gtts.py

import pyttsx3
import re
from pydub import AudioSegment
from pydub.generators import Sine
import json

def speak_with_pauses(text, rate=150):
    # JSONIFY all the segments given by LLM
    segments = json.loads(text)
    print(segments)

    # initialized variables
    audio_segments = []
    durations = []
    asset_list = []

    # adding a silence of 10 second to initialize the audio
    silence_segment = Sine(0).to_audio_segment(duration=0.1)  # Convert to milliseconds
    audio_segments.append(silence_segment)
    durations.append(0.1)

    # creating an instance of tts engine
    engine = pyttsx3.init()
    engine.setProperty('rate', rate)

    for i in range(1, len(segments)+1):
        print(segments[i-1])

        # Every instance have three values asset, pause and sentence
        sentence = segments[i-1].get('sentence')
        pause_duration = segments[i-1].get('pause')
        asset = segments[i-1].get('asset')

        if sentence:
            # Creating audion of one segment and saving in temp.wav
            engine.save_to_file(sentence, 'temp.wav')
            engine.runAndWait()

            # adding that temp audio to the main audio clip
            audio_segment = AudioSegment.from_wav("temp.wav")
            audio_segments.append(audio_segment)

            # updating the durations adding the duration of this temp
            duration = len(audio_segment) / 1000  # convert milliseconds to seconds
            durations.append(duration)
        
        asset_list.append({"time": sum(durations[:-1]), "asset": asset})

        if pause_duration and pause_duration > 0:
            silence_segment = Sine(0).to_audio_segment(duration=pause_duration)  # milliseconds
            audio_segments.append(silence_segment)
            durations.append(pause_duration / 1000)  # convert milliseconds to seconds

    # Concatenate audio segments
    output_audio = audio_segments[0]
    for segment in audio_segments[1:]:
        output_audio = output_audio.append(segment, crossfade=0)

    # Create JSON object to store duration data
    duration_json = {}
    for i, dur in enumerate(durations):
        duration_json[f"Segment {i+1}"] = dur

    with open('pause_durations.json', 'w') as json_file:
        json.dump(duration_json, json_file, indent=4)

    # Export the audio
    output_audio.export("final_audio_with_pauses.mp3", format="mp3")
    print("Audio exported successfully.")

    return ['final_audio_with_pauses.mp3', asset_list]

# Example usage
# test_text = """Welcome back  {"asset": "welcome.mp4", "pause": 100 } folks! Today, we're going to discuss a fundamental aspect of game development: collision detection. {"asset": "collision_detection.mp4", "pause": 100} Now, you might be wondering, what exactly is collision detection? {"pause": 200} Well, it's the process of determining when two objects in a game world intersect or come into contact with each other. {"pause": 200} This might sound straightforward, but trust me, there's a bit more to it than meets the eye. {"pause": 300} Let's delve deeper into this topic and explore how we can implement collision detection in our game. {"pause": 300}"""
# output_audio = speak_with_pauses(test_text, 150)
# print("Asset list:", output_audio[1])