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import gradio as gr
import whisper
from transformers import MarianMTModel, MarianTokenizer
from gtts import gTTS
from io import BytesIO
# Load Whisper ASR model
whisper_model = whisper.load_model("small") # Use a smaller model
# Load translation models for Hausa-English and English-Hausa
model_name_he = 'Helsinki-NLP/opus-mt-ha-en' # Hausa to English
model_name_eh = 'Helsinki-NLP/opus-mt-en-ha' # English to Hausa
tokenizer_he = MarianTokenizer.from_pretrained(model_name_he)
model_he = MarianMTModel.from_pretrained(model_name_he)
tokenizer_eh = MarianTokenizer.from_pretrained(model_name_eh)
model_eh = MarianMTModel.from_pretrained(model_name_eh)
# Function to punctuate (simple punctuation for demo)
def punctuate(text):
if text[-1] not in '.!?':
text += '.'
return text.capitalize()
# Function to translate and punctuate
def translate_and_punctuate(text, direction):
if direction == "Hausa to English":
translated = model_he.generate(**tokenizer_he(text, return_tensors="pt", padding=True))
result = tokenizer_he.decode(translated[0], skip_special_tokens=True)
else:
translated = model_eh.generate(**tokenizer_eh(text, return_tensors="pt", padding=True))
result = tokenizer_eh.decode(translated[0], skip_special_tokens=True)
return punctuate(result)
# Text-to-speech function
def text_to_speech(text, language):
tts = gTTS(text=text, lang=language)
audio_fp = BytesIO()
tts.save(audio_fp)
audio_fp.seek(0)
return audio_fp
# Real-time translation function
def real_time_translation(audio, direction):
# Use Whisper model to transcribe the audio (speech to text)
result = whisper_model.transcribe(audio)
spoken_text = result['text']
# Translate and punctuate the transcribed text
translated_text = translate_and_punctuate(spoken_text, direction)
# Generate speech output from the translated text
if direction == "Hausa to English":
speech_output = text_to_speech(translated_text, "en")
else:
speech_output = text_to_speech(translated_text, "ha")
return translated_text, speech_output
# Gradio interface
def translation_app(audio, direction):
# Handle real-time translation from audio input
translated_text, speech_output = real_time_translation(audio, direction)
return translated_text, speech_output
# Define Gradio inputs and outputs
inputs = [
gr.Audio(type="filepath", label="Speak Now"),
gr.Radio(choices=["Hausa to English", "English to Hausa"], label="Translation Direction")
]
outputs = [
gr.Textbox(label="Translated and Punctuated Text"),
gr.Audio(label="Translated Speech")
]
# Launch Gradio app
gr.Interface(fn=translation_app, inputs=inputs, outputs=outputs, title="Real-Time Hausa-English Speech Translator with Whisper").launch()
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