diff --git a/TTS/api.py b/TTS/api.py
index 7abc188e74..0900db0525 100644
--- a/TTS/api.py
+++ b/TTS/api.py
@@ -88,7 +88,7 @@ def models(self):
 
     @property
     def is_multi_speaker(self):
-        if hasattr(self.synthesizer.tts_model, "speaker_manager") and self.synthesizer.tts_model.speaker_manager:
+        if hasattr(self.synthesizer.tts_model, "speaker_Smanager") and self.synthesizer.tts_model.speaker_manager:
             return self.synthesizer.tts_model.speaker_manager.num_speakers > 1
         return False
 
@@ -243,6 +243,7 @@ def tts(
         emotion: str = None,
         speed: float = None,
         split_sentences: bool = True,
+        SuppresPrintStatements: bool = False,
         **kwargs,
     ):
         """Convert text to speech.
@@ -267,6 +268,9 @@ def tts(
                 Split text into sentences, synthesize them separately and concatenate the file audio.
                 Setting it False uses more VRAM and possibly hit model specific text length or VRAM limits. Only
                 applicable to the 🐸TTS models. Defaults to True.
+            SuppresPrintStatements (bool, optional):
+                Suppress All the Print statements so that when runnging the function in thread the print statement will not apears in the terminal.
+                Setting it to True will suppress the print statements
             kwargs (dict, optional):
                 Additional arguments for the model.
         """
@@ -283,6 +287,7 @@ def tts(
             style_text=None,
             reference_speaker_name=None,
             split_sentences=split_sentences,
+            SuppresPrintStatements=SuppresPrintStatements,
             **kwargs,
         )
         return wav
diff --git a/TTS/utils/synthesizer.py b/TTS/utils/synthesizer.py
index b98647c30c..2666f868a8 100644
--- a/TTS/utils/synthesizer.py
+++ b/TTS/utils/synthesizer.py
@@ -265,6 +265,7 @@ def tts(
         reference_wav=None,
         reference_speaker_name=None,
         split_sentences: bool = True,
+        SuppresPrintStatements: bool= False,
         **kwargs,
     ) -> List[int]:
         """🐸 TTS magic. Run all the models and generate speech.
@@ -279,6 +280,7 @@ def tts(
             reference_wav ([type], optional): reference waveform for voice conversion. Defaults to None.
             reference_speaker_name ([type], optional): speaker id of reference waveform. Defaults to None.
             split_sentences (bool, optional): split the input text into sentences. Defaults to True.
+            SuppresPrintStatements (bool, optional): Suppress the Print statements.
             **kwargs: additional arguments to pass to the TTS model.
         Returns:
             List[int]: [description]
@@ -294,9 +296,11 @@ def tts(
         if text:
             sens = [text]
             if split_sentences:
-                print(" > Text splitted to sentences.")
+                if not SuppresPrintStatements:
+                    print(" > Text splitted to sentences.")
                 sens = self.split_into_sentences(text)
-            print(sens)
+            if not SuppresPrintStatements:
+                print(sens)
 
         # handle multi-speaker
         if "voice_dir" in kwargs:
@@ -420,7 +424,8 @@ def tts(
                         self.vocoder_config["audio"]["sample_rate"] / self.tts_model.ap.sample_rate,
                     ]
                     if scale_factor[1] != 1:
-                        print(" > interpolating tts model output.")
+                        if not SuppresPrintStatements:
+                            print(" > interpolating tts model output.")
                         vocoder_input = interpolate_vocoder_input(scale_factor, vocoder_input)
                     else:
                         vocoder_input = torch.tensor(vocoder_input).unsqueeze(0)  # pylint: disable=not-callable
@@ -484,7 +489,8 @@ def tts(
                     self.vocoder_config["audio"]["sample_rate"] / self.tts_model.ap.sample_rate,
                 ]
                 if scale_factor[1] != 1:
-                    print(" > interpolating tts model output.")
+                    if not SuppresPrintStatements:
+                        print(" > interpolating tts model output.")
                     vocoder_input = interpolate_vocoder_input(scale_factor, vocoder_input)
                 else:
                     vocoder_input = torch.tensor(vocoder_input).unsqueeze(0)  # pylint: disable=not-callable
@@ -500,6 +506,7 @@ def tts(
         # compute stats
         process_time = time.time() - start_time
         audio_time = len(wavs) / self.tts_config.audio["sample_rate"]
-        print(f" > Processing time: {process_time}")
-        print(f" > Real-time factor: {process_time / audio_time}")
+        if not SuppresPrintStatements:
+            print(f" > Processing time: {process_time}")
+            print(f" > Real-time factor: {process_time / audio_time}")
         return wavs