Add application file

Speech_app.py

@@ -0,0 +1,147 @@
+import streamlit as st
+import time
+from IPython.display import Markdown, display
+from datetime import datetime
+from transformers import SpeechT5Processor, SpeechT5ForSpeechToSpeech, SpeechT5HifiGan,SpeechT5ForTextToSpeech
+from datasets import load_dataset
+import numpy as np
+import torch
+from io import StringIO
+# from streamlit_chat import message as st_message
+
+
+html_temp= """
+    <div style="background-color:tomato;padding:10px">
+    <h2 style="color:white;text-align:centre;"> Text-to-Speech </h2>
+    </div>
+    """
+st.markdown(html_temp,unsafe_allow_html=True)
+
+st.markdown(
+   
+    """
+    This is an AI tool. This tool will convert your text into audio. You can also drop you text file here and download the audio file.
+"""
+)
+model = SpeechT5ForTextToSpeech.from_pretrained("speecht5_tts")
+processor = SpeechT5Processor.from_pretrained("speecht5_tts")
+vocoder = SpeechT5HifiGan.from_pretrained("speecht5_hifigan")
+
+speaker_embeddings = np.load("cmu_us_slt_arctic-wav-arctic_a0499.npy")
+speaker_embeddings = torch.tensor(speaker_embeddings).unsqueeze(0)
+
+text = st.text_area("Type your text..")
+st.button("Convert")
+inputs = processor(text=text, return_tensors="pt")
+spectrogram = model.generate_speech(inputs["input_ids"], speaker_embeddings)
+with torch.no_grad():
+    speech = vocoder(spectrogram)
+    import soundfile as sf
+    sf.write("speech.wav", speech.numpy(), samplerate=16000)
+    
+audio_file = open('speech.wav', 'rb')
+audio_bytes = audio_file.read()
+st.audio(audio_bytes, format='audio/wav')
+
+
+uploaded_file=st.file_uploader("Upload your text file here",type=['txt'] )
+if uploaded_file is not None:
+    stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
+    #To read file as string:
+    text = stringio.read()
+    st.write(text)
+    
+    st.button("Convert",key=1)
+    inputs = processor(text=text, return_tensors="pt")
+    spectrogram = model.generate_speech(inputs["input_ids"], speaker_embeddings)
+    with torch.no_grad():
+        speech = vocoder(spectrogram)
+        import soundfile as sf
+        sf.write("speech.wav", speech.numpy(), samplerate=16000)
+    audio_file = open('speech.wav', 'rb')
+    audio_bytes = audio_file.read()
+    st.audio(audio_bytes, format='audio/wav')
+    
+    
+    
+    
+    
+st.text("Thanks for using")
+            
+if st.button("About"):
+        st.text("Created by Surendra Kumar")
+## footer
+from htbuilder import HtmlElement, div, ul, li, br, hr, a, p, img, styles, classes, fonts
+from htbuilder.units import percent, px
+from htbuilder.funcs import rgba, rgb
+
+
+def image(src_as_string, **style):
+    return img(src=src_as_string, style=styles(**style))
+
+
+def link(link, text, **style):
+    return a(_href=link, _target="_blank", style=styles(**style))(text)
+
+
+def layout(*args):
+    style = """
+    <style>
+      # MainMenu {visibility: hidden;}
+      footer {visibility: hidden;}
+     .stApp { bottom: 105px; }
+    </style>
+    """
+
+    style_div = styles(
+        position="fixed",
+        left=0,
+        bottom=0,
+        margin=px(0, 0, 0, 0),
+        width=percent(100),
+        color="black",
+        text_align="center",
+        height="auto",
+        opacity=1
+    )
+
+    style_hr = styles(
+        display="block",
+        margin=px(8, 8, "auto", "auto"),
+        border_style="solid",
+        border_width=px(0.5)
+    )
+
+    body = p()
+    foot = div(
+        style=style_div
+    )(
+        hr(
+            style=style_hr
+        ),
+        body
+    )
+    st.markdown(style,unsafe_allow_html=True)
+
+    for arg in args:
+        if isinstance(arg, str):
+            body(arg)
+
+        elif isinstance(arg, HtmlElement):
+            body(arg)
+
+    st.markdown(str(foot), unsafe_allow_html=True)
+
+
+def footer():
+    myargs = [
+        "©️ surendraKumar",
+        br(),
+        link("https://www.linkedin.com/in/surendra-kumar-51802022b", image('https://icons.getbootstrap.com/assets/icons/linkedin.svg') ),
+        br(),
+        link("https://www.instagram.com/im_surendra_dhaka/",image('https://icons.getbootstrap.com/assets/icons/instagram.svg')),
+    ]
+    layout(*myargs)
+
+if __name__ == "__main__":
+    footer()

cmu_us_slt_arctic-wav-arctic_a0499.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:600f9bd164ef45365598668c9d935cb5f04b7de1fb97bcb0c330a6aaeccc50c9
+size 2176