File size: 2,643 Bytes
1070d85 f77c621 1070d85 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 |
import torch
import gradio as gr
from pytube import YouTube
from transformers import pipeline
MODEL_NAME = "yuweiiizz/whisper-small-taiwanese"
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 "cpu"
# 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)
|