In this paper, we study the impact of the ageing on modern deep speaker
...
The adoption of advanced deep learning architectures in stuttering detec...
Shortcut learning, or `Clever Hans effect` refers to situations where a
...
This study aims to develop a single integrated spoofing-aware speaker
ve...
We address speaker-aware anti-spoofing, where prior knowledge of the tar...
Deep speaker models yield low error rates in speaker verification.
Nonet...
Stuttering is a neuro-developmental speech impairment characterized by
u...
This work addresses the cross-corpora generalization issue for the
low-r...
This work explores the use of constant-Q transform based modulation spec...
Automatic spoken language identification (LID) is a very important resea...
This work analyzes the constant-Q filterbank-based time-frequency
repres...
Benchmarking initiatives support the meaningful comparison of competing
...
With the rise in multimedia content over the years, more variety is obse...
In this paper, we present end-to-end and speech embedding based systems
...
Speaker recognition on household devices, such as smart speakers, featur...
Deep learning has brought impressive progress in the study of both autom...
By automatic detection and identification of stuttering, speech patholog...
The adoption of advanced deep learning (DL) architecture in stuttering
d...
In this paper, we initiate the concern of enhancing the spoofing robustn...
In this study, we focus on nonlinear compression methods in spectral fea...
Multi-taper estimators provide low-variance power spectrum estimates tha...
After their introduction to robust speech recognition, power normalized
...
We address far-field speaker verification with deep neural network (DNN)...
ASVspoof 2021 is the forth edition in the series of bi-annual challenges...
The automatic speaker verification spoofing and countermeasures (ASVspoo...
For many decades, research in speech technologies has focused upon impro...
Stuttering is a speech disorder during which the flow of speech is
inter...
Whether it be for results summarization, or the analysis of classifier
f...
The performance of speaker recognition system is highly dependent on the...
This paper introduces StutterNet, a novel deep learning based stuttering...
This paper introduces scattering transform for speech emotion recognitio...
In this paper, we conduct one of the very first studies for cross-corpor...
Voice anti-spoofing aims at classifying a given speech input either as a...
We propose a learnable mel-frequency cepstral coefficient (MFCC) fronten...
The ASVspoof initiative was conceived to spearhead research in anti-spoo...
This report describes the speaker diarization system developed by the AB...
In this work, we explore the constant-Q transform (CQT) for speech emoti...
In this paper, we propose a novel method that trains pass-phrase specifi...
This report presents the system developed by the ABSP Laboratory team fo...
Modern automatic speaker verification relies largely on deep neural netw...
In this work, we present the system description of the UIAI entry for th...
Most of the speech processing applications use triangular filters spaced...
Recent years have seen growing efforts to develop spoofing countermeasur...
Speech signals are a rich source of speaker-related information includin...
This paper describes the speaker diarization systems developed for the S...
Automatic speaker verification (ASV) is one of the most natural and
conv...
In this work, we simulate a scenario, where a publicly available ASV sys...
The I4U consortium was established to facilitate a joint entry to NIST
s...
ASVspoof, now in its third edition, is a series of community-led challen...
The performances of the automatic speaker verification (ASV) systems deg...