diff --git a/app/backend/InputOutputHandler.tsx b/app/backend/InputOutputHandler.tsx
index 381ef88..36b3fac 100644
--- a/app/backend/InputOutputHandler.tsx
+++ b/app/backend/InputOutputHandler.tsx
@@ -151,7 +151,7 @@ const InputOutputBackend: React.FC = () => {
     }
         
     mediaRecorder.onstop = () => {
-      const audioBlob = new Blob(audioChunks.current, { type: "audio/ogg" })
+      const audioBlob = new Blob(audioChunks.current, { type: "audio/wav" })
       const url = URL.createObjectURL(audioBlob)
       console.log(url);
       setAudioURL(url)
diff --git a/app/backend/voice_backend.ts b/app/backend/voice_backend.ts
index 3c4193b..a93fd89 100644
--- a/app/backend/voice_backend.ts
+++ b/app/backend/voice_backend.ts
@@ -4,9 +4,13 @@ import axios from "axios";
 class VoiceSend {
     sendToVoiceRecognition(audio_data: Blob) {
         console.log("sending recording...");
+        console.log(typeof (audio_data));
+        console.log(audio_data instanceof Blob);
 
         const formdata = new FormData()
         formdata.append("audio", audio_data)
+        formdata.append("option", "offline")
+        formdata.append("type", "basic")
 
         const dataSend = { option:"offline", type:"basic",audio:audio_data }
         axios.post("http://localhost:5000/interstellar_ai/api/voice_recognition", formdata)
diff --git a/py/requirements.txt b/py/requirements.txt
index 212a41d..7ea1a85 100644
--- a/py/requirements.txt
+++ b/py/requirements.txt
@@ -14,5 +14,4 @@ pycouchdb
 pyttsx3
 pip-licenses
 openai-whisper
-pydub
-ffmpeg
\ No newline at end of file
+pydub
\ No newline at end of file
diff --git a/py/voice.py b/py/voice.py
index cd0d657..b4516f0 100644
--- a/py/voice.py
+++ b/py/voice.py
@@ -1,24 +1,10 @@
-import io
-import numpy as np
 import whisper
-from pydub import AudioSegment
 
 
 class VoiceRecognition:
     @staticmethod
     def recognition(audio):
-        audio_data = audio.read()
-        with io.BytesIO(audio_data) as audio_buffer:
-            audio_segment = AudioSegment.from_ogg(audio_buffer)
-            
-            raw_data = np.array(audio_segment.get_array_of_samples())
-            
-            if audio_segment.channels > 1:
-                raw_data = raw_data.reshape((-1, audio_segment.channels))[:, 0]
-            
-            audio_data = raw_data.astype(np.float32) / (2 ** (audio_segment.sample_width * 8 - 1))
-        
         model = whisper.load_model("base")
-        result = model.transcribe(audio_data)
+        result = model.transcribe(audio)
         print(result["text"])
         return result["text"]