Time alignment in speech and speaker recognition by Antanas Lipeika, Joana Lipeikienė

“… Time scale alignment problems in speech and speaker recognition by voice are investigated. Dynamic programming approach to solution of this problem is discussed. …”
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Cross-linguistic rhythmic patterns in Persian-English bilingual speakers: Implications for speaker recognition by Homa Asadi, Maral Asiaee

“…This research has implications for understanding bilingual speech production and enhancing speaker recognition technology.…”
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A Hierarchical Framework Approach for Voice Activity Detection and Speech Enhancement by Yan Zhang, Zhen-min Tang, Yan-ping Li, Yang Luo

“…Accurate and effective voice activity detection (VAD) is a fundamental step for robust speech or speaker recognition. In this study, we proposed a hierarchical framework approach for VAD and speech enhancement. …”
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Multitask Learning with Local Attention for Tibetan Speech Recognition by Hui Wang, Fei Gao, Yue Zhao, Li Yang, Jianjian Yue, Huilin Ma

“…With an increase in task number, such as simultaneous Tibetan speech content recognition, dialect identification, and speaker recognition, the accuracy rate of a single WaveNet-CTC decreases on speech recognition. …”
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Phoneme analysis for multiple languages with fuzzy‐based speaker identification by Thales Aguiar deLima, Márjory Cristiany Da‐Costa Abreu

“…Also, this paper expands the research study of fuzzy models in the speaker recognition field, using a Fuzzy C‐Means and Fuzzy k‐Nearest Neighbours and comparing them with k‐Nearest Neighbours and Support Vector Machines. …”
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A Robust Approach for Speaker Identification Using Dialect Information by Shahid Munir Shah, Muhammad Moinuddin, Rizwan Ahmed Khan

“…The results show that the proposed framework is better in terms of average speaker recognition accuracy (84.5% identification accuracy) and consumes 39% less time for the identification of speaker.…”
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Enhancing depression recognition through a mixed expert model by integrating speaker-related and emotion-related features by Weitong Guo, Qian He, Ziyu Lin, Xiaolong Bu, Ziyang Wang, Dong Li, Hongwu Yang

“…Our approach begins with a Time Delay Neural Network to pre-train a speaker-related feature extractor using a large-scale speaker recognition dataset while simultaneously pre-training a speaker’s emotion-related feature extractor with a speech emotion dataset. …”
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