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from transformers import pipeline
import gradio as gr
from pyctcdecode import BeamSearchDecoderCTC
lmID = "aware-ai/german-lowercase-5gram-kenlm"
decoder = BeamSearchDecoderCTC.load_from_hf_hub(lmID)
p = pipeline("automatic-speech-recognition", model="aware-ai/robust-wav2vec2-xls-r-300m-german-lowercase", decoder=decoder)
ttp = pipeline("text2text-generation", model="aware-ai/marian-german-grammar")
hotwords = [
"hilfe"
]
def transcribe(audio):
transcribed = p(audio, chunk_length_s=16, stride_length_s=(4, 0), hotwords = hotwords)["text"]
return transcribed
def punctuate(transcribed):
punctuated = ttp(transcribed, max_length = 512)[0]["generated_text"]
return punctuated
def get_asr_interface():
return gr.Interface(
fn=transcribe,
inputs=[
gr.inputs.Audio(source="microphone", type="filepath")
],
outputs=[
"textbox",
])
def get_punctuation_interface():
return gr.Interface(
fn=punctuate,
inputs=[
"textbox",
],
outputs=[
"textbox",
])
interfaces = [
get_asr_interface(),
get_punctuation_interface(),
]
names = [
"ASR",
"GRAMMAR",
]
gr.TabbedInterface(interfaces, names).launch(server_name = "0.0.0.0", enable_queue=False) |