Humans can identify a speaker by listening to their voice, over the telephone, or on any
digital devices. Acquiring this congenital human competency, authentication technologies …

We present a structured overview of adaptation algorithms for neural network-based speech
recognition, considering both hybrid hidden Markov model/neural network systems and end …

The objective of this work is speaker recognition under noisy and unconstrained conditions.
We make two key contributions. First, we introduce a very large-scale audio-visual dataset …

Most existing datasets for speaker identification contain samples obtained under quite
constrained conditions, and are usually hand-annotated, hence limited in size. The goal of …

The CHiME challenge series aims to advance robust automatic speech recognition (ASR)
technology by promoting research at the interface of speech and language processing …

Speech enhancement and automatic speech recognition (ASR) are most often evaluated in
matched (or multi-condition) settings where the acoustic conditions of the training data …

Abstract The Speakers in the Wild (SITW) speaker recognition database contains hand-
annotated speech samples from open-source media for the purpose of benchmarking text …

This paper describes the Arabic MGB-3 Challenge-Arabic Speech Recognition in the Wild.
Unlike last year's Arabic MGB-2 Challenge, for which the recognition task was based on …

Ensuring proper punctuation and letter casing is a key pre-processing step towards applying
complex natural language processing algorithms. This is especially significant for textual …

This paper proposes to use self-attention based model to predict punctuation marks for word
sequences. The model is trained using word and speech embedding features which are …