diff --git a/scripts/transcribe-voice-track.py b/scripts/transcribe-voice-track.py
new file mode 100644
index 0000000..41f7b7c
--- /dev/null
+++ b/scripts/transcribe-voice-track.py
@@ -0,0 +1,71 @@
+# pip install requests
+# pip install volk
+# pip install scipy
+import wave
+import json
+import sys
+import os
+import requests
+from zipfile import ZipFile
+from scipy.io import wavfile
+
+from vosk import Model, KaldiRecognizer
+
+model_name = "vosk-model-small-en-us-0.15"
+# model_name = "vosk-model-en-us-0.22" # bigger model. So far, the small one works pretty good.
+
+model_path = f"models/{model_name}"
+model_zip_path = f"{model_path}.zip"
+model_url = f"http://alphacephei.com/vosk/{model_zip_path}"
+
+# Download the model if it doesn't exist
+os.makedirs('models', exist_ok=True)
+if not os.path.exists(model_path):
+    with open(model_zip_path, 'wb') as f:
+        response = requests.get(model_url)
+        f.write(response.content)
+    with ZipFile(model_zip_path, "r") as zip_file:
+        zip_file.extractall('models')
+
+audio_filename = sys.argv[1] if len(sys.argv) > 1 else input("mono-track wav filename? ")
+wf = wave.open(audio_filename, "rb")
+
+model = Model(model_path)
+rec = KaldiRecognizer(model, wf.getframerate())
+rec.SetWords(True)
+
+frames = 4000
+while True:
+    # Mix channels together if the input is stereo
+    if wf.getnchannels() == 2:
+        wf.close()
+        mono_filename = '.'.join(audio_filename.split('.')[:-1]) + '_mono.wav'
+        fs, data = wavfile.read(audio_filename)
+        wavfile.write(mono_filename, fs, data[:, 0])
+        wf = wave.open(mono_filename, 'rb')
+
+    wf.rewind()
+    results = []
+    def filter_result(result):
+        result = json.loads(result)
+        if len(result) != 1:
+            results.append(result)
+
+    while True:
+        data = wf.readframes(frames)
+        if len(data) == 0:
+            break
+        if rec.AcceptWaveform(data):
+            filter_result(rec.Result())
+    filter_result(rec.FinalResult())
+    
+    with open(f"{audio_filename}_{frames}.json", "w") as f:
+        lines = {}
+        for sentence in results:
+            words = sentence['result']
+            text = sentence['text']
+            lines[text] = {'start': words[0]['start'], 'end': words[-1]['end']}
+            print(f'{text}: {words[0]["start"]} {words[-1]["end"]}')
+        json.dump(lines, f)
+
+    frames = int(input(f"Try different frames num? (was {frames}): "))