diff --git a/autotranscript/transcriber.py b/autotranscript/transcriber.py
new file mode 100644
index 0000000..a3927f1
--- /dev/null
+++ b/autotranscript/transcriber.py
@@ -0,0 +1,112 @@
+
+import os
+from typing import TypeVar
+from whisper import load_model
+from glob import glob
+
+whisper = TypeVar('whisper') 
+Transcriber = TypeVar('Transcriber')
+
+def get_whisper_default_path() -> str:
+    """
+    Get default path for whisper models
+
+    Returns
+    -------
+    str
+        path
+    """
+    _path = os.path.dirname(os.path.dirname(__file__))
+    return os.path.join(_path, "models", "whisper")
+
+WHISPER_DEFAULT_PATH = get_whisper_default_path()
+
+class Transcriber:
+    def __init__(self, model: whisper ) -> None:
+        """
+        Initialize Transcriber class with a whisper model
+        :param model: whisper model
+        """
+        self.model = model
+
+
+    def transcribe(self, file : str, language:str = "German"):
+        """
+        transcribe audio file
+        :param file: audio file to transcribe
+        :param language: language of the audio file
+        :return: transcript as string
+        """
+        result = self.model.transcribe(file, language = language)
+
+        return result["text"]
+    
+    @staticmethod
+    def save_transcript(transcript:str , save_path : str) -> None:
+        """
+        Save transcript to file
+        :param transcript: transcript as string
+        :param savepath: path to save the transcript
+        :return: None
+        """
+
+        with open(save_path, 'w') as f:
+            f.write(transcript)
+            f.close()
+            
+        print(f'Transcript saved to {save_path}')
+
+    @classmethod
+    def load_whisper_model(cls,
+                            model: str = "medium", 
+                            local : bool = True,
+                            download_root: str = WHISPER_DEFAULT_PATH) -> Transcriber:
+        """
+        Load whisper module
+
+        Parameters
+        ----------
+        whisper : str
+            whisper model
+            available models:
+
+                - 'tiny.en'
+                - 'tiny'
+                - 'base.en'
+                - 'base'
+                - 'small.en'
+                - 'small'
+                - 'medium.en'
+                - 'medium'
+                - 'large-v1'
+                - 'large-v2'
+                - 'large' 
+
+        local : bool
+            If true, load from local cache
+
+        download_root : str
+            Path to download the model
+
+            default: /models/whisper
+        
+        Returns
+        -------
+        Whisper Object
+        """
+
+        if local:
+            
+            available_models = [os.path.basename(x) for x in glob(os.path.join(download_root, "*"))]
+            
+            for i, module in enumerate(available_models):
+                available_models[i] = module.split(".")[0]
+            
+            if model not in available_models:
+                raise RuntimeError("Model not found. Consider downloading the "/
+                                   "model first. By deactivating the local flag, " /
+                                    "the model will be downloaded automatically.")
+
+        _model = load_model(model, download_root=download_root)
+
+        return cls(_model)