How can I extract the shape from a list-based embedding returned by SpeechBrain?

Below is an explanation of the error and a revised code snippet for handling the embeddings properly.

Why the Error Occurs

The error 'list' object has no attribute 'shape' is raised because the returned embedding (i.e., embeddings[0]) is a Python list rather than a PyTorch tensor or a NumPy array. The attribute shape is available on NumPy arrays (and tensors) but not on Python lists.

Correct Handling of Embeddings

Since SpeechBrain’s encode_batch may return the embeddings inside a list (or even nested lists), the correct way to handle the output is to convert the embedding to a NumPy array if it isn’t one already. This can be done using np.array().

Revised Code Example

Below is your revised code with the appropriate handling of the embedding:

PYTHONCopied
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 if any embeddings were returned
    if embeddings:
        print("Embeddings received successfully.")
        
        # Assuming the first element is a list, convert it to a NumPy array
        embedding = embeddings[0]
        if isinstance(embedding, list):
            first_embedding = np.array(embedding)
            print("Converted the list to a NumPy array.")
        elif hasattr(embedding, 'cpu'):  # The embedding is a tensor
            first_embedding = embedding.cpu().numpy()
            print("Converted the tensor to a NumPy array.")
        elif isinstance(embedding, np.ndarray):
            first_embedding = embedding
            print("The embedding is already a NumPy array.")
        else:
            raise TypeError("Unexpected type of embedding.")
        
        # Display the shape of the first embedding
        print("Shape of the first embedding:", first_embedding.shape)
    else:
        print("No embeddings returned or empty list.")
except Exception as e:
    print(f"Error during encoding: {e}")

Summary

• Error Explanation: The error occurs because embeddings[0] is a list that does not have a .shape attribute.
• Solution: Convert the list to a NumPy array (using np.array(embedding)) before checking its shape.

This approach should help you extract and inspect the shape of the returned embeddings without encountering the attribute error.