Research ArticleOpen accessPhrase in the titleSpeaker Recognition Using Spectral Cross-correlation: A Fast AlgorithmZoubir HamiciThis study presents an original algorithm for computing the cross-correlation function applied for speech recognition A spectral correlation estimation algorithm based on the comparing the magnitude spectrum of the two signals is presented. The number of samples is reduced by a factor of two, after eliminating the image spectrum. A moving average filter is used to smooth the magnitude spectrum … …Journal of Computer Science, Vol. 1, Issue 2 · 19 Oct 2005 · 5,013 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA New Speaker Recognition System with Combined Feature Extraction TechniquesM. G. Sumithra, K. Thanuskodi, A. Helen Jenifer ArchanaProblem statement: This study introduces a new method for speaker verification system by fusing two different feature extraction methods to improve the recognition accuracy and security. Approach: The proposed system uses Mel frequency cepstral coefficients for speaker identification and Modified MFCC for verification. For speaker modeling vector quantization is used. Results: The proposed system was investigated the effect of the … …Journal of Computer Science, Vol. 7, Issue 4 · 4 Apr 2011 · 7,424 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleArabic Speaker Recognition: Babylon Levantine Subset Case StudyMansour Alsulaiman, Youssef Alotaibi, Muhammad Ghulam et al.Problem statement: Researchers on Arabic speaker recognition have used local data bases unavailable to the public. In this study we would like to investigate Arabic speaker recognition using a publically available database, namely Babylon Levantine available from the Linguistic Data Consortium (LDC). Approach: Among the different methods for speaker recognition we focus on Hidden Markov Models (HMM). We studied the … …Journal of Computer Science, Vol. 6, Issue 4 · 30 Apr 2010 · 7,243 accessesView PDFCite
Research ArticleOpen accessIn the keywordsSpeaker Identification: A Hybrid Approach Using Neural Networks and Wavelet TransformMuzhir Shaban Al-Ani, Thabit Sultan Mohammed, Karim M. AljeboryIn speaker identification systems, a database is constructed from the speech samples of known speakers. The approach implemented in this paper is hybrid, where the wavelet transform and neural networks are used together to form a system with improved performance. Features are extracted by applying a discrete wavelet transform (DWT), while a neural network (NN) is used for formulating the … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 7,072 accessesView PDFCite
Research ArticleOpen accessIn the abstractUzNER: A Human-Reviewed Benchmark for Uzbek Named Entity Recognition With Gazetteer-Augmented Transformer ModelsBobur Saidov, Vladimir Barakhnin et al.UzNER-100K is a large-scale human-reviewed benchmark for Uzbek named entity recognition with 100,000 training sentences, 18 fine-grained entity types and 200,083 entity mentions across 114,269 sentences in total. The corpus was constructed through an LLM-assisted, expert-reviewed annotation pipeline that achieved strong reliability on the main audit subset while substantially reducing corpus-construction effort. The benchmark includes a standard test split, a … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,308 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Hybrid Speech Recognition System with Hidden Markov Model and Radial Basis Function Neural NetworkJudith Justin, Ila VennilaWe analyze the performance of continuous speech recognition of a speaker independent system using Hidden Markov Model and Artificial Neural Network. Modern speech recognition systems use different combinations of the standard techniques over the basic approach to improve performance accuracy. One such combination which has gained more attention is the hybrid model. Our hybrid system for continuous speech recognition consists … …American Journal of Applied Sciences, Vol. 10, Issue 10 · 5 Sep 2013 · 6,819 accessesView PDFCite
Research ArticleOpen accessIn the abstractAcoustic Model Adaptation for Indonesian Language Utterance Training SystemLinda Indrayanti, Yoshifumi Chisaki, Tsuyoshi UsagawaProblem statement: In order to build an utterance training system for Indonesian language, a speech recognition system designed for Indonesian is necessary. However, the system hardly works well due to the pronunciation variants of non-native utterances may lead to substitution/deletion error. This research investigated the pronunciation variant and proposes acoustic model adaptation to improve performance of the system. Approach: The … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 7,168 accessesView PDFCite