Spaces:
Build error
Build error
import os | |
import gradio as gr | |
import torch | |
import soundfile as sf | |
from transformers import Wav2Vec2Processor, Wav2Vec2ForCTC | |
import librosa | |
from TTS.api import TTS | |
from TTS.utils.manage import ModelManager | |
# Agreeing to Coqui TTS terms of service and setting up environment variables | |
os.environ["COQUI_TOS_AGREED"] = "1" | |
os.makedirs("output_audio", exist_ok=True) | |
# Initialize ASR model | |
asr_processor = Wav2Vec2Processor.from_pretrained("facebook/wav2vec2-large-960h") | |
asr_model = Wav2Vec2ForCTC.from_pretrained("facebook/wav2vec2-large-960h") | |
asr_model.eval() | |
# Dynamically list and select TTS model | |
tts_manager = ModelManager() | |
model_name = "tts_models/multilingual/multi-dataset/xtts_v2" | |
tts = TTS(model_name, gpu=False) | |
def resample_audio(input_audio_path, target_sr=16000): | |
waveform, sr = sf.read(input_audio_path) | |
if sr != target_sr: | |
waveform = librosa.resample(waveform, orig_sr=sr, target_sr=target_sr) | |
return waveform | |
def speech_to_text(input_audio_path): | |
waveform = resample_audio(input_audio_path) | |
input_values = asr_processor(waveform, return_tensors="pt").input_values | |
with torch.no_grad(): | |
logits = asr_model(input_values).logits | |
predicted_ids = torch.argmax(logits, dim=-1) | |
transcription = asr_processor.batch_decode(predicted_ids)[0] | |
return transcription.strip() | |
def text_to_speech(text, speaker_wav_path, output_path="output_audio/output.wav"): | |
if not text.strip(): | |
return "Empty text input." | |
tts.tts_to_file(text=text, file_path=output_path, speaker_wav=speaker_wav_path) | |
return output_path | |
def speech_to_speech(input_audio, text_input=None): | |
speaker_wav_path = input_audio | |
if text_input is None: | |
text_input = speech_to_text(input_audio) | |
return text_to_speech(text_input, speaker_wav_path) | |
iface = gr.Interface(fn=speech_to_speech, | |
inputs=[gr.Audio(type="filepath"), gr.Textbox(optional=True)], | |
outputs=gr.Audio()) | |
iface.launch() | |