Text to speech in Python

audiotext.py

# importing libraries
import pathlib
import sys
import speech_recognition as sr
import os
from pydub import AudioSegment
from pydub.silence import split_on_silence

# create a speech recognition object
r = sr.Recognizer()

# a function to recognize speech in the audio file
# so that we don't repeat ourselves in in other functions
def transcribe_audio(path):
    # use the audio file as the audio source
    with sr.AudioFile(path) as source:
        audio_listened = r.record(source)
        # try converting it to text
        text = r.recognize_google(audio_listened)
    return text

# a function that splits the audio file into chunks on silence
# and applies speech recognition
def get_large_audio_transcription_on_silence(path):
    """Splitting the large audio file into chunks
    and apply speech recognition on each of these chunks"""
    # open the audio file using pydub
    sound = AudioSegment.from_file(path)
    # split audio sound where silence is 500 miliseconds or more and get chunks
    chunks = split_on_silence(sound,
                              # experiment with this value for your target audio file
                              min_silence_len = 500,
                              # adjust this per requirement
                              silence_thresh = sound.dBFS-14,
                              # keep the silence for 1 second, adjustable as well
                              keep_silence=500,
                              )
    folder_name = "audio-chunks"
    # create a directory to store the audio chunks
    if not os.path.isdir(folder_name):
        os.mkdir(folder_name)
    whole_text = ""
    # process each chunk
    for i, audio_chunk in enumerate(chunks, start=1):
        # export audio chunk and save it in
        # the `folder_name` directory.
        chunk_filename = os.path.join(folder_name, f"chunk{i}.wav")
        audio_chunk.export(chunk_filename, format="wav")
        # recognize the chunk
        try:
            text = transcribe_audio(chunk_filename)
        except sr.UnknownValueError as e:
            print("Error:", str(e))
        else:
            text = f"{text.capitalize()}. "
            print(chunk_filename, ":", text)
            whole_text += text
    # return the text for all chunks detected
    return whole_text


def convert_mp3_files(path):
    path = pathlib.Path(path)
    mp3 = [str(mp3_file) for mp3_file in path.glob('**/*.mp3')]
    for m in mp3:
        sound = AudioSegment.from_mp3(m)
        x = m.replace(".mp3", ".wav")
        sound.export(f"converted/{os.path.basename(x)}", format="wav")


def find_audio_files(path):
    path = pathlib.Path(path)
    return [str(mp3_file) for mp3_file in path.glob('**/*.wav')]

# Usage
if __name__ == '__main__':
    p = sys.argv[1]
    convert_mp3_files(p)
    files = find_audio_files(p)
    d = dict()
    for f in files:
        d[f] = transcribe_audio(f)
    with open('merged-audio.txt', 'w') as out:
        for k, v in d.items():
            print(k, v, file=out)