diff --git a/vall_e/__main__.py b/vall_e/__main__.py
index 2709ace..c435bff 100755
--- a/vall_e/__main__.py
+++ b/vall_e/__main__.py
@@ -19,6 +19,7 @@ def main():
 
 	parser.add_argument("--ar-temp", type=float, default=1.0)
 	parser.add_argument("--nar-temp", type=float, default=1.0)
+	parser.add_argument("--input-prompt-length", type=float, default=3.0)
 
 	parser.add_argument("--top-p", type=float, default=1.0)
 	parser.add_argument("--top-k", type=int, default=0)
@@ -32,7 +33,7 @@ def main():
 	args = parser.parse_args()
 
 	tts = TTS( config=args.yaml, ar_ckpt=args.ar_ckpt, nar_ckpt=args.nar_ckpt, device=args.device, dtype=args.dtype, amp=args.amp )
-	tts.inference( text=args.text, references=args.references, out_path=args.out_path, max_ar_steps=args.max_ar_steps, ar_temp=args.ar_temp, nar_temp=args.nar_temp, top_p=args.top_p, top_k=args.top_k, repetition_penalty=args.repetition_penalty, repetition_penalty_decay=args.repetition_penalty_decay, length_penalty=args.length_penalty )
+	tts.inference( text=args.text, references=args.references, out_path=args.out_path, input_prompt_length=args.input_prompt_length, max_ar_steps=args.max_ar_steps, ar_temp=args.ar_temp, nar_temp=args.nar_temp, top_p=args.top_p, top_k=args.top_k, repetition_penalty=args.repetition_penalty, repetition_penalty_decay=args.repetition_penalty_decay, length_penalty=args.length_penalty )
 
 if __name__ == "__main__":
 	main()
diff --git a/vall_e/inference.py b/vall_e/inference.py
index 293e705..49f2d76 100755
--- a/vall_e/inference.py
+++ b/vall_e/inference.py
@@ -121,7 +121,7 @@ class TTS():
 		phones = [ " " if not p else p for p in content ]
 		return torch.tensor([ 1 ] + [*map(self.symmap.get, phones)] + [ 2 ])
 
-	def encode_audio( self, paths, should_trim=True ):
+	def encode_audio( self, paths, trim_length=0.0 ):
 		# already a tensor, return it
 		if isinstance( paths, Tensor ):
 			return paths
@@ -133,17 +133,17 @@ class TTS():
 		# merge inputs
 		res = torch.cat([qnt.encode_from_file(path)[0][:, :].t().to(torch.int16) for path in paths])
 		
-		if should_trim:
-			res = trim( res, int( 75 * cfg.dataset.prompt_duration ) )
+		if trim_length:
+			res = trim( res, int( 75 * trim_length ) )
 		
 		return res
 
 	@torch.inference_mode()
-	def inference( self, text, references, max_ar_steps=6 * 75, ar_temp=0.95, nar_temp=0.5, top_p=1.0, top_k=0, repetition_penalty=1.0, repetition_penalty_decay=0.0, length_penalty=0.0, out_path=None ):
+	def inference( self, text, references, max_ar_steps=6 * 75, input_prompt_length=0.0, ar_temp=0.95, nar_temp=0.5, top_p=1.0, top_k=0, repetition_penalty=1.0, repetition_penalty_decay=0.0, length_penalty=0.0, out_path=None ):
 		if out_path is None:
 			out_path = f"./data/{cfg.start_time}.wav"
 
-		prom = self.encode_audio( references )
+		prom = self.encode_audio( references, trim_length=input_prompt_length )
 		phns = self.encode_text( text )
 
 		prom = to_device(prom, self.device).to(torch.int16)
diff --git a/vall_e/webui.py b/vall_e/webui.py
index 28777b1..a2b7b79 100644
--- a/vall_e/webui.py
+++ b/vall_e/webui.py
@@ -57,6 +57,7 @@ def do_inference( progress=gr.Progress(track_tqdm=True), *args, **kwargs ):
 	parser = argparse.ArgumentParser(allow_abbrev=False)
 	parser.add_argument("--text", type=str, default=kwargs["text"])
 	parser.add_argument("--references", type=str, default=kwargs["reference"])
+	parser.add_argument("--input-prompt-length", type=float, default=kwargs["input-prompt-length"])
 	parser.add_argument("--max-ar-steps", type=int, default=int(kwargs["max-seconds"]*75))
 	parser.add_argument("--ar-temp", type=float, default=kwargs["ar-temp"])
 	parser.add_argument("--nar-temp", type=float, default=kwargs["nar-temp"])
@@ -75,6 +76,7 @@ def do_inference( progress=gr.Progress(track_tqdm=True), *args, **kwargs ):
 		references=[args.references.split(";")],
 		out_path=tmp.name,
 		max_ar_steps=args.max_ar_steps,
+		input_prompt_length=args.input_prompt_length,
 		ar_temp=args.ar_temp,
 		nar_temp=args.nar_temp,
 		top_p=args.top_p,
@@ -161,7 +163,9 @@ with ui:
 				layout["inference"]["outputs"]["output"] = gr.Audio(label="Output")
 				layout["inference"]["buttons"]["inference"] = gr.Button(value="Inference")
 			with gr.Column(scale=7):
-				layout["inference"]["inputs"]["max-seconds"] = gr.Slider(value=6, minimum=1, maximum=32, step=0.1, label="Maximum Seconds", info="This sets a limit of how many steps to perform in the AR pass.")
+				with gr.Row():
+					layout["inference"]["inputs"]["max-seconds"] = gr.Slider(value=6, minimum=1, maximum=32, step=0.1, label="Maximum Seconds", info="This sets a limit of how many steps to perform in the AR pass.")
+					layout["inference"]["inputs"]["input-prompt-length"] = gr.Slider(value=3.0, minimum=0.0, maximum=12.0, step=0.05, label="Input Prompt Trim Length", info="Trims the input prompt down to X seconds. Set 0 to disable.")
 				with gr.Row():
 					layout["inference"]["inputs"]["ar-temp"] = gr.Slider(value=0.95, minimum=0.0, maximum=1.2, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR.")
 					layout["inference"]["inputs"]["nar-temp"] = gr.Slider(value=0.25, minimum=0.0, maximum=1.2, step=0.05, label="Temperature (NAR)", info="Modifies the randomness from the samples in the NAR.")