implemented tts sementation generation code

speech_tts_queue.py

@@ -3,61 +3,214 @@ from AppKit import *
 from Foundation import NSURL
 from PyObjCTools import AppHelper
 from time import time
+import os
+import sys
+import random
+import json
+import csv
+import subprocess
+from tqdm import tqdm
+
+from speech_samplegen import SynthVariant, format_filename
+from speech_tools import create_dir
 
 apple_phonemes = [
     '%', '@', 'AE', 'EY', 'AO', 'AX', 'IY', 'EH', 'IH', 'AY', 'IX', 'AA', 'UW',
     'UH', 'UX', 'OW', 'AW', 'OY', 'b', 'C', 'd', 'D', 'f', 'g', 'h', 'J', 'k',
     'l', 'm', 'n', 'N', 'p', 'r', 's', 'S', 't', 'T', 'v', 'w', 'y', 'z', 'Z'
 ]
-len(apple_phonemes)
 
-speech_phoneme_data = []
+OUTPUT_NAME = 'test'
+
+dest_dir = os.path.abspath('.') + '/outputs/' + OUTPUT_NAME + '/'
+csv_dest_file = os.path.abspath('.') + '/outputs/' + OUTPUT_NAME + '.csv'
+create_dir(dest_dir)
+
+
+def cli_gen_audio(speech_cmd, out_path):
+    subprocess.call(
+        ['say', '-o', out_path, "'" + speech_cmd + "'"])
+
 
 class SpeechDelegate (NSObject):
     def speechSynthesizer_willSpeakWord_ofString_(self, sender, word, text):
         '''Called automatically when the application has launched'''
-        print("Speaking word {} in sentence {}".format(word,text))
+        # print("Speaking word {} in sentence {}".format(word,text))
+        self.wordWillSpeak()
 
     def speechSynthesizer_willSpeakPhoneme_(self, sender, phoneme):
         phon_ch = apple_phonemes[phoneme]
-        # print('first',speech_phoneme_data)
+        self.phonemeWillSpeak(phon_ch)
-        # prev_time = speech_phoneme_data[-1][1]
-        # print('prev_time',prev_time)
-        speech_phoneme_data.append((phon_ch,time()))
-        print("phoneme boundary for {} time {}".format(phon_ch,time()))
-        # NSApp().terminate_(self)
 
     def speechSynthesizer_didFinishSpeaking_(self, synth, didFinishSpeaking):
-        speech_phoneme_data.append(('%',time()))
+        if didFinishSpeaking:
-        print("finished speaking time {}".format(time()))
+            self.completeCB()
-        diff_time = []
+
-        for i in range(len(speech_phoneme_data)-1):
+    def setC_W_Ph_(self, completed, word, phoneme):
-            dur = speech_phoneme_data[i+1][1] - speech_phoneme_data[i][1]
+        self.completeCB = completed
-            diff_time.append((speech_phoneme_data[i][0],dur))
+        self.wordWillSpeak = word
-        print(diff_time)
+        self.phonemeWillSpeak = phoneme
 
 # del SpeechDelegate
+
+
 class Delegate (NSObject):
     def applicationDidFinishLaunching_(self, aNotification):
         '''Called automatically when the application has launched'''
-        print("Window, World!")
+        print("App Launched!")
+        generate_audio()
 
-    def windowWillClose_(self, aNotification):
+
-        '''Called automatically when the window is closed'''
+class PhonemeTiming(object):
-        print("Window has been closed")
+    """docstring for PhonemeTiming."""
-        # Terminate the application
+
-        NSApp().terminate_(self)
+    def __init__(self, phon, start):
+        super(PhonemeTiming, self).__init__()
+        self.phoneme = phon
+        self.start = start
+        self.fraction = 0
+        self.duration = None
+        self.end = None
+
+    def is_audible(self):
+        return self.phoneme not in ['%', '~']
+
+    def tune(self):
+        if self.is_audible():
+            dur_ms = int(self.duration * 1000)
+            return '{} {{D {}}}'.format(self.phoneme, dur_ms)
+        else:
+            return '~'
+
+    def __repr__(self):
+        return '[{}]({:0.4f})'.format(self.phoneme, self.fraction)
+
+    @staticmethod
+    def to_tune(phone_ts):
+        tune_list = ['[[inpt TUNE]]']
+        for ph in phone_ts:
+            tune_list.append(ph.tune())
+        tune_list.append('[[inpt TEXT]]')
+        return '\n'.join(tune_list)
+
+
+class SegData(object):
+    """docstring for SegData."""
+
+    def __init__(self, text, filename):
+        super(SegData, self).__init__()
+        self.text = text
+        self.tune = ''
+        self.filename = filename
+        self.segments = []
+
+    def csv_rows(self):
+        result = []
+        s_tim = self.segments[0].start
+        for i in range(len(self.segments) - 1):
+            cs = self.segments[i]
+            # if cs.is_audible():
+            ns = self.segments[i + 1]
+            row = [self.text, self.filename, cs.phoneme, ns.phoneme,
+                   (cs.start - s_tim) * 1000, (cs.end - s_tim) * 1000]
+            result.append(row)
+        return result
+
+
+class SynthesizerQueue(object):
+    """docstring for SynthesizerQueue."""
+
+    def __init__(self):
+        super(SynthesizerQueue, self).__init__()
+        self.synth = NSSpeechSynthesizer.alloc().init()
+        self.didComplete = None
+        q_delg = SpeechDelegate.alloc().init()
+        self.synth.setDelegate_(q_delg)
+
+        def synth_complete():
+            end_time = time()
+            for i in range(len(self.phoneme_timing)):
+                if i == len(self.phoneme_timing) - 1:
+                    self.phoneme_timing[i].duration = end_time - \
+                        self.phoneme_timing[i].start
+                    self.phoneme_timing[i].end = end_time
+                else:
+                    self.phoneme_timing[i].duration = self.phoneme_timing[i +
+                                                                          1].start - self.phoneme_timing[i].start
+                    self.phoneme_timing[i].end = self.phoneme_timing[i + 1].start
+
+            total_time = sum(
+                [i.duration for i in self.phoneme_timing if i.is_audible()])
+            for ph in self.phoneme_timing:
+                if ph.is_audible():
+                    ph.fraction = ph.duration / total_time
+            if self.didComplete:
+                self.data.segments = self.phoneme_timing
+                self.data.tune = PhonemeTiming.to_tune(self.phoneme_timing)
+                self.didComplete(self.data)
+
+        def will_speak_phoneme(phon):
+            phtm = PhonemeTiming(phon, time())
+            self.phoneme_timing.append(phtm)
+
+        def will_speak_word():
+            pass
+            # coz it comes after the first phoneme of the word is started
+            # phtm = PhonemeTiming('~', time())
+            # self.phoneme_timing.append(phtm)
+
+        q_delg.setC_W_Ph_(synth_complete, will_speak_word, will_speak_phoneme)
+
+    def queueTask(self, text):
+        rand_no = str(random.randint(0, 10000))
+        fname = '{}-{}.aiff'.format(text, rand_no)
+        sanitized = format_filename(fname)
+        dest_file = dest_dir + sanitized
+        cli_gen_audio(text, dest_file)
+        self.phoneme_timing = []
+        self.data = SegData(text, sanitized)
+        self.synth.startSpeakingString_(text)
+
+
+def story_texts():
+    # story_file = './inputs/all_stories_hs.json'
+    story_file = './inputs/all_stories.json'
+    stories_data = json.load(open(story_file))
+    # text_list_dup = [t[0] for i in stories_data.values() for t in i]
+    text_list_dup = [t for i in stories_data.values() for t in i]
+    text_list = sorted(list(set(text_list_dup)))
+    return text_list
+
+
+def generate_audio():
+    synthQ = SynthesizerQueue()
+    phrases = random.sample(story_texts(), 5)  # story_texts()
+    f = open(csv_dest_file, 'w')
+    s_csv_w = csv.writer(f, quoting=csv.QUOTE_MINIMAL)
+    i = 0
+    p = tqdm(total=len(phrases))
+
+    def nextTask(seg_data=None):
+        nonlocal i
+        if i < len(phrases):
+            p.set_postfix(phrase=phrases[i])
+            p.update()
+            synthQ.queueTask(phrases[i])
+            i += 1
+        else:
+            p.close()
+            f.close()
+            dg = NSApplication.sharedApplication().delegate
+            print('App terminated.')
+            NSApp().terminate_(dg)
+        if seg_data:
+            s_csv_w.writerows(seg_data.csv_rows())
+    synthQ.didComplete = nextTask
+    nextTask()
 
 
 def main():
-    speech_delg = SpeechDelegate.alloc().init()
+
-    speech_delg.speechSynthesizer_didFinishSpeaking_('t',True)
-    voices = NSSpeechSynthesizer.availableVoices()
-    identifier = voices[2]
-    time()
-    alex_voice = NSSpeechSynthesizer.alloc().initWithVoice_(identifier)
-    alex_voice.setDelegate_(speech_delg)
-    alex_voice.startSpeakingString_("This is a test for speech synthesis generation")
     # Create a new application instance ...
     a = NSApplication.sharedApplication()
     # ... and create its delgate.  Note the use of the
@@ -69,5 +222,6 @@ def main():
 
     AppHelper.runEventLoop()
 
+
 if __name__ == '__main__':
     main()