⚰️ Remove unused functions

src/engines/TTSEngine/BaseTTSEngine.py

@@ -16,48 +16,9 @@ class Word(TypedDict):
 
 class BaseTTSEngine(BaseEngine):
     @abstractmethod
-    def synthesize(self, text: str, path: str) -> None:
+    def synthesize(self, text: str, path: str) -> float:
         pass
 
-    def remove_punctuation(self, text: str) -> str:
-        return text.translate(str.maketrans("", "", ".,!?;:"))
-
-    def time_with_whisper(self, path: str) -> list[Word]:
-        """
-        Transcribes the audio file at the given path using a pre-trained model and returns a list of words.
-
-        Args:
-            path (str): The path to the audio file.
-
-        Returns:
-            list[Word]: A list of Word objects representing the transcribed words.
-            Example:
-            ```json
-            [
-                {
-                    "start": "0.00",
-                    "end": "0.50",
-                    "text": "Hello"
-                },
-                {
-                    "start": "0.50",
-                    "end": "1.00",
-                    "text": "world"
-                }
-            ]
-            ```
-        """
-        device = "cuda" if is_available() else "cpu"
-        audio = wt.load_audio(path)
-        model = wt.load_model("large-v3", device=device)
-
-        result = wt.transcribe(model=model, audio=audio)
-        results = [word for chunk in result["segments"] for word in chunk["words"]]
-        for result in results:
-            # Not needed for the current use case
-            del result["confidence"]
-        return results
-
     def force_duration(self, duration: float, path: str):
         """
         Forces the audio clip at the given path to have the specified duration.