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import streamlit as st | |
st.set_page_config(page_title="SpeechT5", page_icon = "static/images/PLAYGROUND_LOGO_REDESIGN_IMAGE.png") | |
hide_menu_style = """ | |
<style> | |
footer {visibility: hidden;} | |
</style> | |
""" | |
st.markdown(hide_menu_style, unsafe_allow_html= True) | |
st.write("Languages: Vietnamese, English") | |
import glob | |
from src.model import Model, dataset_dict | |
if "model_name" not in st.session_state: | |
st.session_state.model_name = None | |
st.session_state.audio = None | |
st.session_state.wav_file = None | |
st.session_state.speaker_url = "" | |
with st.sidebar.form("my_form"): | |
text = st.text_input("Your input: ") | |
model_name = st.selectbox(label="Model: ", options=["truong-xuan-linh/speecht5-vietnamese-voiceclone-lsvsc", | |
"truong-xuan-linh/speecht5-vietnamese-commonvoice", | |
"truong-xuan-linh/speecht5-vietnamese-hlpcvoice", | |
"truong-xuan-linh/speecht5-vietnamese-vstnvoice", | |
"truong-xuan-linh/speecht5-vietnamese-kcbnvoice", | |
"truong-xuan-linh/speecht5-irmvivoice", | |
"truong-xuan-linh/speecht5-vietnamese-voiceclone", | |
"truong-xuan-linh/speecht5-multilingual-voiceclone-speechbrain", | |
"truong-xuan-linh/speecht5-vietnamese-voiceclone-v3", | |
"truong-xuan-linh/speecht5-multilingual-voiceclone-pynote", | |
"truong-xuan-linh/speecht5-multilingual-voiceclone-speechbrain-nonverbal"]) | |
speaker_id = st.selectbox("source voice", options= ["speech_dataset_denoised"] + list(dataset_dict.keys())) | |
speaker_url = st.text_input("speaker url", value="") | |
# speaker_id = st.selectbox("source voice", options= glob.glob("voices/*.wav")) | |
if st.session_state.model_name != model_name or speaker_url != st.session_state.speaker_url : | |
st.session_state.model_name = model_name | |
st.session_state.model = Model(model_name=model_name, speaker_url=speaker_url) | |
st.session_state.speaker_id = speaker_id | |
st.session_state.speaker_url = speaker_url | |
# Every form must have a submit button. | |
submitted = st.form_submit_button("Submit") | |
if submitted: | |
st.session_state.audio = st.session_state.model.inference(text=text, speaker_id=speaker_id) | |
audio_holder = st.empty() | |
audio_holder.audio(st.session_state.audio, sample_rate=16000) |