diff --git a/vall_e/inference.py b/vall_e/inference.py
index 150e128..44d2e1e 100755
--- a/vall_e/inference.py
+++ b/vall_e/inference.py
@@ -103,7 +103,7 @@ class TTS():
 		return torch.tensor([ id ])
 
 	# to-do: trim before quantizing, instead of after
-	def encode_audio( self, paths, trim_length=9.0 ):
+	def encode_audio( self, paths, trim_length=5.0 ):
 		# already a tensor, return it
 		if isinstance( paths, Tensor ):
 			return paths
@@ -126,14 +126,9 @@ class TTS():
 
 		res = torch.cat(proms)
 		
-		# kludge, but it's to correct an oversight in training
 		if trim_length:
 			res = repeat_extend_audio( res, int( cfg.dataset.frames_per_second * trim_length ) )
-
-		"""
-		if trim_length:
-			res = trim( res, int( cfg.dataset.frames_per_second * trim_length ) )
-		"""
+			#res = trim( res, int( cfg.dataset.frames_per_second * trim_length ) )
 		
 		return res
 
diff --git a/vall_e/webui.py b/vall_e/webui.py
index 97f166e..8ce9285 100644
--- a/vall_e/webui.py
+++ b/vall_e/webui.py
@@ -346,9 +346,9 @@ with ui:
 						with gr.Row():
 							layout["inference_tts"]["inputs"]["max-seconds"] = gr.Slider(value=12, minimum=1, maximum=32, step=0.1, label="Maximum Seconds", info="Limits how many steps to perform in the AR pass.")
 							#layout["inference_tts"]["inputs"]["max-nar-levels"] = gr.Slider(value=7, minimum=0, maximum=7, step=1, label="Max NAR Levels", info="Limits how many steps to perform in the NAR pass.")
-							layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=9.0, 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.")
+							layout["inference_tts"]["inputs"]["input-prompt-length"] = gr.Slider(value=5.0, 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_tts"]["inputs"]["ar-temp"] = gr.Slider(value=1.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR. (0 to greedy sample)")
+							layout["inference_tts"]["inputs"]["ar-temp"] = gr.Slider(value=0.9, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (AR)", info="Modifies the randomness from the samples in the AR. (0 to greedy sample)")
 							layout["inference_tts"]["inputs"]["nar-temp"] = gr.Slider(value=0.0, minimum=0.0, maximum=1.5, step=0.05, label="Temperature (NAR)", info="Modifies the randomness from the samples in the NAR. (0 to greedy sample)")
 						with gr.Row():
 							#layout["inference_tts"]["inputs"]["input-prompt-prefix"] = gr.Checkbox(label="Input Prompt as Prefix", info="Treats the input prompt clip as the prefix of the generated sequence.")