is the following python code removing any ssml tags from the source json file before synthesizing it:

import boto3
import json
import os
import shutil  # Import shutil for file operations
from pydub import AudioSegment
from pydub.exceptions import CouldntDecodeError

# Configure AWS Polly client
# Note: Ensure that your AWS credentials are configured in your environment.
polly_client = boto3.Session().client('polly')

# Define speaker voice mapping
SPEAKER_VOICES = {
    "Speaker 1": "Stephen",   # Replace with desired neural voices
    "Speaker 2": "Ruth"
}

# Define directories for temporary files
AUDIO_OUTPUT_DIR = r'D:\Podcast\audio_output'
TEMP_AUDIO_DIR = r'D:\Podcast\temp_audio'

# Create directories if they don't exist
os.makedirs(AUDIO_OUTPUT_DIR, exist_ok=True)
os.makedirs(TEMP_AUDIO_DIR, exist_ok=True)

def synthesize_speech(text, voice_id, output_filename):
    """
    Synthesizes speech using Amazon Polly and saves it to a file.
    """
    try:
        response = polly_client.synthesize_speech(
            Text=text,
            VoiceId=voice_id,
            OutputFormat='mp3',
            Engine='generative' # Use the 'neural' engine for Polly
        )
        # Save the audio stream returned by Amazon Polly
        with open(output_filename, 'wb') as file:
            file.write(response['AudioStream'].read())
        return output_filename
    except Exception as e:
        print(f"Error synthesizing speech: {e}")
        return None

def process_segment(segment):
    """
    Processes a segment by synthesizing audio for the content item.
    """
    segment_audio = None
    content_items = segment.get('content', [])
    if not content_items:
        return None
    # Assuming only one content item per segment
    content = content_items[0]
    if content.get('type') == 'dialogue':
        speaker_id = content.get('speaker_id')
        text = content.get('text')
        voice_id = SPEAKER_VOICES.get(speaker_id, 'Joanna')
        temp_audio_file = os.path.join(
            TEMP_AUDIO_DIR, f"segment_{segment['segment_number']}_{speaker_id}.mp3")
        synthesize_speech(text, voice_id, temp_audio_file)
        try:
            segment_audio = AudioSegment.from_mp3(temp_audio_file)
        except CouldntDecodeError:
            print(f"Could not decode audio file {temp_audio_file}")
            segment_audio = None
    # Annotations are skipped
    return segment_audio

def main():
    # Load the JSON data
    with open(r'D:\Podcast\podcast_script_natural.json', 'r', encoding='utf-8') as file:
        podcast_data = json.load(file)

    segments = podcast_data.get('segments', [])
    segment_audios = []

    # Process each segment and store the audio along with its overlap flag
    for segment in segments:
        segment_number = segment.get('segment_number')
        print(f"Processing segment {segment_number}")
        segment_audio = process_segment(segment)
        if segment_audio:
            segment_audios.append({
                'audio': segment_audio,
                'overlap': segment.get('overlap', False),
                'segment_number': segment_number
            })
        else:
            print(f"No audio generated for segment {segment_number}")

    if segment_audios:
        # Initialize final_audio with the first segment's audio
        final_audio = segment_audios[0]['audio']
        # Iterate over the segments to append them with correct overlay durations
        for i in range(1, len(segment_audios)):
            prev_segment = segment_audios[i - 1]
            current_segment = segment_audios[i]
            prev_overlap = prev_segment['overlap']
            current_overlap = current_segment['overlap']

            # Determine overlay duration based on the specified rules
            if not prev_overlap and not current_overlap:
                overlay_duration = 200  # milliseconds
            elif (not prev_overlap and current_overlap) or (prev_overlap and not current_overlap):
                overlay_duration = 100
            elif prev_overlap and current_overlap:
                overlay_duration = 400
            else:
                overlay_duration = 0  # Default case, should not occur

            current_audio = current_segment['audio']
            # Append the current_audio to final_audio with the calculated overlay duration
            final_audio = final_audio.append(current_audio, crossfade=overlay_duration)

        # Export the final audio
        output_file = os.path.join(AUDIO_OUTPUT_DIR, 'final_podcast.mp3')
        final_audio.export(output_file, format='mp3')
        print(f"Final podcast audio saved to {output_file}")

        # Clean up temporary files
        if os.path.exists(TEMP_AUDIO_DIR):
            shutil.rmtree(TEMP_AUDIO_DIR)
            print(f"Temporary files in {TEMP_AUDIO_DIR} have been deleted.")

    else:
        print("No audio was generated.")

if __name__ == "__main__":
    main()