import tempfile from typing import Optional import gradio as gr import numpy as np from TTS.api import TTS from huggingface_hub import snapshot_download MAX_TXT_LEN = 100 snapshot_download(repo_id="DigitalUmuganda/Kinyarwanda_YourTTS",revision="main") def generate_audio(text): if len(text) > MAX_TXT_LEN: text = text[:MAX_TXT_LEN] print(f"Input text was cutoff since it went over the {MAX_TXT_LEN} character limit.") # model_path, config_path, model_item = manager.download_model(model_name) # vocoder_name: Optional[str] = model_item["default_vocoder"] # vocoder_path = None # vocoder_config_path = None # if vocoder_name is not None: # vocoder_path, vocoder_config_path, _ = manager.download_model(vocoder_name) # synthesizer = Synthesizer( # model_path, config_path, None, None, vocoder_path, vocoder_config_path, # ) # if synthesizer is None: # raise NameError("model not found") tts = TTS(model_path="Kinyarwanda_YourTTS/model.pth", config_path="Kinyarwanda_YourTTS/config.json", tts_speakers_file="Kinyarwanda_YourTTS/speakers.pth", encoder_checkpoint="Kinyarwanda_YourTTS/SE_checkpoint.pth.tar", encoder_config="Kinyarwanda_YourTTS/config_se.json",) wav = tts.tts(text, speaker_wav="kinyarwanda_YourTTS/conditioning_audio.wav") return wav # with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as fp: # synthesizer.save_wav(wav, fp) # return fp.name iface = gr.Interface( fn=generate_audio, inputs=[ gr.inputs.Textbox( label="Input Text", default="This sentence has been generated by a speech synthesis system.", ), ], outputs=gr.outputs.Audio(type="numpy",label="Output"), title="Kinyarwanda tts Demo", description="Kinyarwanda tts build with ", allow_flagging=False, flagging_options=['error', 'bad-quality', 'wrong-pronounciation'], layout="vertical", live=False ) iface.launch(share=False)