diff --git a/whisper_timestamped/transcribe.py b/whisper_timestamped/transcribe.py
index ff23405..aca629e 100755
--- a/whisper_timestamped/transcribe.py
+++ b/whisper_timestamped/transcribe.py
@@ -117,6 +117,10 @@ def transcribe_timestamped(
     suppress_tokens="-1",
     sample_len=None,
     verbose=False,
+    avoid_empty_speech=True,
+    vad_min_speech_duration=0.1,
+    vad_min_silence_duration=1,
+    vad_dilatation=0.5,
 ):
     """
     Transcribe an audio file using Whisper
@@ -214,6 +218,18 @@ def transcribe_timestamped(
         Whether to display the text being decoded to the console. If True, displays all the details,
         If False, displays minimal details. If None, does not display anything
 
+    avoid_empty_speech: bool
+        Whether to avoid empty speech segments (i.e. segments with no speech detected).
+
+    vad_min_speech_duration: float
+        Minimum duration of a speech segment, in seconds. If a speech segment is shorter than this, it will be removed.
+
+    vad_min_silence_duration: float
+        Minimum duration of a silence segment, in seconds. If a silence segment is shorter than this, it will be removed.
+
+    vad_dilatation: float
+        Dilatation factor for the speech segments. If a speech segment is shorter than this, it will be removed.
+
     Returns
     -------
     A dictionary containing the resulting text ("text") and segment-level details ("segments"), and
@@ -293,7 +309,15 @@ def transcribe_timestamped(
 
     if vad is not None:
         audio = get_audio_tensor(audio)
-        audio, vad_segments, convert_timestamps = remove_non_speech(audio, method=vad, sample_rate=SAMPLE_RATE, plot=plot_word_alignment, avoid_empty_speech=True)
+        audio, vad_segments, convert_timestamps = remove_non_speech(audio,
+                                                                    method=vad,
+                                                                    sample_rate=SAMPLE_RATE,
+                                                                    plot=plot_word_alignment,
+                                                                    avoid_empty_speech=avoid_empty_speech,
+                                                                    min_speech_duration=vad_min_speech_duration,
+                                                                    min_silence_duration=vad_min_silence_duration,
+                                                                    dilatation=vad_dilatation,
+                                                                    )
     else:
         vad_segments = None