Update app.py

app.py

@@ -11,9 +11,9 @@ whisper_model = whisper.load_model("base")
 tokenizer = AutoTokenizer.from_pretrained("alirezamsh/small100")
 model = AutoModelForSeq2SeqLM.from_pretrained("alirezamsh/small100")
 
-def translate_speech(audio):
-    audio = audio[0]
-    audio = whisper.pad_or_trim(audio)
+def translate_speech(audio, target_lang):
+    audio = audio.astype("float32")
+    audio = whisper.pad_or_trim(audio, whisper_model.audio_config.sample_rate)
     mel = whisper.log_mel_spectrogram(audio).to(whisper_model.device)
     _, probs = whisper_model.detect_language(mel)
     options = whisper.DecodingOptions(fp16=False)
@@ -21,26 +21,30 @@ def translate_speech(audio):
     text = result.text
 
     # Translate text
-    tokenizer.src_lang = 'en'  # Assuming the input is always in English
+    tokenizer.src_lang = target_lang  # Assuming the input is always in English
     encoded_text = tokenizer(text, return_tensors="pt")
     generated_tokens = model.generate(**encoded_text)
     translated_text = tokenizer.batch_decode(generated_tokens, skip_special_tokens=True)[0]
 
     # Text-to-speech (TTS)
-    tts = gTTS(text=translated_text, lang='en')  # Assuming the target language is English
+    tts = gTTS(text=translated_text, lang=target_lang)
     audio_path = "translated_audio.mp3"
     tts.save(audio_path)
 
     return audio_path
 
-def translate_speech_interface(audio):
-    translated_audio = translate_speech(audio)
+def translate_speech_interface(audio, target_lang):
+    translated_audio = translate_speech(audio, target_lang)
     translated_audio_bytes = open(translated_audio, "rb").read()
 
     return translated_audio_bytes
 
 audio_recording = gr.inputs.Audio(source="microphone", type="numpy", label="Record your speech")
+lang_choices = ["ru", "fr", "en", "de"]
+lang_dropdown = gr.inputs.Dropdown(lang_choices, label="Select Language to Translate")
 output_audio = gr.outputs.Audio(type="numpy", label="Translated Audio")
 
-iface = gr.Interface(fn=translate_speech_interface, inputs=audio_recording, outputs=output_audio, title="Speech Translator")
+iface = gr.Interface(fn=translate_speech_interface, inputs=[audio_recording, lang_dropdown], outputs=output_audio, title="Speech Translator")
 iface.launch()
+
+