diff --git a/advanced_training_notebook.ipynb b/advanced_training_notebook.ipynb
index 51c3046..7c8a779 100644
--- a/advanced_training_notebook.ipynb
+++ b/advanced_training_notebook.ipynb
@@ -173,9 +173,19 @@
     "# -----------------------------\n",
     "# Download and Process Audioset\n",
     "# -----------------------------\n",
+    "from datasets import Dataset, Audio\n",
+    "import os\n",
+    "from pathlib import Path\n",
+    "import scipy.io.wavfile\n",
+    "from tqdm import tqdm\n",
+    "\n",
+    "# Directory setup\n",
     "audioset_dir = \"./audioset\"\n",
     "os.makedirs(audioset_dir, exist_ok=True)\n",
     "\n",
+    "output_dir = \"./audioset_16k\"\n",
+    "os.makedirs(output_dir, exist_ok=True)\n",
+    "\n",
     "# Full-scale dataset download links\n",
     "dataset_links = [\n",
     "    f\"https://huggingface.co/datasets/agkphysics/AudioSet/resolve/main/data/bal_train0{i}.tar\"\n",
@@ -192,10 +202,6 @@
     "        print(f\"Extracting {file_name}...\")\n",
     "        os.system(f\"tar -xf {out_path} -C {audioset_dir}\")\n",
     "\n",
-    "# Directory for 16kHz WAV files\n",
-    "output_dir = \"./audioset_16k\"\n",
-    "os.makedirs(output_dir, exist_ok=True)\n",
-    "\n",
     "# Collect all FLAC files for processing\n",
     "audioset_files = list(Path(audioset_dir).glob(\"**/*.flac\"))\n",
     "print(f\"Number of FLAC files found: {len(audioset_files)}\")\n",
@@ -212,14 +218,18 @@
     "            # Define output file name and path\n",
     "            name = Path(row[\"audio\"][\"path\"]).stem + \".wav\"\n",
     "            output_path = Path(output_dir) / name\n",
-    "            \n",
+    "\n",
     "            # Read and convert audio\n",
-    "            data = row[\"audio\"][\"array\"]\n",
-    "            if data is None or len(data) == 0:\n",
-    "                raise ValueError(f\"Empty audio data in file: {row['audio']['path']}\")\n",
-    "            scipy.io.wavfile.write(output_path, 16000, (data * 32767).astype(np.int16))\n",
-    "        \n",
+    "            if row[\"audio\"][\"array\"] is None or len(row[\"audio\"][\"array\"]) == 0:\n",
+    "                raise ValueError(f\"Empty or invalid audio data in file: {row['audio']['path']}\")\n",
+    "\n",
+    "            scipy.io.wavfile.write(\n",
+    "                output_path,\n",
+    "                16000,\n",
+    "                (row[\"audio\"][\"array\"] * 32767).astype(np.int16),\n",
+    "            )\n",
     "        except Exception as e:\n",
+    "            # Log and skip problematic files\n",
     "            print(f\"Error converting {row['audio']['path']}: {e}\")\n",
     "            corrupted_files.append(row[\"audio\"][\"path\"])\n",
     "\n",