Text-Independent Speaker Verification
17 papers with code • 0 benchmarks • 0 datasets
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Improving Text-Independent Speaker Verification with Auxiliary Speakers Using Graph
Given the embeddings from a pair of input utterances, a graph model is designed to incorporate additional information from a group of embeddings representing the so-called auxiliary speakers.
Serialized Multi-Layer Multi-Head Attention for Neural Speaker Embedding
Instead of utilizing multi-head attention in parallel, the proposed serialized multi-layer multi-head attention is designed to aggregate and propagate attentive statistics from one layer to the next in a serialized manner.
Multi-user VoiceFilter-Lite via Attentive Speaker Embedding
In this paper, we propose a solution to allow speaker conditioned speech models, such as VoiceFilter-Lite, to support an arbitrary number of enrolled users in a single pass.
Personalized Keyphrase Detection using Speaker and Environment Information
In this paper, we introduce a streaming keyphrase detection system that can be easily customized to accurately detect any phrase composed of words from a large vocabulary.
SpeakerStew: Scaling to Many Languages with a Triaged Multilingual Text-Dependent and Text-Independent Speaker Verification System
To the best of our knowledge, this is the first study of speaker verification systems at the scale of 46 languages.
Bidirectional Multiscale Feature Aggregation for Speaker Verification
In this paper, we propose a novel bidirectional multiscale feature aggregation (BMFA) network with attentional fusion modules for text-independent speaker verification.
An Empirical Study on Text-Independent Speaker Verification based on the GE2E Method
While many researchers in the speaker recognition area have started to replace the former classical state-of-the-art methods with deep learning techniques, some of the traditional i-vector-based methods are still state-of-the-art in the context of text-independent speaker verification.
Small footprint Text-Independent Speaker Verification for Embedded Systems
Deep neural network approaches to speaker verification have proven successful, but typical computational requirements of State-Of-The-Art (SOTA) systems make them unsuited for embedded applications.
Multi-task Metric Learning for Text-independent Speaker Verification
To evaluate the proposed method, we conduct experiments on the Speaker in the Wild (SITW) dataset.
Few Shot Text-Independent speaker verification using 3D-CNN
Facial recognition system is one of the major successes of Artificial intelligence and has been used a lot over the last years.
