Zobrazeno 1 - 10
of 14 220
pro vyhledávání: '"Speaker recognition"'
Autor:
Piotr Staroniewicz
Publikováno v:
International Journal of Electronics and Telecommunications, Vol vol. 70, Iss No 3, Pp 615-620 (2024)
Research work on the effectiveness of voice disguise techniques is important for the development of biometric systems (surveillance) as well as phonoscopic research (forensics). A speaker recognition system or a listener can be deliberately or non-de
Externí odkaz:
https://doaj.org/article/7816be0b183e4eff9adcc921776acb4b
Autor:
Gökay Dişken, Barış Aydın
Publikováno v:
Uludağ University Journal of The Faculty of Engineering, Vol 29, Iss 1, Pp 191-204 (2024)
Ensuring security in speaker recognition systems is crucial. In the past years, it has been demonstrated that spoofing attacks can fool these systems. In order to deal with this issue, spoof speech detection systems have been developed. While these s
Externí odkaz:
https://doaj.org/article/b59b9e17a5b24a909f0d10ec8b57d49b
Autor:
Omar Ratib Khazaleh, Leen Ahmed Khrais
Publikováno v:
Journal of Engineering and Applied Science, Vol 71, Iss 1, Pp 1-24 (2024)
Abstract This paper studies the performance and reliability of deep learning-based speaker recognition schemes under various recording situations and background noise presence. The study uses the Speaker Recognition Dataset offered in the Kaggle webs
Externí odkaz:
https://doaj.org/article/04e605264e9143d89cf899b6d671c6e9
Publikováno v:
IEEE Access, Vol 12, Pp 82949-82971 (2024)
Speaker embeddings are ubiquitous, with applications ranging from speaker recognition and diarization to speech synthesis and voice anonymization. The amount of information held by these embeddings lends them versatility but also raises privacy conce
Externí odkaz:
https://doaj.org/article/0ddad9e46c0c40ffb71513cb0fa3ee20
Autor:
Alberto Yoshihiro Nakano, Hélio Rodrigues da Silva, Julian Rodrigues Dourado, Felipe Walter Dafico Pfrimer
Publikováno v:
Semina: Ciências Exatas e Tecnológicas, Vol 45 (2024)
A small Brazilian speech corpus was created for educational purposes to study a state-of-the-art speaker recognition system. The system uses the Gaussian Mixture Model (GMM) as a statistical model for speakers and employs the Mel-frequency cepstral c
Externí odkaz:
https://doaj.org/article/977480f0971543cd952653f1e63e4932
Publikováno v:
مجله مدل سازی در مهندسی, Vol 21, Iss 75, Pp 1-18 (2023)
Speaker recognition is a process of recognizing persons based on their voice which is widely used in many applications. Although many researches have been performed in this domain, there are some challenges that have not been addressed yet. In this r
Externí odkaz:
https://doaj.org/article/767fcfe0390b4ac59bcd31539d0a6ebc
Publikováno v:
Frontiers in Artificial Intelligence, Vol 7 (2024)
This study assessed the influence of speaker similarity and sample length on the performance of an automatic speaker recognition (ASR) system utilizing the SpeechBrain toolkit. The dataset comprised recordings from 20 male identical twin speakers eng
Externí odkaz:
https://doaj.org/article/5d390e0020ad4f0f802478e57d5426c5
Autor:
Zhiyong Chen, Shugong Xu
Publikováno v:
EURASIP Journal on Audio, Speech, and Music Processing, Vol 2023, Iss 1, Pp 1-17 (2023)
Abstract Speaker recognition, the process of automatically identifying a speaker based on individual characteristics in speech signals, presents significant challenges when addressing heterogeneous-domain conditions. Federated learning, a recent deve
Externí odkaz:
https://doaj.org/article/ce507c02ff854c68a668b34eebb84c3b
Publikováno v:
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), Vol 7, Iss 4, Pp 832-836 (2023)
Speaker recognition is a field of research that continues to this day. Various methods have been developed to detect the human voice with greater precision and accuracy. Research on human speech recognition that is quite challenging is accent recogni
Externí odkaz:
https://doaj.org/article/1414c68553fa4dbc867a65b5a6455963
Autor:
Starlet Ben Alex, Leena Mary
Publikováno v:
ETRI Journal, Vol 45, Iss 4, Pp 678-689 (2023)
This paper describes a novel end-to-end deep generative model-based speaker recognition system using prosodic features. The usefulness of variational autoencoders (VAE) in learning the speaker-specific prosody representations for the speaker recognit
Externí odkaz:
https://doaj.org/article/385e84b5cef94c2a97de5507e46ef1f5