diff --git a/TTS/tts/models/xtts.py b/TTS/tts/models/xtts.py
index 7ca6ff85..aec1a098 100644
--- a/TTS/tts/models/xtts.py
+++ b/TTS/tts/models/xtts.py
@@ -410,15 +410,13 @@ class Xtts(BaseTTS):
         if speaker_id is not None:
             gpt_cond_latent, speaker_embedding = self.speaker_manager.speakers[speaker_id].values()
             return self.inference(text, language, gpt_cond_latent, speaker_embedding, **settings)
-        settings.update(
-            {
-                "gpt_cond_len": config.gpt_cond_len,
-                "gpt_cond_chunk_len": config.gpt_cond_chunk_len,
-                "max_ref_len": config.max_ref_len,
-                "sound_norm_refs": config.sound_norm_refs,
-            }
-        )
-        return self.full_inference(text, speaker_wav, language, speed, **settings)
+        settings.update({
+            "gpt_cond_len": config.gpt_cond_len,
+            "gpt_cond_chunk_len": config.gpt_cond_chunk_len,
+            "max_ref_len": config.max_ref_len,
+            "sound_norm_refs": config.sound_norm_refs,
+        })
+        return self.full_inference(text, speaker_wav, language, **settings)
 
     @torch.inference_mode()
     def full_inference(
@@ -761,12 +759,13 @@ class Xtts(BaseTTS):
 
         model_path = checkpoint_path or os.path.join(checkpoint_dir, "model.pth")
         vocab_path = vocab_path or os.path.join(checkpoint_dir, "vocab.json")
-        speaker_file_path = speaker_file_path or os.path.join(checkpoint_dir, "speakers_xtts.pth")
+        
+        if speaker_file_path is None and checkpoint_dir is not None:
+            speaker_file_path = os.path.join(checkpoint_dir, "speakers_xtts.pth")
 
         self.language_manager = LanguageManager(config)
         self.speaker_manager = None
-        if os.path.exists(speaker_file_path):
-            self.speaker_manager = SpeakerManager(speaker_file_path)
+        if speaker_file_path is not None and os.path.exists(speaker_file_path):
 
         if os.path.exists(vocab_path):
             self.tokenizer = VoiceBpeTokenizer(vocab_file=vocab_path)