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Found 7 papers, 3 papers with code
Summary of the DISPLACE Challenge 2023 -- DIarization of SPeaker and LAnguage in Conversational Environments
In multi-lingual societies, where multiple languages are spoken in a small geographic vicinity, informal conversations often involve mix of languages.
DISPLACE Challenge: DIarization of SPeaker and LAnguage in Conversational Environments
The challenge attempts to highlight outstanding issues in speaker diarization (SD) in multilingual settings with code-mixing.
DiCOVA Challenge: Dataset, task, and baseline system for COVID-19 diagnosis using acoustics
The DiCOVA challenge aims at accelerating research in diagnosing COVID-19 using acoustics (DiCOVA), a topic at the intersection of speech and audio processing, respiratory health diagnosis, and machine learning.
Neural PLDA Modeling for End-to-End Speaker Verification
Recently, we had proposed a neural network approach for backend modeling in speaker verification called the neural PLDA (NPLDA) where the likelihood ratio score of the generative PLDA model is posed as a discriminative similarity function and the learnable parameters of the score function are optimized using a verification cost.
NPLDA: A Deep Neural PLDA Model for Speaker Verification
The likelihood ratio score of the generative PLDA model is posed as a discriminative similarity function and the learnable parameters of the score function are optimized using a verification cost.
LEAP System for SRE19 CTS Challenge -- Improvements and Error Analysis
In this paper, we provide a detailed account of the LEAP SRE system submitted to the CTS challenge focusing on the novel components in the back-end system modeling.
Pairwise Discriminative Neural PLDA for Speaker Verification
The pre-processing steps of linear discriminant analysis (LDA), unit length normalization and within class covariance normalization are all modeled as layers of a neural model and the speaker verification cost functions can be back-propagated through these layers during training.
