Delete app.py

app.py

@@ -1,79 +0,0 @@
-import gradio as gr
-import numpy as np
-import torch
-from datasets import load_dataset
-from deep_translator import GoogleTranslator
-from transformers import (
-    AutoTokenizer,
-    SpeechT5ForTextToSpeech,
-    SpeechT5HifiGan,
-    SpeechT5Processor,
-    VitsModel,
-    pipeline,
-)
-
-# device = "cuda:0" if torch.cuda.is_available() else "cpu"
-
-device = "cpu"
-# load speech translation checkpoint
-asr_pipe = pipeline("automatic-speech-recognition",
-                    model="openai/whisper-base", device=device)
-
-# load text-to-speech mms-tts-id model (speaker embeddings included)
-model = VitsModel.from_pretrained("facebook/mms-tts-tel")
-tokenizer = AutoTokenizer.from_pretrained("facebook/mms-tts-tel")
-
-
-def translate(audio):
-    outputs = asr_pipe(audio, max_new_tokens=256,
-                       generate_kwargs={"task": "translate"})
-    return outputs["text"]
-
-
-def synthesise(text):
-    inputs = tokenizer(text=text, return_tensors="pt")
-    with torch.no_grad():
-        speech = model(**inputs).waveform
-    return speech.reshape(-1, 1).cpu()
-
-
-def speech_to_speech_translation(audio):
-    translated_text = translate(audio)
-    google_translated = GoogleTranslator(
-        source="en", target="tel").translate(translated_text)
-    synthesised_speech = synthesise(google_translated)
-    synthesised_speech = (synthesised_speech.numpy() * 32767).astype(np.int16)
-    return 16000, synthesised_speech
-
-
-title = "Cascaded STST"
-description = """
-Demo for cascaded speech-to-speech translation (STST), mapping from source speech in any language to target speech in Indonesian. Demo uses OpenAI's [Whisper Base](https://huggingface.co/openai/whisper-base) model for speech transcription, [Deep Translator](https://github.com/nidhaloff/deep-translator) for translation, and Meta's
-[MMS TTS IND](https://huggingface.co/facebook/mms-tts-ind) model for text-to-speech:
-![Cascaded STST](https://huggingface.co/datasets/huggingface-course/audio-course-images/resolve/main/s2st_cascaded.png "Diagram of cascaded speech to speech translation")
-"""
-
-demo = gr.Blocks()
-
-mic_translate = gr.Interface(
-    fn=speech_to_speech_translation,
-    inputs=gr.Audio(sources="microphone", type="filepath"),
-    outputs=gr.Audio(label="Generated Speech", type="numpy"),
-    title=title,
-    description=description,
-)
-
-file_translate = gr.Interface(
-    fn=speech_to_speech_translation,
-    inputs=gr.Audio(sources="upload", type="filepath"),
-    outputs=gr.Audio(label="Generated Speech", type="numpy"),
-    examples=[["./example.wav"]],
-    title=title,
-    description=description,
-)
-
-with demo:
-    gr.TabbedInterface([mic_translate, file_translate],
-                       ["Microphone", "Audio File"])
-
-demo.launch()