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This This research constructs a phonetic feature (PF) table for all the phonemes pronounced in Bangla (widely known as Bengali) language where the whole study is divided into two parts. In the first part, a PF table is constructed, while the second part deals with Bangla automatic speech recognition (ASR) using PFs. For Bangla language, fifty three phonemes including both vowels and consonants are...
Efficiency of the speech recognition system in noise free environment is impressive but in the presence of environmental noise the efficiency of the speech recognition system deteriorates drastically. Environmental noise also affects human-to-human or human-to-machine communications and degrades the speech quality as well as intelligibility. Here a speech recognition system is proposed in presence...
In order to help general technicians to recognize insects conveniently in pests management, this paper proposed a viable scheme to identify insect sounds automatically by using Sub-band based cepstral(SBC) and Hidden Markov Model(HMM). The acoustic signal is preprocessed, segmented into a series of sound samples. SBC is extracted from the sound sample as the feature, and HMMs are trained with given...
The problem of identification of noise sources in the ocean is of prime importance because of its diverse practical applications. Hidden Markov Models provide an effective architecture for the classification of underwater noise sources. A technique for the estimation of State Transition Matrix for a twenty state Hidden Markov Model for the classification of noise sources in the ocean is presented...
The paper represents a front-end process for changing esophageal speech features into normal speech features in order to improve a recognition rate of esophageal speech in a speech recognition system that training by normal speech corpus based on Hidden Markov Models (HMMs). A system, that combines feature conversion technique and cepstral normalization technique in order to prevent variation bias...
In this paper, we introduce a Hidden Markov Model (HMM) recognition system for the articulation features of Arabic phones. The low-level features are described by Mel-Frequency Cepstral Coefficients (MFCCs). The created HMMs directly model certain articulation features (fricative and plosive). Classification is done on these features regardless of the phone itself. The model has been created successfully...
In this paper we present our investigations on statistical classification of acoustic signals which is one special assignment in condition monitoring. We compare three pattern recognition methods and three selected feature extraction algorithms with regard to their capability to distinguish between structure-borne sound signatures emitted by intact and worn-out rollers in a drawframe. Our goal is...
This paper presents a technique for improving the performance of multi-stream HMMs in ASR systems. In this technique stream exponents of the multi-stream model are chosen with respect to the phonological content of the underlying states. Two distinctive feature sets namely MFCCs and formant-like features are used for investigating the potential of this technique. The experiments are performed on the...
The challenge of modern sensor systems is besides the tracking of targets more and more their classification. The knowledge of the target class has significant influence on the identification, threat evaluation and weapon assignment process of large systems. Especially, considering new types of threats in anti asymmetric warfare the knowledge of a target class has an important drawback. Also the target...
This paper describes continuous speech recognition experiments on a Romanian language speech database, by using hidden Markov models (EMM). We compare the recognition rates obtained in our ASR system realising front-ends based on features extracted by perceptual variants of cepstral analysis and linear prediction and by simple linear prediction. The best results obtained with 36 coefficients mel-frequency...
In this paper we analyse a speaker verification system with fixed uttered text for Romanian language. The feature extraction in the system is based on perceptual cepstral analysis, giving the melfrequency cepstral coefficients. The acoustical modeling of speech in the statistical framework is based on hidden Markov models. To assess performance of the system, the models were trained with each speaker...
This paper proposed a low-cost dual-ALU processor for speech recognition. It does not give an emphasis on sophistication but on low-cost solution. The dual-ALU architecture provides parallel calculation capability. For the consideration of chip size, the area of the second ALU is only half of the first ALU. We use hardware-software codesign method to implement the speech recognition. The feature extraction...
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