Microsoft Corporation
Convolutional neural network with phonetic attention for speaker verification

Abstract:

Embodiments may include reception of a plurality of speech frames, determination of a multi-dimensional acoustic feature associated with each of the plurality of speech frames, determination of a plurality of multi-dimensional phonetic features, each of the plurality of multi-dimensional phonetic features determined based on a respective one of the plurality of speech frames, generation of a plurality of two-dimensional feature maps based on the phonetic features, input of the feature maps and the plurality of acoustic features to a convolutional neural network, the convolutional neural network to generate a plurality of speaker embeddings based on the plurality of feature maps and the plurality of acoustic features, aggregation of the plurality of speaker embeddings into a first speaker embedding based on respective weights determined for each of the plurality of speaker embeddings, and determination of a speaker associated with the plurality of speech frames based on the first speaker embedding.