Adarsh1967 commited on
Commit
8380b47
Β·
verified Β·
1 Parent(s): 0cc53c9

Create app.py

Browse files
Files changed (1) hide show
  1. app.py +51 -0
app.py ADDED
@@ -0,0 +1,51 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ import gradio as gr
2
+ from transformers import pipeline, MBartForConditionalGeneration, MBart50TokenizerFast
3
+
4
+ # Load ASR model
5
+ asr = pipeline("automatic-speech-recognition", model="Subu19/whisper-small-nepali")
6
+
7
+ # Load translation model
8
+ model = MBartForConditionalGeneration.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
9
+ tokenizer = MBart50TokenizerFast.from_pretrained("facebook/mbart-large-50-many-to-many-mmt")
10
+
11
+ def translate_nepali_to_english(text):
12
+ tokenizer.src_lang = "ne_NP"
13
+ encoded = tokenizer(text, return_tensors="pt")
14
+ generated = model.generate(**encoded, forced_bos_token_id=tokenizer.lang_code_to_id["en_XX"])
15
+ return tokenizer.batch_decode(generated, skip_special_tokens=True)[0]
16
+
17
+ def translate_english_to_nepali(text):
18
+ tokenizer.src_lang = "en_XX"
19
+ encoded = tokenizer(text, return_tensors="pt")
20
+ generated = model.generate(**encoded, forced_bos_token_id=tokenizer.lang_code_to_id["ne_NP"])
21
+ return tokenizer.batch_decode(generated, skip_special_tokens=True)[0]
22
+
23
+ # Load summarizer
24
+ summarizer = pipeline("summarization")
25
+
26
+ def summarize_text(text):
27
+ word_count = len(text.split())
28
+ if word_count < 25:
29
+ return text
30
+ summary = summarizer(text, max_length=word_count, min_length=int(word_count * 0.4), do_sample=False)
31
+ return summary[0]['summary_text']
32
+
33
+ def pipeline_fn(audio):
34
+ result = asr(audio)["text"]
35
+ english = translate_nepali_to_english(result)
36
+ summary = summarize_text(english)
37
+ nepali_summary = translate_english_to_nepali(summary)
38
+ return result, english, summary, nepali_summary
39
+
40
+ gr.Interface(
41
+ fn=pipeline_fn,
42
+ inputs=gr.Audio(source="microphone", type="filepath", label="🎀 Speak Nepali"),
43
+ outputs=[
44
+ gr.Textbox(label="πŸ—£οΈ Transcribed Nepali"),
45
+ gr.Textbox(label="πŸ“˜ Translated English"),
46
+ gr.Textbox(label="πŸ“ English Summary"),
47
+ gr.Textbox(label="πŸ” Summarized Nepali"),
48
+ ],
49
+ title="Nepali Voice Summarizer",
50
+ description="Speak Nepali β†’ Get English & Nepali Summary"
51
+ ).launch()