espnet2.spk.pooling.chn_attn_stat_pooling.ChnAttnStatPooling

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class espnet2.spk.pooling.chn_attn_stat_pooling.ChnAttnStatPooling(input_size: int = 1536)

Bases: AbsPooling

Aggregates frame-level features to single utterance-level feature.

Reference: ECAPA-TDNN: Emphasized Channel Attention, Propagation and Aggregation in TDNN Based Speaker Verification https://arxiv.org/pdf/2005.07143

• Parameters:input_size – Dimension of the input frame-level embeddings. The output dimensionality will be 2 × input_size after concatenating mean and std.

Initializes internal Module state, shared by both nn.Module and ScriptModule.

forward(x: Tensor, feat_lengths: Tensor | None = None) → Tensor

Forward pass of channel-attentive statistical pooling.

• Parameters:
  • x – Input feature tensor of shape (batch_size, feature_dim, seq_len)
  • feat_lengths – Optional tensor of shape (batch_size,) containing the valid length of each sequence before padding
• Returns: Utterance-level embeddings of shape (batch_size, 2 × feature_dim)
• Return type: x

output_size()