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Update app.py
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app.py
CHANGED
@@ -4,6 +4,9 @@ from scipy.io.wavfile import write
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import tempfile
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import os
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from pydub import AudioSegment
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# Initialize model configuration
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model_config = outetts.HFModelConfig_v1(
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@@ -21,6 +24,7 @@ st.write("Enter text below to generate speech.")
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# Sidebar for reference voice
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st.sidebar.title("Voice Cloning")
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reference_audio = st.sidebar.file_uploader("Upload a reference audio (any format)", type=["wav", "mp3", "ogg", "flac", "m4a"])
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# Function to convert audio to WAV format
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def convert_to_wav(audio_file):
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@@ -29,28 +33,51 @@ def convert_to_wav(audio_file):
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audio.export(temp_audio.name, format="wav")
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return temp_audio.name
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if reference_audio:
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ref_audio_path = convert_to_wav(reference_audio)
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else:
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-
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# Recording functionality
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st.sidebar.write("Or record your voice below:")
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if st.sidebar.button("Record Voice"):
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text_input = st.text_area("Text to convert to speech:", "Hello, this is an AI-generated voice.")
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if st.button("Generate Speech"):
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with st.spinner("Generating audio..."):
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# Generate speech with
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output = interface.generate(
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text=text_input,
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temperature=0.1,
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repetition_penalty=1.1,
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max_length=4096,
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)
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# Save the synthesized speech to a file
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@@ -62,5 +89,5 @@ if st.button("Generate Speech"):
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st.success("Speech generated successfully!")
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# Clean up temporary files
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if
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os.remove(ref_audio_path)
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import tempfile
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import os
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from pydub import AudioSegment
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import sounddevice as sd
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import wave
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import numpy as np
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# Initialize model configuration
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model_config = outetts.HFModelConfig_v1(
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# Sidebar for reference voice
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st.sidebar.title("Voice Cloning")
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reference_audio = st.sidebar.file_uploader("Upload a reference audio (any format)", type=["wav", "mp3", "ogg", "flac", "m4a"])
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transcript = st.sidebar.text_area("Transcription of the reference audio")
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# Function to convert audio to WAV format
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def convert_to_wav(audio_file):
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audio.export(temp_audio.name, format="wav")
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return temp_audio.name
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if reference_audio and transcript:
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ref_audio_path = convert_to_wav(reference_audio)
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# Create speaker profile
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speaker = interface.create_speaker(ref_audio_path, transcript)
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# Save the speaker profile
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interface.save_speaker(speaker, "speaker.json")
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else:
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speaker = None
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# Recording functionality
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def record_audio(duration=5, samplerate=44100):
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st.sidebar.write("Recording...")
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recording = sd.rec(int(duration * samplerate), samplerate=samplerate, channels=1, dtype=np.int16)
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sd.wait()
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temp_audio_path = tempfile.NamedTemporaryFile(delete=False, suffix=".wav").name
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with wave.open(temp_audio_path, "wb") as wf:
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wf.setnchannels(1)
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wf.setsampwidth(2)
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wf.setframerate(samplerate)
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wf.writeframes(recording.tobytes())
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return temp_audio_path
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if not speaker:
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st.sidebar.write("Or record your voice below:")
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if st.sidebar.button("Record Voice"):
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ref_audio_path = record_audio()
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st.sidebar.success("Recording complete!")
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transcript = st.sidebar.text_area("Transcription of the recorded audio")
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if transcript:
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# Create speaker profile from recorded audio
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speaker = interface.create_speaker(ref_audio_path, transcript)
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# Save the speaker profile
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interface.save_speaker(speaker, "speaker.json")
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text_input = st.text_area("Text to convert to speech:", "Hello, this is an AI-generated voice.")
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if st.button("Generate Speech"):
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with st.spinner("Generating audio..."):
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# Generate speech with or without the speaker profile
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output = interface.generate(
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text=text_input,
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temperature=0.1,
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repetition_penalty=1.1,
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max_length=4096,
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speaker=speaker
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)
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# Save the synthesized speech to a file
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st.success("Speech generated successfully!")
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# Clean up temporary files
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if reference_audio:
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os.remove(ref_audio_path)
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