253 lines
8.6 KiB
Python
253 lines
8.6 KiB
Python
import objc
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from AppKit import NSSpeechSynthesizer, NSSpeechInputModeProperty
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from AppKit import NSSpeechModePhoneme
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from Foundation import NSURL
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import json
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import csv
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import random
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import os
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import re
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import subprocess
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import time
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from tqdm import tqdm
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from generate_similar import similar_phoneme_phrase,similar_phrase
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from speech_tools import hms_string,create_dir,format_filename,reservoir_sample
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OUTPUT_NAME = 'test_5_words'
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dest_dir = os.path.abspath('.') + '/outputs/' + OUTPUT_NAME + '/'
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dest_file = './outputs/' + OUTPUT_NAME + '.csv'
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def dest_filename(w, v, r, t):
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rand_no = str(random.randint(0, 10000))
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fname = '{}-{}-{}-{}-{}.aiff'.format(w, v, r, t, rand_no)
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sanitized = format_filename(fname)
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return sanitized
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def dest_path(v, r, n):
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rel = v + '/' + str(r) + '/' + n
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return (dest_dir + rel), rel
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def cli_gen_audio(speech_cmd, rate, voice, out_path):
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subprocess.call(
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['say', '-v', voice, '-r',
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str(rate), '-o', out_path, "'"+speech_cmd+"'"])
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class SynthFile(object):
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"""docstring for SynthFile."""
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def __init__(self, word, phon, filename, voice, voice_lang, rate, operation):
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super(SynthFile, self).__init__()
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self.word = word
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self.phoneme = phon
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self.filename = filename
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self.voice = voice
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self.voice_lang = voice_lang
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self.rate = rate
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self.variant = operation
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def get_json(self):
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return {
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'filename': self.filename,
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'voice': self.voice,
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'rate': self.rate,
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'operation': self.operation
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}
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def get_csv(self):
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cols = [self.word, self.phoneme, self.voice,
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self.voice_lang, self.rate, self.variant,
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self.filename]
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return ','.join([str(c) for c in cols])+'\n'
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def get_values(self):
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cols = [self.word, self.phoneme, self.voice,
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self.voice_lang, self.rate, self.variant,
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self.filename]
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return [str(c) for c in cols]
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class SynthVariant(object):
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"""docstring for SynthVariant."""
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def __init__(self, identifier, voice, lang, rate):
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super(SynthVariant, self).__init__()
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self.synth = NSSpeechSynthesizer.alloc().initWithVoice_(identifier)
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self.synth.setVolume_(100)
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self.synth.setRate_(rate)
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self.phone_synth = NSSpeechSynthesizer.alloc().initWithVoice_(
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identifier)
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self.phone_synth.setVolume_(100)
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self.phone_synth.setRate_(rate)
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self.phone_synth.setObject_forProperty_error_(
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NSSpeechModePhoneme, NSSpeechInputModeProperty, None)
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self.identifier = identifier
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self.rate = rate
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self.name = voice
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self.lang = lang
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self.phoneme_capable = self.is_phoneme_capable()
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def __repr__(self):
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return 'Synthesizer[{} - {}]'.format(self.name, self.rate)
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def is_phoneme_capable(self):
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orig_phon = self.synth.phonemesFromText_('water')
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return orig_phon != ''
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def generate_audio(self, text, variant):
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orig_phon, phoneme, phon_cmd = self.synth.phonemesFromText_(
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text), '', text
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if variant == 'low':
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# self.synth.startSpeakingString_toURL_(word,d_url)
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phoneme = orig_phon
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elif variant == 'medium':
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phoneme = similar_phoneme_phrase(orig_phon)
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phon_cmd = '[[inpt PHON]] ' + phoneme
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elif variant == 'high':
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phoneme = similar_phrase(text)
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phon_cmd = phoneme
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# elif variant == 'long':
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# if phon != '':
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# self.phone_synth.startSpeakingString_toURL_(phon,d_url)
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# else:
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# self.synth.startSpeakingString_toURL_(word,d_url)
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fname = dest_filename(text, self.name, self.rate, variant)
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d_path, r_path = dest_path(self.name, self.rate, fname)
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# d_url = NSURL.fileURLWithPath_(d_path)
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cli_gen_audio(phon_cmd, self.rate, self.name, d_path)
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return SynthFile(text, phoneme, r_path, self.name, self.lang, self.rate, variant)
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def create_synth_dirs(self):
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if self.phoneme_capable:
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create_dir(dest_dir + self.name + '/' + str(self.rate))
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@staticmethod
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def voices_for_lang(lang):
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voices_installed = NSSpeechSynthesizer.availableVoices()
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voice_attrs = [
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NSSpeechSynthesizer.attributesForVoice_(v) for v in voices_installed
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]
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# sk = [k for k in voice_attrs[0].keys() if k not in [
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# 'VoiceIndividuallySpokenCharacters', 'VoiceSupportedCharacters']]
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# s_attrs = [[v[i] for i in sk] for v in voice_attrs if 'VoiceShowInFullListOnly' in v
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# and 'VoiceRelativeDesirability' in v]
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return [
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(v['VoiceIdentifier'],
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v['VoiceName'],
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v['VoiceLanguage']) for v in voice_attrs
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if v['VoiceLanguage'] == lang
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and v['VoiceGender'] != 'VoiceGenderNeuter'
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]
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@classmethod
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def synth_with(cls,voice_params,rate=180):
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identifier,voice,lang = voice_params
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return cls(identifier,voice,lang,rate)
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def synth_generator():
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us_voices_ids = SynthVariant.voices_for_lang('en-US')
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voice_rates = [150, 180, 210]#, 250]
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voice_synths = []
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create_dir(dest_dir)
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for vp in us_voices_ids:
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for r in voice_rates:
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s = SynthVariant.synth_with(vp,r)
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if s.phoneme_capable:
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print('Adding ', s)
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voice_synths.append(s)
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else:
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print('Discarding phoneme incapable ', s)
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def synth_for_words(words, writer):
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start_time = time.time()
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prog_title = "Synthesizing {} words : ".format(len(words))
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for s in voice_synths:
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s.create_synth_dirs()
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for v in ['low', 'medium', 'high']:
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prog = tqdm(words)
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prog.set_postfix(variant=v,voice=s.name,rate=s.rate)
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for w in tqdm(words):
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prog.set_description('Synthesizing text:"{}"'.format(w))
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synthed = s.generate_audio(w, v)
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writer(synthed)
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prog.close()
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end_time = time.time()
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time_str = hms_string(end_time - start_time)
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print("It took {} to synthsize all variants.".format(time_str))
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return synth_for_words
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def synth_logger(fname, csv_mode=False):
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f = open(fname, 'w')
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s_csv_w = csv.writer(f, quoting=csv.QUOTE_MINIMAL)
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def csv_writer(s):
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s_csv_w.writerow(s.get_values())
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synth_list = []
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def json_writer(s):
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synth_list.append(s)
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def close_file():
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if csv_mode:
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f.close()
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else:
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json.dump([s.get_json() for s in synth_list], f)
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f.close()
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if csv_mode:
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return csv_writer, close_file
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else:
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return json_writer, close_file
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def generate_audio_for_text_list(text_list):
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(writer, closer) = synth_logger(dest_file, csv_mode=True)
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synth_for_texts = synth_generator()
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try:
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synth_for_texts(text_list, writer)
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except:
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import traceback
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import sys
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traceback.print_exc(file=sys.stdout)
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pass
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closer()
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def generate_audio_for_stories():
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'''
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Generates the audio sample variants for the list of words in the stories
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'''
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# story_file = './inputs/all_stories_hs.json'
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story_file = './inputs/all_stories.json'
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stories_data = json.load(open(story_file))
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# text_list_dup = [t[0] for i in stories_data.values() for t in i]
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text_list_dup = [t for i in stories_data.values() for t in i]
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text_list = sorted(list(set(text_list_dup)))
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generate_audio_for_text_list(text_list)
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def generate_test_audio_for_stories(sample_count=0):
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'''
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Picks a list of words from the wordlist that are not in story words
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and generates the variants
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'''
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story_file = './inputs/all_stories_hs.json'
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# story_file = './inputs/all_stories.json'
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stories_data = json.load(open(story_file))
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text_list_dup = [t[0] for i in stories_data.values() for t in i]
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text_list = sorted(list(set(text_list_dup)))
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# text_list = [i.replace('-','') for g in stories_data.values() for i in g]
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word_list = [i.strip('\n_') for i in open('./inputs/wordlist.txt','r').readlines()]
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text_set = set(text_list)
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new_word_list = [i for i in word_list if i not in text_set and len(i) > 4]
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# test_words = new_word_list[:int(len(text_list)/5+1)]
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test_words = reservoir_sample(new_word_list,sample_count) if sample_count > 0 else new_word_list
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generate_audio_for_text_list(test_words)
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if __name__ == '__main__':
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generate_test_audio_for_stories(5)
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# generate_audio_for_text_list(['I want to go home','education'])
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# generate_audio_for_stories()
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