Spaces:
Runtime error
Runtime error
File size: 2,548 Bytes
b8b135b c2110e8 14c0ec2 e559d03 b8b135b e559d03 8549c9b e559d03 77fc3c3 e559d03 77fc3c3 accb4e2 77fc3c3 accb4e2 77fc3c3 c2110e8 accb4e2 14c0ec2 accb4e2 77fc3c3 89c0d34 accb4e2 89c0d34 14c0ec2 accb4e2 14c0ec2 be35c90 14c0ec2 accb4e2 251ab2e e891b09 14c0ec2 c1335fa 89c0d34 |
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 |
import gradio as gr
import torch
from icon import generate_icon
from transformers import pipeline
from timestamp import format_timestamp
MODEL_NAME = "openai/whisper-medium"
BATCH_SIZE = 8
device = 0 if torch.cuda.is_available() else "cpu"
pipe = pipeline(
task="automatic-speech-recognition",
model=MODEL_NAME,
chunk_length_s=30,
device=device,
)
def transcribe(file, task, return_timestamps):
outputs = pipe(file, batch_size=BATCH_SIZE, generate_kwargs={"task": task}, return_timestamps=True)
text = outputs["text"]
timestamps = outputs["chunks"]
if return_timestamps==True:
timestamps = [f"[{format_timestamp(chunk['timestamp'][0])} -> {format_timestamp(chunk['timestamp'][1])}] {chunk['text']}" for chunk in timestamps]
else:
timestamps = [f"{chunk['text']}" for chunk in timestamps]
text = "<br>".join(str(feature) for feature in timestamps)
text = f"<h4>Transcription</h4><div style='overflow-y: scroll; height: 250px;'>{text}</div>"
return file, text
inputs = [gr.Audio(source="upload", label="Audio file", type="filepath"),
gr.Radio(["transcribe"], label="Task", value="transcribe"),
gr.Checkbox(value=True, label="Return timestamps")]
outputs = [gr.Audio(label="Processed Audio", type="filepath"),
gr.outputs.HTML("text")]
title = "Whisper Demo: Transcribe Audio"
MODEL_NAME1 = "jpdiazpardo/whisper-tiny-metal"
description = ("Transcribe long-form audio inputs with the click of a button! Demo uses the"
f" checkpoint [{MODEL_NAME1}](https://huggingface.co/{MODEL_NAME1}) and 🤗 Transformers to transcribe audio files"
" of arbitrary length. Check some of the 'cool' examples below")
examples = [["When a Demon Defiles a Witch.wav","transcribe",True]]
linkedin = generate_icon("linkedin")
github = generate_icon("github")
article = ("<div style='text-align: center; max-width:800px; margin:10px auto;'>"
f"<p>{linkedin} <a href='https://www.linkedin.com/in/juanpablodiazp/' target='_blank'>Juan Pablo Díaz Pardo</a><br>"
f"{github} <a href='https://github.com/jpdiazpardo' target='_blank'>jpdiazpardo</a></p>"
)
title = "Scream: Fine-Tuned Whisper model for automatic gutural speech recognition 🤟🤟🤟"
demo = gr.Interface(title = title, fn=transcribe, inputs = inputs, outputs = outputs, description=description, cache_examples=True,
allow_flagging="never", article = article , examples=examples)
demo.queue(concurrency_count=3)
demo.launch(debug = True) |