espnet2.spk.pooling.stat_pooling.StatsPooling

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class espnet2.spk.pooling.stat_pooling.StatsPooling(input_size: int = 1536)

Bases: AbsPooling

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

Proposed in D. Snyder et al., “X-vectors: Robust dnn embeddings for speaker recognition”

• Parameters:input_size – dimensionality of the input frame-level embeddings. Determined by encoder hyperparameter. For this pooling layer, the output dimensionality will be double of the input_size

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

forward(x, task_tokens: Tensor | None = None)

Defines the computation performed at every call.

Should be overridden by all subclasses.

NOTE

Although the recipe for forward pass needs to be defined within this function, one should call the Module instance afterwards instead of this since the former takes care of running the registered hooks while the latter silently ignores them.

output_size()