Generate Audio from Text Scripts using Self-Hosted Bark Model and Google Drive

Audio Generator – Documentation

🎯 Purpose: Generate audio files from text scripts stored in Google Drive.

🔁 Flow: Receive repo IDs. Fetch text scripts. Generate .wav files using local Bark model. Upload back to Drive.

📦 Dependencies: Python script: /scripts/generate_voice.py Bark (voice generation system) n8n instance with access to local shell Google Drive OAuth2 credentials

✏️ Notes: Script filenames must end with .txt Only works with plain text No external API used = 100% free

📦 /scripts/generate_voice.py: import sys import torch import numpy import re from bark import SAMPLE_RATE, generate_audio, preload_models from scipy.io.wavfile import write as write_wav

Patch to allow numpy._core.multiarray.scalar during loading torch.serialization.add_safe_globals([numpy._core.multiarray.scalar])

Monkey patch torch.load to force weights_only=False _original_torch_load = torch.load def patched_torch_load(f, args, *kwargs): if 'weights_only' not in kwargs: kwargs['weights_only'] = False return _original_torch_load(f, args, *kwargs) torch.load = patched_torch_load

Preload Bark models preload_models()

def split_text(text, max_len=300): Split on punctuation to avoid mid-sentence cuts sentences = re.split(r'(?<=[.?!])\s+', text) chunks = [] current = "" for sentence in sentences: if len(current) + len(sentence) < max_len: current += sentence + " " else: chunks.append(current.strip()) current = sentence + " " if current: chunks.append(current.strip()) return chunks

Input text file and output path input_text_path = sys.argv[1] output_wav_path = sys.argv[2]

with open(input_text_path, 'r', encoding='utf-8') as f: full_text = f.read()

voice_preset = "v2/en_speaker_7"

chunks = split_text(full_text)

Generate and concatenate audio chunks audio_arrays = [] for chunk in chunks: print(f"Generating audio for chunk: {chunk[:50]}...") audio = generate_audio(chunk, history_prompt=voice_preset) audio_arrays.append(audio)

Merge all audio chunks final_audio = numpy.concatenate(audio_arrays)

Write final .wav file write_wav(output_wav_path, SAMPLE_RATE, final_audio)

print(f"Full audio generated at: {output_wav_path}") `