Removed PyAudio from the project

README.md

@@ -23,7 +23,7 @@ You will need the following whether you plan to use the toolbox only or to retra
 
 **Python 3.7**. Python 3.6 might work too, but I wouldn't go lower because I make extensive use of pathlib.
 
-Run `pip -r requirements.txt` to install the necessary packages. Additionally you will need [PyTorch](https://pytorch.org/get-started/locally/), PyQt4 (Linux: package `python-qt4`, [Windows](https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyqt4)) and [PyAudio](https://people.csail.mit.edu/hubert/pyaudio/).
+Run `pip -r requirements.txt` to install the necessary packages. Additionally you will need [PyTorch](https://pytorch.org/get-started/locally/) and PyQt4 (Linux: package `python-qt4`, [Windows](https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyqt4)).
 
 A GPU is *highly* recommended (CPU-only is currently not implemented), but you don't necessarily need a high tier GPU if you only want to use the toolbox.
 

synthesizer/synthesize.py

@@ -2,40 +2,11 @@
 from synthesizer.hparams import hparams_debug_string
 from synthesizer.infolog import log
 import tensorflow as tf
-from time import sleep
 from tqdm import tqdm
 import time
 import os
 
 
-def generate_fast(model, text):
-    model.synthesize(text, None, None, None, None)
-
-def run_live(args, checkpoint_path, hparams):
-    #Log to Terminal without keeping any records in files
-    log(hparams_debug_string())
-    synth = Synthesizer()
-    synth.load(checkpoint_path, hparams)
-
-    #Generate fast greeting message
-    greetings = "Hello, Welcome to the Live testing tool. Please type a message and I will try " \
-                "to read it!"
-    log(greetings)
-    generate_fast(synth, greetings)
-
-    #Interaction loop
-    while True:
-        try:
-            text = input()
-            generate_fast(synth, text)
-
-        except KeyboardInterrupt:
-            leave = "Thank you for testing our features. see you soon."
-            log(leave)
-            generate_fast(synth, leave)
-            sleep(2)
-            break
-
 def run_eval(args, checkpoint_path, output_dir, hparams, sentences):
     eval_dir = os.path.join(output_dir, "eval")
     log_dir = os.path.join(output_dir, "logs-eval")

synthesizer/synthesizer.py

@@ -5,7 +5,6 @@
 from synthesizer.utils import plot
 import tensorflow as tf
 import numpy as np
-import pyaudio
 import wave
 import os
 
@@ -181,27 +180,7 @@ def synthesize(self, texts, basenames, out_dir, log_dir, mel_filenames, embed_fi
             assert len(mels) == len(linears) == len(texts)
 
         if basenames is None:
-            #Generate wav and read it
-            wav = audio.inv_mel_spectrogram(mels.T, hparams)
-            audio.save_wav(wav, "temp.wav", sr=hparams.sample_rate) #Find a better way
-
-            chunk = 512
-            f = wave.open("temp.wav", "rb")
-            p = pyaudio.PyAudio()
-            stream = p.open(format=p.get_format_from_width(f.getsampwidth()),
-                            channels=f.getnchannels(),
-                            rate=f.getframerate(),
-                            output=True)
-            data = f.readframes(chunk)
-            while data:
-                stream.write(data)
-                data=f.readframes(chunk)
-
-            stream.stop_stream()
-            stream.close()
-
-            p.terminate()
-            return
+            raise NotImplemented()
 
         saved_mels_paths = []
         for i, mel in enumerate(mels):