Update README.md

README.md

@@ -106,18 +106,29 @@ plt.show()
 ## Example: Accessing a reverberant speech file encoded to 8th-order Ambisonics
 ```python
 from datasets import load_dataset, Audio
-ds = load_dataset(
-    "treble-technologies/Treble10-Speech",
-    split="speech_hoa8",
-    streaming=True,
-)
-# Keep native sampling rate (don’t ask TorchCodec to resample)
-ds = ds.cast_column("audio", Audio())
-rec = next(iter(ds))
-# Read the samples from the TorchCodec decoder object:
-samples = rec["audio"].get_all_samples()
-speech = samples.data.cpu().numpy()  # shape: (frames, channels), HOA preserved
-sr = samples.sample_rate
+import io, soundfile as sf
+
+# Load dataset in streaming mode
+ds = load_dataset("treble-technologies/Treble10-Speech", split="speech_hoa8", streaming=True)
+
+# Disable automatic decoding (we'll do it manually)
+ds = ds.cast_column("audio", Audio(decode=False))
+
+# Get one sample from the iterator
+sample = next(iter(ds))
+
+# Fetch raw audio bytes
+audio_bytes = sample["audio"]["bytes"]
+
+# Some older datasets may not have "bytes", so fall back to reading from the file
+if audio_bytes is None:
+    # Use huggingface's file object directly
+    with sample["audio"]["path"].open("rb") as f:
+        audio_bytes = f.read()
+
+# Decode the HOA audio directly from memory
+rir_hoa, sr = sf.read(io.BytesIO(audio_bytes))
+print(f"Loaded HOA audio: shape={rir_hoa.shape}, sr={sr}")
 ```
 
 ## Example: Accessing a reverberant speech file at the microphones of a 6-channel device