Text to speech

Opensource Models

• https://github.com/coqui-ai/TTS
• https://huggingface.co/tasks/text-to-speech

Examples to generate audio using python

Option 1: Using Pre-trained Models and APIs This is the simplest and quickest way to get started.

• Libraries:
  • gTTS: A straightforward library that uses Google’s TTS API.
  • pyttsx3: A cross-platform library that works offline.
  • Picovoice Orca: Provides high-quality voices with a smaller footprint.

from gtts import gTTS
 
text = "Hello, this is a text-to-speech example."
tts = gTTS(text=text, lang='en')
tts.save("output.mp3")

Option 2: Cloud services

import openai
 
response = openai.audio.speech.create(
    model="tts-1",
    voice="alloy",
    input="This is an example using OpenAI's TTS."
)
 
with open("output.mp3", "wb") as f:
    f.write(response.content)

Option 3: Building a Custom Model This involves training your own TTS model, which requires a significant amount of data and computational resources.

• Libraries:

  • TensorFlow: A popular deep learning framework.
  • PyTorch: Another powerful deep learning framework.
  • Tacotron 2: A well-known TTS model architecture.
  • WaveNet: A neural network for generating audio waveforms.

• Steps:

  1. Gather Data: Collect a large dataset of paired text and audio recordings.
  2. Preprocess Data: Clean the text, extract features from the audio, and align the text with the audio.
  3. Train Model: Use a deep learning framework to train your TTS model on the preprocessed data.
  4. Inference: Deploy your trained model to convert new text into speech.

Option 4:

from pydub import AudioSegment
from pydub.generators import Sine
 
# Text-to-speech section
intro_text = """
Welcome to this short meditation practice. Begin by sitting comfortably, with your back straight 
and your hands resting gently on your lap. Close your eyes, and take a deep breath in through your nose, 
and slowly exhale through your mouth.
"""
 
# Using silent audio as a placeholder for the 2-minute meditation duration
pause = AudioSegment.silent(duration=120000)  # 2 minutes of silence
 
# End of meditation message
end_text = "This concludes your meditation. When you're ready, gently open your eyes."
 
# Generate audio segments with TTS
intro_audio = AudioSegment.silent(duration=1000)  # Placeholder to simulate TTS audio
end_audio = AudioSegment.silent(duration=1000)    # Placeholder to simulate TTS audio
 
# Combine intro, 2-minute pause, and end audio
meditation_audio = intro_audio + pause + end_audio
 
# Save the audio file
output_file = "/mnt/data/meditation_practice_with_pause.mp3"
meditation_audio.export(output_file, format="mp3")
 
output_file