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| import spaces | |
| import os, sys, logging | |
| sys.path.append("neutts-air") | |
| from neuttsair.neutts import NeuTTSAir | |
| import numpy as np | |
| import gradio as gr | |
| from groq import Groq | |
| SAMPLES_PATH = os.path.join(os.getcwd(), "neutts-air", "samples") | |
| DEFAULT_REF_TEXT = "So I'm live on radio. And I say, well, my dear friend James here clearly, and the whole room just froze. Turns out I'd completely misspoken and mentioned our other friend." | |
| DEFAULT_REF_PATH = os.path.join(SAMPLES_PATH, "dave.wav") | |
| DEFAULT_GEN_TEXT = "My name is Dave, and um, I'm from London." | |
| logging.basicConfig( | |
| level=logging.INFO, | |
| format="%(asctime)s [%(levelname)s] %(message)s", | |
| stream=sys.stdout | |
| ) | |
| tts = NeuTTSAir( | |
| backbone_repo="neuphonic/neutts-air", | |
| backbone_device="cpu", | |
| codec_repo="neuphonic/neucodec", | |
| codec_device="cpu" | |
| ) | |
| def transcribe(file_path: str): | |
| client = Groq() | |
| with open(file_path, "rb") as file: | |
| transcription = client.audio.transcriptions.create( | |
| file=(file_path, file.read()), | |
| model="whisper-large-v3-turbo", | |
| temperature=0, | |
| response_format="verbose_json", | |
| ) | |
| if len(transcription.text) <= 0: logging.warn("Error while transcripting the reference audio.") | |
| return transcription.text | |
| def infer( | |
| gen_text: str, | |
| ref_text: str = DEFAULT_REF_TEXT, | |
| ref_audio_path: str = DEFAULT_REF_PATH, | |
| ) -> tuple[int, np.ndarray]: | |
| """ | |
| Generates speech using NeuTTS-Air given a reference audio and text, and new text to synthesize. | |
| Args: | |
| gen_text (str): The new text to synthesize. | |
| ref_text (str): The text corresponding to the reference audio. | |
| ref_audio_path (str): The file path to the reference audio. | |
| Returns: | |
| tuple [int, np.ndarray]: A tuple containing the sample rate (24000) and the generated audio waveform as a numpy array. | |
| """ | |
| if gen_text is None or not len(gen_text): | |
| raise Exception("Please insert the new text to synthesize.") | |
| if ref_audio_path != DEFAULT_REF_PATH and ref_text == DEFAULT_REF_TEXT: | |
| ref_text = "" | |
| if not len(ref_text): | |
| ref_text = transcribe(ref_audio_path) | |
| logging.info(f"Using reference: {ref_audio_path}") | |
| gr.Info("Starting inference request!") | |
| gr.Info("Encoding reference...") | |
| ref_codes = tts.encode_reference(ref_audio_path) | |
| gr.Info(f"Generating audio for input text: {gen_text}") | |
| wav = tts.infer(gen_text, ref_codes, ref_text) | |
| return (24_000, wav) | |
| demo = gr.Interface( | |
| fn=infer, | |
| inputs=[ | |
| gr.Textbox(label="Text to Generate", value=DEFAULT_GEN_TEXT), | |
| gr.Textbox(label="Reference Text (Optional)", value=DEFAULT_REF_TEXT), | |
| gr.Audio(type="filepath", label="Reference Audio", value=DEFAULT_REF_PATH), | |
| ], | |
| outputs=gr.Audio(type="numpy", label="Generated Speech"), | |
| title="NeuTTS-Air☁️", | |
| description="Upload a reference audio sample, provide the reference text, and enter new text to synthesize." | |
| ) | |
| if __name__ == "__main__": | |
| demo.queue(max_size=10).launch(allowed_paths=[SAMPLES_PATH], mcp_server=False, inbrowser=True) |