diff --git a/haystack/preview/components/audio/whisper_local.py b/haystack/preview/components/audio/whisper_local.py
index 423455fd4..7d829e2db 100644
--- a/haystack/preview/components/audio/whisper_local.py
+++ b/haystack/preview/components/audio/whisper_local.py
@@ -36,12 +36,9 @@ class LocalWhisperTranscriber:
     ):
         """
         :param model_name_or_path: Name of the model to use. Set it to one of the following values:
-            - `tiny`
-            - `small`
-            - `medium`
-            - `large`
-            - `large-v2`
+        :type model_name_or_path: Literal["tiny", "small", "medium", "large", "large-v2"]
         :param device: Name of the torch device to use for inference. If None, CPU is used.
+        :type device: Optional[str]
         """
         whisper_import.check()
         if model_name_or_path not in get_args(WhisperLocalModel):
@@ -78,8 +75,8 @@ class LocalWhisperTranscriber:
         [Whisper API documentation](https://platform.openai.com/docs/guides/speech-to-text) and the official Whisper
         [github repo](https://github.com/openai/whisper).
 
-        :param audio_files: a list of paths or binary streams to transcribe
-        :returns: a list of Documents, one for each file. The content of the document is the transcription text,
+        :param audio_files: A list of paths or binary streams to transcribe.
+        :returns: A list of Documents, one for each file. The content of the document is the transcription text,
             while the document's metadata contains all the other values returned by the Whisper model, such as the
             alignment data. Another key called `audio_file` contains the path to the audio file used for the
             transcription.
@@ -101,8 +98,8 @@ class LocalWhisperTranscriber:
         [Whisper API documentation](https://platform.openai.com/docs/guides/speech-to-text) and the official Whisper
         [github repo](https://github.com/openai/whisper).
 
-        :param audio_files: a list of paths or binary streams to transcribe
-        :returns: a list of Documents, one for each file. The content of the document is the transcription text,
+        :param audio_files: A list of paths or binary streams to transcribe.
+        :returns: A list of Documents, one for each file. The content of the document is the transcription text,
             while the document's metadata contains all the other values returned by the Whisper model, such as the
             alignment data. Another key called `audio_file` contains the path to the audio file used for the
             transcription.
@@ -125,8 +122,8 @@ class LocalWhisperTranscriber:
         [Whisper API documentation](https://platform.openai.com/docs/guides/speech-to-text) and the official Whisper
         [github repo](https://github.com/openai/whisper).
 
-        :param audio_files: a list of paths or binary streams to transcribe
-        :returns: a list of transcriptions.
+        :param audio_files: A list of paths or binary streams to transcribe.
+        :returns: A list of transcriptions.
         """
         return_segments = kwargs.pop("return_segments", False)
         transcriptions = []