording. for i in reversed(range(4)): print(f"\rRecording in {i}", end="\r") sleep(1) record_to_file(test_audio_file, recording_length_secs=duration, sampling_freq=sampling_rate) play_sound_file(test_audio_file) result = send_to_speech_api(test_audio_file) print(result)
def record_and_test(textbox, button, filename): button.configure(state="disabled") textbox.configure(state="normal") textbox.delete("1.0", END) textbox.insert(INSERT, "Recording") textbox.tag_add("recording", "1.0", END) textbox.configure(state="disabled") record_to_file(filename) testNet = testInit() inputArray = extractFeature(filename) print len(inputArray) outStr = "Detected : " + str(feedToNetwork(inputArray, testNet) + 1) textbox.configure(state="normal") textbox.delete("1.0", END) textbox.tag_remove("recording", "1.0") textbox.insert(INSERT, outStr) textbox.tag_add("success", "1.0", END) textbox.configure(state="disabled") button.configure(state="normal")
def record_and_test(textbox, button, filename): button.configure(state="disabled") textbox.configure(state="normal") textbox.delete("1.0", END) textbox.insert(INSERT, "Recording") textbox.tag_add("recording", "1.0", END) textbox.configure(state="disabled") record_to_file(filename) testNet = testInit() inputArray = extractFeature(filename) print len(inputArray) outStr = "Detected : " + str(feedToNetwork(inputArray,testNet)+1) textbox.configure(state="normal") textbox.delete("1.0", END) textbox.tag_remove("recording", "1.0") textbox.insert(INSERT, outStr) textbox.tag_add("success", "1.0", END) textbox.configure(state="disabled") button.configure(state="normal")
def recordSoundData(self): record.record_to_file("/tmp/%s.lyric" % self.hash)
import playsound as plsnd import requests as req HOST = "http://192.168.0.103:3000" if __name__ == '__main__': testNet = testInit() num_loop = 0 filename = "test_files/test.wav" while True: # Record to file num_loop += 1 print("please speak a word into the microphone", num_loop) record_to_file(filename) # Feed into ANN inputArray = extractFeature(filename) res = feedToNetwork(inputArray, testNet) if (res == 0): # ban can giup gi? plsnd.playsound("speak_out_files/bancangiupgi.wav") print("Ban can giup gi? ...") record_to_file(filename) inputArray = extractFeature(filename) res = feedToNetwork(inputArray, testNet)
def run_record(status): record_to_file('query.wav') status.audio = True status.stop_recording()
## здесь соберем все воедино import acrcloud_api import vk_api import record # авторизовываемся в вк api = vk_api.authorization(access_token=vk_api.access_token) # получаем путь к файлу от алексы... #но пока стандартный music_file_path = '/Users//Desktop/Git/icon_hack/demo.mp3' # запись в файл wave.mp3 record.record_to_file(music_file_path) # запись с микрофона # обрабатываем его через acrcloud_api responce = acrcloud_api.get_responce(config=acrcloud_api.config, music_file_path=music_file_path, start_seconds=3) title, artist = acrcloud_api.parce_responce(responce) # отправляем шаблонную строку в вк pattern_string = "Это песня " + title + " исполнителя " + artist + "!" # еще хз как выбирать юзера, поэтому отправляю себе #vk_api.send_message(api=api, user_id=62811131, message=pattern_string)
def RecordSpeech(self): print "please speak a word into the microphone" record_to_file(join(dirname(__file__),self.audiofile)) print "done - result written to audio.wav"
import sys import record if __name__ == '__main__': record.record_to_file(sys.stdout)
def exp_evidence(logits): return np.exp(np.clip(logits, -10, 10)) def uncertainty_score(logits_output): evidence = exp_evidence(logits_output) alpha = evidence + 1 u_score = 10 / np.sum(alpha, axis=1, keepdims=True) # K = num_classes = 10 return u_score while True: print("Listening...") record_start = time() record_to_file("sound/input.wav") record_time = time() - record_start work_dir = 'sound' start_time = time() test_x, test_y = data_processing(work_dir) load_time = time() - start_time # # Testing on loaded model start_time = time() output = sess.run(output_tensor, feed_dict={model_input: test_x}) y_pred = predict_label(output) uncertainty_y_list = uncertainty_score(output) test_time = time() - start_time print("Inference time:", infer_time)