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app.py

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+import torch
+import gradio as gr
+from pytube import YouTube
+from transformers import pipeline
+
+MODEL_NAME = "linshoufan/linshoufan-whisper-small-nan-tw-pinyin-several-datasets"
+lang = "chinese"
+
+# 根據是否有可用的 CUDA 設備來選擇設備
+device = 0 if torch.cuda.is_available() else "mps"
+
+# 初始化 pipeline，指定任務、模型和設備
+pipe = pipeline(
+    task="automatic-speech-recognition",
+    chunk_length_s=15,
+    model=MODEL_NAME,
+    device=device,
+)
+
+# 設置模型的語言和任務
+pipe.model.config.forced_decoder_ids = pipe.tokenizer.get_decoder_prompt_ids(language=lang, task="transcribe")
+
+# 定義轉錄功能
+def transcribe(microphone=None, file_upload=None):
+    warn_output = ""
+    if microphone is not None and file_upload is not None:
+        warn_output = "警告：您同時使用了麥克風與上傳音訊檔案，將只會使用麥克風錄製的檔案。\n"
+    elif microphone is None and file_upload is None:
+        return "錯誤：您必須至少使用麥克風或上傳一個音頻檔案。"
+
+    file = microphone if microphone is not None else file_upload
+    text = pipe(file)["text"]
+    return warn_output + text
+
+# 定義 YouTube 轉寫功能
+def yt_transcribe(yt_url):
+    yt = YouTube(yt_url)
+    stream = yt.streams.filter(only_audio=True).first()
+    stream.download(filename="audio.mp3")
+    text = pipe("audio.mp3")["text"]
+    # 嵌入 YouTube 影片
+    video_id = yt_url.split("?v=")[-1]
+    html_embed = f'<center><iframe width="500" height="320" src="https://www.youtube.com/embed/{video_id}"></iframe></center>'
+    
+    return html_embed, text
+
+# 初始化 Gradio Blocks
+demo = gr.Blocks()
+
+# 定義兩個介面
+mf_transcribe = gr.Interface(
+    fn=transcribe,
+    inputs=gr.Audio(label="audio",type="filepath"),
+    outputs="text",
+    title="Whisper 演示: 語音轉錄",
+    description=f"演示使用 fine-tuned checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME} 以及 🤗 Transformers 轉錄任意長度的音訊檔案",
+    allow_flagging="manual",
+)
+
+yt_transcribe = gr.Interface(
+    fn=yt_transcribe,
+    inputs=[gr.Textbox(lines=1, placeholder="在此處貼上 YouTube 影片的 URL", label="YouTube URL")],
+    outputs=["html", "text"],
+    title="Whisper 演示: Youtube轉錄",
+    description=f"演示使用 fine-tuned checkpoint [{MODEL_NAME}](https://huggingface.co/{MODEL_NAME} 以及 🤗 Transformers 轉錄任意長度的Youtube影片",
+    allow_flagging="manual",
+)
+
+# 將兩個介面加入到標籤介面中
+with demo:
+    gr.TabbedInterface([mf_transcribe, yt_transcribe], ["語音轉錄", "Youtube轉錄"])
+
+# 啟動並分享 Gradio 介面
+demo.launch(share=True)

requirements.txt

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+accelerate==0.27.2
+datasets==2.18.0
+evaluate==0.4.1
+gradio==4.20.1
+librosa==0.10.1
+pytube==15.0.0
+soundfile==0.12.1
+tensorboard==2.16.2
+transformers==4.38.2
+torch==2.2.1
+jiwer==3.0.3