1 citations · 1 across the 2 of their papers we have counts for
5 papers
Language Modelling for Speaker Diarization in Telephonic Interviews
Miquel India, Javier Hernando, José A. R. Fonollosa
The aim of this paper is to investigate the benefit of combining both language and acoustic modelling for speaker diarization. Although conventional systems only use acoustic featu…
Speaker Characterization by means of Attention Pooling
Federico Costa, Miquel India, Javier Hernando
State-of-the-art Deep Learning systems for speaker verification are commonly based on speaker embedding extractors. These architectures are usually composed of a feature extractor…
Self-attention encoding and pooling for speaker recognition
Pooyan Safari, Miquel India, Javier Hernando
The computing power of mobile devices limits the end-user applications in terms of storage size, processing, memory and energy consumption. These limitations motivate researchers f…
Double Multi-Head Attention for Speaker Verification
Miquel India, Pooyan Safari, Javier Hernando
Most state-of-the-art Deep Learning systems for speaker verification are based on speaker embedding extractors. These architectures are commonly composed of a feature extractor fro…
Self Multi-Head Attention for Speaker Recognition
Miquel India, Pooyan Safari, Javier Hernando
Most state-of-the-art Deep Learning (DL) approaches for speaker recognition work on a short utterance level. Given the speech signal, these algorithms extract a sequence of speaker…