diff --git a/GUIs/qt/audio_visualizer.py b/GUIs/qt/audio_visualizer.py
index cbe742f..5d8e55f 100644
--- a/GUIs/qt/audio_visualizer.py
+++ b/GUIs/qt/audio_visualizer.py
@@ -121,6 +121,7 @@ def update(self):
         update the mesh and shift the noise each time
         """
         wf_data = self.stream.read(self.CHUNK)
+        print(type(wf_data))
 
         verts, faces, colors = self.mesh(offset=self.offset, wf_data=wf_data)
         self.mesh1.setMeshData(vertexes=verts, faces=faces, faceColors=colors)
diff --git a/learning_diary/may.md b/learning_diary/may.md
index d5bd28c..aba5026 100644
--- a/learning_diary/may.md
+++ b/learning_diary/may.md
@@ -1,4 +1,13 @@
 # MAY 2023
 
-## Automatic Speech Recognition
+## Automatic Speech Recognition (ASR)
 
+1. [**Tutorials — NVIDIA NeMo**](https://docs.nvidia.com/deeplearning/nemo/user-guide/docs/en/stable/starthere/tutorials.html)
+2. [**SpeechBrain: A PyTorch Speech Toolkit**](https://speechbrain.github.io/index.html)
+3. [**Uberi/speech_recognition: Speech recognition module for Python, supporting several engines and APIs, online and offline. (github.com)**](https://github.com/Uberi/speech_recognition/tree/master)
+4. [**mozilla/DeepSpeech: DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers. (github.com)**](https://github.com/mozilla/DeepSpeech)
+5. [**Introducing Whisper (openai.com)**](https://openai.com/research/whisper)
+
+### Offline vs. Online
+
+The above links refers to open-source models which usually needs GPU to run properly in real-time. So, for a mid-budget laptop these models are too slow for real-time implementation (especially if ASR is not the only model that you want to run on the PC).