Clean unused methods and incorrect arg doc

src/diart/argdoc.py

@@ -15,4 +15,4 @@
 OUTPUT = "Directory to store the system's output in RTTM format"
 HF_TOKEN = "Huggingface authentication token for hosted models ('true' | 'false' | <token>). If 'true', it will use the token from huggingface-cli login"
 SAMPLE_RATE = "Sample rate of the audio stream"
-NORMALIZE_EMBEDDING_WEIGHTS = "Rescale embedding weights (min-max normalization) to be in the range [0, 1]. This is useful in some models without weighted statistics pooling that rely on masking, like WeSpeaker or ECAPA-TDNN"
+NORMALIZE_EMBEDDING_WEIGHTS = "Rescale embedding weights (min-max normalization) to be in the range [0, 1]. This is useful in some models without weighted statistics pooling that rely on masking, like Nvidia's NeMo or ECAPA-TDNN"

src/diart/models.py

@@ -35,14 +35,6 @@ def __init__(self, segmentation_model: nn.Module):
         max_speakers_per_chunk = len(specs.classes)
         self.powerset = Powerset(max_speakers_per_chunk, max_speakers_per_frame)
 
-    @property
-    def specifications(self):
-        return self.model.specifications
-
-    @property
-    def audio(self):
-        return self.model.audio
-
     def forward(self, waveform: torch.Tensor) -> torch.Tensor:
         return self.powerset.to_multilabel(self.model(waveform))