import sys import os,stat import subprocess import random from zipfile import ZipFile import uuid # By using XTTS you agree to CPML license https://coqui.ai/cpml os.environ["COQUI_TOS_AGREED"] = "1" # langid is used to detect language for longer text # Most users expect text to be their own language, there is checkbox to disable it import langid import gradio as gr from TTS.api import TTS from TTS.tts.configs.xtts_config import XttsConfig from TTS.tts.models.xtts import Xtts from TTS.utils.generic_utils import get_user_data_dir HF_TOKEN = os.environ.get("HF_TOKEN") from huggingface_hub import HfApi # will use api to restart space on a unrecoverable error api = HfApi(token=HF_TOKEN) repo_id = "coqui/xtts" # Use never ffmpeg binary for Ubuntu20 to use denoising for microphone input print("Export newer ffmpeg binary for denoise filter") ZipFile("ffmpeg.zip").extractall() print("Make ffmpeg binary executable") st = os.stat('ffmpeg') os.chmod('ffmpeg', st.st_mode | stat.S_IEXEC) # Load TTS from TTS.utils.manage import ModelManager import torch model_name = "tts_models/multilingual/multi-dataset/xtts_v2" ModelManager().download_model(model_name) model_path = os.path.join(get_user_data_dir("tts"), model_name.replace("/", "--")) print("XTTS downloaded") tts = TTS(model_name) if torch.cuda.is_available(): tts.to("cuda") else: tts.to("cpu") # This is for debugging purposes only DEVICE_ASSERT_DETECTED=0 DEVICE_ASSERT_PROMPT=None DEVICE_ASSERT_LANG=None def predict(prompt, language, audio_file_pth, mic_file_path, use_mic, voice_cleanup, no_lang_auto_detect, agree,): if agree == True: supported_languages=["en","es","fr","de","it","pt","pl","tr","ru","nl","cs","ar","zh-cn","ja","ko","hu"] if language not in supported_languages: gr.Warning("Language you put in is not in is not in our Supported Languages, please choose from dropdown") return ( None, None, None, ) language_predicted=langid.classify(prompt)[0].strip() # strip need as there is space at end! # tts expects chinese as zh-cn if language_predicted == "zh": #we use zh-cn language_predicted = "zh-cn" print(f"Detected language:{language_predicted}, Chosen language:{language}") # After text character length 15 trigger language detection if len(prompt)>15: # allow any language for short text as some may be common # If user unchecks language autodetection it will not trigger # You may remove this completely for own use if language_predicted != language and not no_lang_auto_detect: #Please duplicate and remove this check if you really want this #Or auto-detector fails to identify language (which it can on pretty short text or mixed text) gr.Warning(f"It looks like your text isn’t the language you chose , if you’re sure the text is the same language you chose, please check disable language auto-detection checkbox" ) return ( None, None, None, ) if use_mic == True: if mic_file_path is not None: speaker_wav=mic_file_path else: gr.Warning("Please record your voice with Microphone, or uncheck Use Microphone to use reference audios") return ( None, None, None, ) else: speaker_wav=audio_file_pth # Filtering for microphone input, as it has BG noise, maybe silence in beginning and end # This is fast filtering not perfect # Apply all on demand lowpassfilter=denoise=trim=loudness=True if lowpassfilter: lowpass_highpass="lowpass=8000,highpass=75," else: lowpass_highpass="" if trim: # better to remove silence in beginning and end for microphone trim_silence="areverse,silenceremove=start_periods=1:start_silence=0:start_threshold=0.02,areverse,silenceremove=start_periods=1:start_silence=0:start_threshold=0.02," else: trim_silence="" if (voice_cleanup): try: out_filename = speaker_wav + str(uuid.uuid4()) + ".wav" #ffmpeg to know output format #we will use newer ffmpeg as that has afftn denoise filter shell_command = f"./ffmpeg -y -i {speaker_wav} -af {lowpass_highpass}{trim_silence} {out_filename}".split(" ") command_result = subprocess.run([item for item in shell_command], capture_output=False,text=True, check=True) speaker_wav=out_filename print("Filtered microphone input") except subprocess.CalledProcessError: # There was an error - command exited with non-zero code print("Error: failed filtering, use original microphone input") else: speaker_wav=speaker_wav if len(prompt)<2: gr.Warning("Please give a longer prompt text") return ( None, None, None, ) if len(prompt)>200: gr.Warning("Text length limited to 200 characters for this demo, please try shorter text. You can clone this space and edit code for your own usage") return ( None, None, None, ) global DEVICE_ASSERT_DETECTED if DEVICE_ASSERT_DETECTED: global DEVICE_ASSERT_PROMPT global DEVICE_ASSERT_LANG #It will likely never come here as we restart space on first unrecoverable error now print(f"Unrecoverable exception caused by language:{DEVICE_ASSERT_LANG} prompt:{DEVICE_ASSERT_PROMPT}") try: tts.tts_to_file( text=prompt, file_path="output.wav", language=language, speaker_wav=speaker_wav, ) except RuntimeError as e : if "device-side assert" in str(e): # cannot do anything on cuda device side error, need tor estart print(f"Exit due to: Unrecoverable exception caused by language:{language} prompt:{prompt}", flush=True) gr.Warning("Unhandled Exception encounter, please retry in a minute") print("Cuda device-assert Runtime encountered need restart") if not DEVICE_ASSERT_DETECTED: DEVICE_ASSERT_DETECTED=1 DEVICE_ASSERT_PROMPT=prompt DEVICE_ASSERT_LANG=language # HF Space specific.. This error is unrecoverable need to restart space api.restart_space(repo_id=repo_id) else: print("RuntimeError: non device-side assert error:", str(e)) raise e return ( gr.make_waveform( audio="output.wav", ), "output.wav", speaker_wav, ) else: gr.Warning("Please accept the Terms & Condition!") return ( None, None, None, ) title = "🐸 XTTSv2 - 3秒语音合成,支持中英双语,告别电音!" description = f""" ##
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