catiR
commited on
Commit
•
f0fa26d
1
Parent(s):
82bdcd7
app
Browse files- app.py +78 -0
- scripts/__init__.py +0 -0
- scripts/runSQ.py +28 -11
app.py
ADDED
@@ -0,0 +1,78 @@
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import gradio as gr
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import subprocess
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import scripts.runSQ
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#https://huggingface.co/spaces/clr/prosalign/blob/main/app.py
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def setup():
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r0 = subprocess.run(["pwd"], capture_output=True, text=True)
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print('PWD::', r0.stdout)
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r1 = subprocess.run(["wget", "https://github.com/google/REAPER/archive/refs/heads/master.zip"], capture_output=True, text=True)
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print(r1.stdout)
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subprocess.run(["unzip", "./master.zip"])
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subprocess.run(["mv", "REAPER-master", "REAPER"])
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subprocess.run(["rm", "./master.zip"])
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os.chdir('./REAPER')
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subprocess.run(["mkdir", "build"])
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os.chdir('./build')
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r2 = subprocess.run(["cmake", ".."], capture_output=True, text=True)
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print(r2.stdout)
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r3 = subprocess.run(["make"], capture_output=True, text=True)
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print(r3.stdout)
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os.chdir('../..')
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r9 = subprocess.run(["ls", "-la"], capture_output=True, text=True)
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print('LS::', r9.stdout)
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print('about to setup')
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setup()
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def f1(voices, sent):
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one_tts = scripts.runSQ.run(sentence,voices)
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return (one_tts)
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bl = gr.Blocks()
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with bl:
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temp_sentences = ['Litlaus græn hugmynd?','Var það ekki nóg?', 'Ef svo er hvað heita þau þá?','Eru maríuhænur á Íslandi?']
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voices = ['Alfur','Dora']
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# currently i only get json speech marks for those two.
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# supposedly they also provided for Karl, Dora, but i dont even get their wavs
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# i get everyone elses wavs tho
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with gr.Row():
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with gr.column(scale=4):
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voiceselect = gr.checkboxgroup(voices, label="TTS voice",value='Alfur')
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temp_sentmenu = gr.dropdown(temp_sentences, label="Sentence")
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with gr.column(scale=1:)
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temp_button = gr.Button(value="A button")
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tts_output = gr.Audio(interactive=False)
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tmp_button.click(f1,[voiceselect,temp_sentmenu],[tts_output])
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if __name__ == "__main__":
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bl.launch()
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scripts/__init__.py
ADDED
File without changes
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scripts/runSQ.py
CHANGED
@@ -8,30 +8,41 @@ from tapi import tiro
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# report how many, or if 0.
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def run():
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sentence = 'hvaða sjúkdómar geta fylgt óbeinum reykingum'
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voices = ['Alfur','Dilja','Karl', 'Dora']
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# On tts.tiro.is speech marks are only available
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# for the voices: Alfur, Dilja, Karl and Dora.
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corpus_meta = 'human_data/SQL1adult_metadata.tsv'
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speech_dir = 'human_data/audio/squeries/'
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speech_aligns = 'human_data/aligns/squeries/'
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speech_f0 = 'human_data/f0/squeries/'
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align_model_path ="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-icelandic-ep10-1000h"
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tts_dir = 'tts_data/'
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meta = get_recordings(
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if meta:
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align_human(meta,speech_aligns,speech_dir,align_model_path)
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f0_human(meta, speech_f0, speech_dir, 'TODO path to reaper')
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if voices:
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get_tts(sentence,voices,tts_dir)
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f0_tts(sentence, voices, tts_dir, 'TODO path to reaper')
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# find all the recordings of a given sentence
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# listed in the corpus metadata.
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# sentence should be provided lowercase without punctuation
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dpath = sentence.replace(' ','_')[:65]
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no_voice = []
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for v in voices:
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wpath = f'{ttsdir}{dpath}/{v}.wav'
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jpath = f'{ttsdir}{dpath}/{v}.json'
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if not (os.path.exists(wpath) and os.path.exists(jpath)):
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no_voice.append(v)
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if no_voice:
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print(f'Need to generate TTS for {len(no_voice)} voices')
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else:
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print('TTS for all voices existed')
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# report how many, or if 0.
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def run(sentence, voices):
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#sentence = 'hvaða sjúkdómar geta fylgt óbeinum reykingum'
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#voices = ['Alfur','Dilja','Karl', 'Dora']
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# On tts.tiro.is speech marks are only available
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# for the voices: Alfur, Dilja, Karl and Dora.
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corpus_meta = '../human_data/SQL1adult_metadata.tsv'
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speech_dir = '../human_data/audio/squeries/'
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speech_aligns = '../human_data/aligns/squeries/'
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speech_f0 = '../human_data/f0/squeries/'
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align_model_path ="carlosdanielhernandezmena/wav2vec2-large-xlsr-53-icelandic-ep10-1000h"
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tts_dir = '../tts_data/'
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norm_sentencd = snorm(sentence)
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meta = get_recordings(norm_sentence, corpus_meta)
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if meta:
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align_human(meta,speech_aligns,speech_dir,align_model_path)
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f0_human(meta, speech_f0, speech_dir, 'TODO path to reaper')
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if voices:
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temp_a_sample = get_tts(sentence,voices,tts_dir)
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f0_tts(sentence, voices, tts_dir, 'TODO path to reaper')
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return temp_a_sample
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def snorm(s):
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s = ''.join([c.lower() for c in s if not unicodedata.category(c).startswith("P") ])
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while ' ' in s:
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s = s.replace(' ', ' ')
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return s
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# find all the recordings of a given sentence
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# listed in the corpus metadata.
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# sentence should be provided lowercase without punctuation
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dpath = sentence.replace(' ','_')[:65]
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no_voice = []
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temp_sample_path = ''
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for v in voices:
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wpath = f'{ttsdir}{dpath}/{v}.wav'
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jpath = f'{ttsdir}{dpath}/{v}.json'
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if not (os.path.exists(wpath) and os.path.exists(jpath)):
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no_voice.append(v)
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if not temp_sample_path:
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temp_sample_path = wpath
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if no_voice:
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print(f'Need to generate TTS for {len(no_voice)} voices')
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else:
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print('TTS for all voices existed')
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return temp_sample_path
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