[Python] 'list' object has no attribute 'shape' speechbrain python

I encountered an error while using the SpeechBrain library with the following message:
Error during encoding: 'list' object has no attribute 'shape'

Context:


I am working on speaker recognition using the SpeechBrain pre-trained SpeakerRecognition model. Below is the code I am using:

import numpy as np
from speechbrain.pretrained import SpeakerRecognition

# Initialize the speaker recognition model
model = SpeakerRecognition.from_hparams(
source="speechbrain/spkrec-ecapa-voxceleb",
savedir="pretrained_model"
)

# Path to the WAV file
wav_file = r"c:\audio_files\test.wav" # Update with your file path

# Test the model encoding using the encode_batch method
try:
# The model expects input as a list of file paths
embeddings = model.encode_batch([wav_file])

# Check the returned embeddings' structure
if embeddings:
print("Embeddings received successfully.")

# Check if the embeddings are tensors or NumPy arrays
if hasattr(embeddings[0], 'cpu'): # If it's a tensor
first_embedding = embeddings[0].cpu().numpy() # Convert to NumPy array
print("First embedding converted to NumPy array.")
elif isinstance(embeddings[0], np.ndarray): # If it's already a NumPy array
first_embedding = embeddings[0]
print("First embedding is already a NumPy array.")

# Display the shape of the first embedding if it's a NumPy array
if isinstance(first_embedding, np.ndarray):
print("Shape of the first embedding:", first_embedding.shape)
else:
print("The embedding is neither a tensor nor a NumPy array.")
else:
print("No embeddings returned or empty list.")
except Exception as e:
print(f"Error during encoding: {e}")

Problem:


The issue seems to arise when checking the shape of the embedding. Specifically, it looks like embeddings[0] is a list instead of a tensor or NumPy array.

Question:

• Why am I getting the error 'list' object has no attribute 'shape'?
• What is the correct way to handle the embeddings returned by model.encode_batch to extract their shape?

Notes:

• I am new to SpeechBrain and Python-based ML frameworks. Any clarification or guidance would be appreciated!

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