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import re
import numpy as np
from transformers import pipeline
import gradio as gr
# Available voices and their corresponding models
VOICES = {
"Amy (Female)": "microsoft/vits-piper-en-us-amy",
"Joe (Male)": "microsoft/vits-piper-en-us-joe",
"Clara (Female)": "microsoft/vits-piper-en-us-clb",
"Ryan (Male)": "microsoft/vits-piper-en-us-jvs"
}
def parse_segments(text):
"""Parse input text for speaker segments using regex"""
pattern = re.compile(r'$$(?P<speaker>[^$$]+)$$(?P<text>.*?)$$\/\1$$', re.DOTALL)
return [(match.group('speaker'), match.group('text').strip())
for match in pattern.finditer(text)]
def generate_podcast(input_text):
"""Convert text to podcast with multiple voices"""
try:
segments = parse_segments(input_text)
if not segments:
return (22050, np.zeros(0)), "No valid speaker segments found"
all_audio = []
current_pipe = None
current_model = ""
for speaker, text in segments:
if speaker not in VOICES:
return (22050, np.zeros(0)), f"Invalid speaker: {speaker}"
model_name = VOICES[speaker]
# Load model only when needed
if current_model != model_name:
if current_pipe: del current_pipe
current_pipe = pipeline("text-to-speech", model=model_name)
current_model = model_name
# Generate audio for this segment
output = current_pipe(text)
all_audio.append(output["audio"])
# Combine all audio segments with short pauses
final_audio = np.concatenate([np.concatenate((audio, np.zeros(5000))) for audio in all_audio])
return (output["sampling_rate"], final_audio), "Podcast generated successfully!"
except Exception as e:
return (22050, np.zeros(0)), f"Error: {str(e)}"
# Create Gradio interface
def podcast_interface(text):
(sr, audio), status = generate_podcast(text)
return (sr, audio) if audio.size > 0 else gr.update(), status
demo = gr.Interface(
fn=podcast_interface,
inputs=gr.Textbox(
label="Input Text with Speaker Tags",
lines=12,
placeholder="""Example format:
[Amy (Female)]Hello and welcome to today's episode![/Amy (Female)]
[Joe (Male)]Excited to have you here![/Joe (Male)]"""
),
outputs=[
gr.Audio(label="Generated Podcast", type="numpy"),
gr.Textbox(label="Status", value="Ready")
],
examples=[
["""[Amy (Female)]Welcome to our podcast![/Amy (Female)]
[Joe (Male)]Today we're discussing AI innovations.[/Joe (Male)]"""]
],
title="🎙️ Multi-Voice Podcast Generator",
description="Generate podcasts with multiple free AI voices using Microsoft's Piper TTS models. Use [SpeakerName] tags to assign different voices to different text segments.",
theme="soft",
allow_flagging="never"
)
if __name__ == "__main__":
demo.launch() |