Speaker Recognition
90 papers with code • 1 benchmarks • 6 datasets
Speaker Recognition is the process of identifying or confirming the identity of a person given his speech segments.
Source: Margin Matters: Towards More Discriminative Deep Neural Network Embeddings for Speaker Recognition
Benchmarks
These leaderboards are used to track progress in Speaker Recognition
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Libraries
Use these libraries to find Speaker Recognition models and implementationsDatasets
VoxCeleb1
VGG-Sound
CN-CELEB
Latest papers with no code
Who is Authentic Speaker
Therefore our experiments are geared towards recognising the source speakers given the converted voices, which are generated by using FragmentVC on the randomly paired utterances from source and target speakers.
Certification of Speaker Recognition Models to Additive Perturbations
In this paper, we pioneer applying robustness certification techniques to speaker recognition, originally developed for the image domain.
TIMIT Speaker Profiling: A Comparison of Multi-task learning and Single-task learning Approaches
This study employs deep learning techniques to explore four speaker profiling tasks on the TIMIT dataset, namely gender classification, accent classification, age estimation, and speaker identification, highlighting the potential and challenges of multi-task learning versus single-task models.
Artificial Neural Networks to Recognize Speakers Division from Continuous Bengali Speech
In this paper, we presented a method that will provide a speakers geographical identity in a certain region using continuous Bengali speech.
Voice Conversion Augmentation for Speaker Recognition on Defective Datasets
Our experimental results on three created datasets demonstrated that VCA-NN effectively mitigates these dataset problems, which provides a new direction for handling the speaker recognition problems from the data aspect.
Asymmetric and trial-dependent modeling: the contribution of LIA to SdSV Challenge Task 2
The SdSv challenge Task 2 provided an opportunity to assess efficiency and robustness of modern text-independent speaker verification systems.
Cosine Scoring with Uncertainty for Neural Speaker Embedding
Uncertainty modeling in speaker representation aims to learn the variability present in speech utterances.
Post-Training Embedding Alignment for Decoupling Enrollment and Runtime Speaker Recognition Models
Automated speaker identification (SID) is a crucial step for the personalization of a wide range of speech-enabled services.
Voxceleb-ESP: preliminary experiments detecting Spanish celebrities from their voices
This paper presents VoxCeleb-ESP, a collection of pointers and timestamps to YouTube videos facilitating the creation of a novel speaker recognition dataset.
Vulnerability of Automatic Identity Recognition to Audio-Visual Deepfakes
From the publicly available speech dataset LibriTTS, we also created a separate database of only audio deepfakes LibriTTS-DF using several latest text to speech methods: YourTTS, Adaspeech, and TorToiSe.
