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Found 8 papers, 0 papers with code
VoxWatch: An open-set speaker recognition benchmark on VoxCeleb
Prior studies on this problem are sparse, and lack a common benchmark for systematic evaluations.
The 2021 NIST Speaker Recognition Evaluation
Evaluation results indicate: audio-visual fusion produce substantial gains in performance over audio-only or visual-only systems; top performing speaker and face recognition systems exhibited comparable performance under the matched domain conditions present in this evaluation; and, the use of complex neural network architectures (e. g., ResNet) along with angular losses with margin, data augmentation, as well as long duration fine-tuning contributed to notable performance improvements for the audio-only speaker recognition task.
The NIST CTS Speaker Recognition Challenge
The US National Institute of Standards and Technology (NIST) has been conducting a second iteration of the CTS challenge since August 2020.
Multimodal Emotion Recognition using Transfer Learning from Speaker Recognition and BERT-based models
Experimental results indicate that both audio and text-based models improve the emotion recognition performance and that the proposed multimodal solution achieves state-of-the-art results on the IEMOCAP benchmark.
NIST SRE CTS Superset: A large-scale dataset for telephony speaker recognition
This document provides a brief description of the National Institute of Standards and Technology (NIST) speaker recognition evaluation (SRE) conversational telephone speech (CTS) Superset.
Improved Speech Emotion Recognition using Transfer Learning and Spectrogram Augmentation
Automatic speech emotion recognition (SER) is a challenging task that plays a crucial role in natural human-computer interaction.
The IBM Speaker Recognition System: Recent Advances and Error Analysis
We present the recent advances along with an error analysis of the IBM speaker recognition system for conversational speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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The IBM 2016 Speaker Recognition System
In this paper we describe the recent advancements made in the IBM i-vector speaker recognition system for conversational speech.
