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from tts_infer.tts import TextToMel, MelToWav
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from tts_infer.transliterate import XlitEngine
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from tts_infer.num_to_word_on_sent import normalize_nums
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import re
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import numpy as np
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from scipy.io.wavfile import write
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from mosestokenizer import *
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from indicnlp.tokenize import sentence_tokenize
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import gradio as gr
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INDIC = ["as", "bn", "gu", "hi", "kn", "ml", "mr", "or", "pa", "ta", "te"]
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def split_sentences(paragraph, language):
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if language == "en":
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with MosesSentenceSplitter(language) as splitter:
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return splitter([paragraph])
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elif language in INDIC:
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return sentence_tokenize.sentence_split(paragraph, lang=language)
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device='cpu'
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text_to_mel = TextToMel(glow_model_dir='vakyansh-tts/tts_infer/odia/glow', device=device)
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mel_to_wav = MelToWav(hifi_model_dir='vakyansh-tts/tts_infer/odia/hifi', device=device)
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def run_tts(text, lang):
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final_text = text
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mel = text_to_mel.generate_mel(final_text)
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audio, sr = mel_to_wav.generate_wav(mel)
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write(filename='temp.wav', rate=sr, data=audio)
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return (sr, audio)
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def run_tts_paragraph(text, lang):
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audio_list = []
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split_sentences_list = split_sentences(text, language='hi')
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for sent in split_sentences_list:
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sr, audio = run_tts(sent, lang)
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audio_list.append(audio)
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concatenated_audio = np.concatenate([i for i in audio_list])
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write(filename='temp_long.wav', rate=sr, data=concatenated_audio)
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return (sr, concatenated_audio)
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_, audio = run_tts("ଆମେ ଦୁଖିତ, ଆପଣଙ୍କର ଚିନ୍ତାଧାରାକୁ ସମାଧାନ କରିବାରେ ଅସମର୍ଥ, ଆମେ ଆପଣଙ୍କ ସହ ଯୋଗାଯୋଗ କରିବାକୁ ୱାର୍କସପ୍ଦ ଦଳକୁ କହିବୁ, ତୁମର ଦିନ ଶୁଭମୟ ହଉ.", "or")
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options = ["Odia"]
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newOptions = ["Male","Female"]
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language = gr.Dropdown(options,label="Select language")
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gender = gr.Dropdown(newOptions,label="Select Voice")
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input = gr.Textbox(
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label="Input from model will appear here:",
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lines=5
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)
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output = gr.Audio(label="Output from model will appear here:", type="filepath")
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gr.Interface(run_tts, inputs = [input,language], outputs=output,
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streaming=True, interactive=True,
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analytics_enabled=False, show_tips=False, enable_queue=True).launch(inline=False); |
