Speaker Diarization with LSTM
Speaker Diarization with LSTM
For many years, i-vector based audio embedding techniques were the dominant approach for speaker verification and speaker diarization applications. However, mirroring the rise of deep learning in various domains, neural network based audio embeddings, also known as <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d-vectors</i> , have consistently demonstrated superior speaker verification performance. In this …