Spaces:
Runtime error
Runtime error
File size: 1,592 Bytes
f725323 |
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 |
from transformers import pipeline
import gradio as gr
import time
p = pipeline("automatic-speech-recognition",model="jonatasgrosman/wav2vec2-large-xlsr-53-spanish")
pc = pipeline("automatic-speech-recognition",model="softcatala/wav2vec2-large-xlsr-catala")
pe = pipeline("automatic-speech-recognition",model="jonatasgrosman/wav2vec2-large-xlsr-53-english")
def transcribe(language,audio, state=""):#language="Spanish",
time.sleep(2)
if language=="Spanish":
state=""
text = p(audio)["text"]
if language=="Catalan":
state=""
text = pc(audio)["text"]
if language=="English":
state=""
text = pe(audio)["text"]
state += text + " "
#text2="Esto es loq ue te he entendido"
return state, state
demo=gr.Interface(
fn=transcribe,
title="TEDCAS Offline Speech recognition",
description="1)Select language 2)Click on 'record from microphone' and talk 3)Click on 'stop recording' 4)Click on submit 5)Before starting again, click on 'clear'",
inputs=[
gr.Dropdown(["Spanish","Catalan","English"]),
#gr.Audio(source="microphone", type="filepath", streaming=True),
gr.inputs.Audio(source="microphone", type="filepath"),
"state"#,"language"
],
outputs=[
"textbox",
"state"
],
#live=True).launch()
)
demo.launch()
#gr.Interface(
# fn=transcribe,
# inputs=[
# gr.inputs.Audio(source="microphone", type="filepath"),
# "state"
# ],
# outputs=[
# "textbox",
# "state"
# ],
# live=True).launch()
|