Updated archtecture, fixed dependencies

_stt.py

@@ -1,60 +0,0 @@
-import torch
-import sounddevice as sd
-import speech_recognition as sr
-import time
-import numpy
-from glob import glob
-
-device = torch.device('cpu')
-model, decoder, utils = torch.hub.load(repo_or_dir='snakers4/silero-models',
-                                       model='silero_stt',
-                                       language='en', # en, ru
-                                       device=device)
-(read_batch, split_into_batches,
- read_audio, prepare_model_input) = utils
-
-
-def callback(_r, audio):
-    try:
-        # CONVERT raw wav data to NumPy array
-        # wav_raw = audio.get_wav_data()
-        # data_s16 = numpy.frombuffer(wav_raw, dtype=numpy.int16, count=len(wav_raw) // 2, offset=0)
-        # np_audio = data_s16 * 0.5 ** 15
-
-        # Play it via sounddevice
-        #sd.play(np_audio, m.SAMPLE_RATE)
-        #time.sleep(len(np_audio) / m.SAMPLE_RATE)
-        #sd.stop()
-
-        print("Распознание ...")
-
-        # TODO: fix crutch, pass audio data directly as a model input of Silero STT
-        with open('speech.wav', 'wb') as f:
-            f.write(audio.get_wav_data())
-
-        test_files = glob('speech.wav')
-        batches = split_into_batches(test_files, batch_size=10)
-        input = prepare_model_input(read_batch(batches[0]),
-                                    device=device)
-
-        output = model(input)
-        for example in output:
-            print(decoder(example.cpu()))
-
-        # voice = recognizer.recognize_google(audio, language="ru-RU").lower()
-        # print("[log] Распознано: " + voice)
-
-    except sr.UnknownValueError:
-        print("[log] Голос не распознан!")
-
-
-# запуск
-r = sr.Recognizer()
-r.pause_threshold = 0.5
-m = sr.Microphone(device_index=1)
-
-with m as source:
-    r.adjust_for_ambient_noise(source)
-
-stop_listening = r.listen_in_background(m, callback)
-while True: time.sleep(0.1)