import os import textwrap import scipy import ffmpeg import numpy as np def clear_screen(): """Clears the console screen.""" os.system("cls" if os.name == "nt" else "clear") def print_transcript(text): """Prints formatted transcript text.""" wrapper = textwrap.TextWrapper(width=60) for line in wrapper.wrap(text="".join(text)): print(line) def format_time(s): """Convert seconds (float) to SRT time format.""" hours = int(s // 3600) minutes = int((s % 3600) // 60) seconds = int(s % 60) milliseconds = int((s - int(s)) * 1000) return f"{hours:02}:{minutes:02}:{seconds:02},{milliseconds:03}" def create_srt_file(segments, output_file): with open(output_file, 'w', encoding='utf-8') as srt_file: segment_number = 1 for segment in segments: start_time = format_time(float(segment['start'])) end_time = format_time(float(segment['end'])) text = segment['text'] srt_file.write(f"{segment_number}\n") srt_file.write(f"{start_time} --> {end_time}\n") srt_file.write(f"{text}\n\n") segment_number += 1 def resample(file: str, sr: int = 16000): """ # https://github.com/openai/whisper/blob/7858aa9c08d98f75575035ecd6481f462d66ca27/whisper/audio.py#L22 Open an audio file and read as mono waveform, resampling as necessary, save the resampled audio Args: file (str): The audio file to open sr (int): The sample rate to resample the audio if necessary Returns: resampled_file (str): The resampled audio file """ try: # This launches a subprocess to decode audio while down-mixing and resampling as necessary. # Requires the ffmpeg CLI and `ffmpeg-python` package to be installed. out, _ = ( ffmpeg.input(file, threads=0) .output("-", format="s16le", acodec="pcm_s16le", ac=1, ar=sr) .run(cmd=["ffmpeg", "-nostdin"], capture_stdout=True, capture_stderr=True) ) except ffmpeg.Error as e: raise RuntimeError(f"Failed to load audio: {e.stderr.decode()}") from e np_buffer = np.frombuffer(out, dtype=np.int16) resampled_file = f"{file.split('.')[0]}_resampled.wav" scipy.io.wavfile.write(resampled_file, sr, np_buffer.astype(np.int16)) return resampled_file