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检索条件"主题词=Linear Predictive Coding"

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A 450bps Speech coding Algorithm Based on Multi-Mode Matrix Quantization

A 450bps Speech Coding Algorithm Based on Multi-Mode Matrix ...

引用

Congress on Image and Signal Processing, CISP

作者： Xia Zou Xiongwei Zhang People''s Liberation Army University of Science and Technology Nanjing China

A 450 bps speech coder based on multi-frame structure and multi-mode matrix quantization is presented. The multiframe structure consisting of four frames is adopted to reduce the algorithm delay. The parameter matrices are classified into different modes based on the voicing vector information of superframe. To improve speech quality, a dynamic bit allocation scheme is developed. Experimental results show that the speech quality of the proposed vocoder is intelligible with good naturalness.

关键词： Speech coding Quantization Bit rate linear predictive coding Autocorrelation Low pass filters Frequency Programmable logic arrays Delay Vocoders

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Partitioned Feature-based Classifier model

Partitioned Feature-based Classifier model

引用

IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)

作者： Dong-Chul Park Department of Information Engineering Myongji University Yongin si South Korea

The Partitioned Feature-based Classifier (PFC) is proposed in this paper. PFC does not use entire feature vectors extracted from the original data at once to classify each datum, but use only groups of features related to each feature vector to classify data separately. In the training stage, the contribution rate calculated from each feature vector group is drawn throughout the accuracy of each feature vector group and then, in the testing stage, the final classification result is obtained by applying weights corresponding to the contribution rate of each feature vector group. The proposed PFC algorithm is applied to two audio data classification problems, a speech/music data classification problem and a music genre classification problem. The results demonstrate that conventional clustering algorithms can improve their classification accuracy when the proposed PFC model is used with them.

关键词： Feature extraction Music Data mining Multiple signal classification Speech Discrete wavelet transforms linear predictive coding Cepstrum Clustering algorithms Brightness

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An auditory BCI using voluntary mental response

An auditory BCI using voluntary mental response

引用

International IEEE/EMBS Conference on Neural Engineering, CNE

作者： Jing Guo Bo Hong Fei Guo Xiaorong Gao Shangkai Gao Department of Biomedical Engineering School of Medicine Tsinghua University Beijing China

A novel brain computer interface (BCI) is implemented in this study, which only depends on auditory modality. The subjects voluntary recognition of the property (e.g. voice laterality) of a target human voice makes the discriminability between brain responses to target and non-target voices in a random sequence. EEG data from eight subjects showed that the amplitude of N2 and late positive component (LPC) elicited by target voice was significantly higher than that by non-target ones. The area of N2 and LPC component was used as features for identifying the target among digit numbers 1-8, achieving an average accuracy of 89%.

关键词： Electroencephalography Electrodes linear predictive coding Human voice Auditory system USA Councils Brain computer interfaces Testing Neural engineering Enterprise resource planning

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A Research on Recognition of Tibetan Speakers Based on MFCC and Delta Features

A Research on Recognition of Tibetan Speakers Based on MFCC ...

引用

International Forum on Computer Science-Technology and Applications (IFCSTA)

作者： Yu Hongzhi China Minorities Information Technology Institute Northwest University for Nationalities Lanzhou Gansu China

Through experiment, the paper analyses and extracts MFCC and delta features of different Tibetan speakers and makes comparison. It shows that MFCC has certain stability between frames of the same speaker, while delta ... 详细信息

关键词： Mel frequency cepstral coefficient Speaker recognition Loudspeakers Feature extraction Speech recognition linear predictive coding Ear Data mining Character recognition Cepstral analysis

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Voice singer detection in polyphonic music

Voice singer detection in polyphonic music

引用

IEEE International Conference on Electronics, Circuits and Systems (ICECS)

作者： Hassan Ezzaidi Mohammed Bahoura ERMETIS DSA Université du Québecá Chicoutimi Quebec Canada DIMG Université du Québecá Chicoutimi Quebec Canada

ISBN: (纸本)9781424450909;9781424450916

Song and music discrimination play a significant role in multimedia applications such as genre classification and singer identification. The problem of identifying sections of singer voice and instruments is addressed in this paper. A set of classification techniques based on features extracted from the auditory models, which are commonly used in the speech and speaker recognition domains, are investigated in this paper. All the proposed approaches, assuming no knowledge of song and music segments, use only a threshold based distance measure for discrimination. Particularly, it is observed that certain approaches are more appropriate for tracking the singer, while others are more appropriate for detecting the transition from music to the singer and vice versa. The experimental data are extracted from the music genre database RWC including various styles.

关键词： Databases Instruments Loudspeakers Mel frequency cepstral coefficient linear predictive coding Speech recognition Data mining Support vector machines Support vector machine classification Multiple signal classification

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Jawi Character Speech-to-Text Engine Using linear predictive and Neural Network for Effective Reading

Jawi Character Speech-to-Text Engine Using Linear Predictive...

引用

Asia International Conference on Modeling & Simulation

作者： Zaini Arifah Othman Zaidi Razak Nor Aniza Abdullah Mohd. Yakub Zulkifli Bin Mohd. Yusoff Faculty of Computer Science and Information Technology Academy of Islamic Studies University of Malaya Kuala Lumpur Malaysia

Jawi is an old version of Malay language writing that need to be preserved. Therefore, it is important to develop tools for teaching kids about Jawi characters and speech-to-text (STT) application can serve this purpose well. Unlike English, Jawi uses special characters similar to Arabic characters. However, its pronunciations are in Malay language. This uniqueness makes STT development a challenging task. In this paper, we investigate the applicability of linear predictive coding to extract important features from voice signal and neural network with backpropagation to classify and recognize spoken words into Jawi characters. A total of 225 samples of words in Jawi characters are recorded from speakers with over 95% accuracy. Jawi characters speech-to-text engine aims to help students to read Jawi document accurately and independently without the need for close monitoring from parents or teachers.

关键词： Engines Neural networks Natural languages Writing Education linear predictive coding Feature extraction Backpropagation Character recognition Speech recognition

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Parameteric coding of speech signals

Parameteric coding of speech signals

引用

International Conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Vivek Kumar Sehgal Shilpy Arora Sahil Jain Shantanu Agarwal Ujjawal Khandelwal Karan Jain Department of ECE Jaypee University of Information Technology Solan India Department of CSE and IT Jaypee University of Information Technology Solan India Hindustan College of Science and Technology Agra India

In this paper an FS1015 LPC coder has been designed using Matlab to produce intelligible speech. This paper focuses on the different methods of implementation and compared to determine, which gives the best performance. The coder has been tested on Hindi. Subjective mean opinion scores have been used to measure the speech quality based on the score given by the listeners.

关键词： Speech coding linear predictive coding Bit rate Speech synthesis Digital filters Quantization Information technology Vocoders Decoding Mathematical model

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Joint estimation of short-term and long-term predictors in speech coders

Joint estimation of short-term and long-term predictors in s...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Daniele Giacobello Mads Graesboll Christensen Joachim Dahl Soren Holdt Jensen Marc Moonen Department of Electronic Systems (ES-MISP) University of Aalborg Aalborg Denmark Department of Electrical Engineering (ESAT-SCD) Katholieke Universiteit Leuven Leuven Belgium

In low bit-rate coders, the near-sample and far-sample redundancies of the speech signal are usually removed by a cascade of a short-term and a long-term linear predictor. These two predictors are usually found in a sequential and therefore suboptimal approach. In this paper we propose an analysis model that jointly finds the two predictors by adding a regularization term in the minimization process to impose sparsity constraints on a high order predictor. The result is a linear predictor that can be easily factorized into the short-term and long-term predictors. This estimation method is then incorporated into an algebraic code excited linear prediction scheme and shows to have a better performance than traditional cascade methods and other joint optimization methods, offering lower distortion and higher perceptual speech quality.

关键词： Speech analysis Speech synthesis Redundancy predictive models Speech coding Error correction Signal analysis Quantization Optimization methods linear predictive coding

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Steganalysis of the MELP quantization index modulation data hiding methods by using chaotic type features

Steganalysis of the MELP quantization index modulation data ...

引用

IEEE Signal Processing and Communications Applications (SIU)

作者： A. Utku Yargicoglu H. Gokhan Ilk Elektronik Muhendisligi Bolumu Muhendislik Fakultesi Ankara Universitesi Turkey

The success of data hiding methods, which hide data to media like speech signal, is primarily determined by their strength aganist to the steganalysis methods. In this paper, some data hiding methods, which embed secret data during MELP analysis of speech signal using quantization index modulation are introduced. These methods in question are examined by a steganalysis method which takes advantage of chaotic-type features of speech signal. Thus, by evaluating the steganalysis results, the practical usage limitations of data hiding methods can be exposed.

关键词： Quantization Data encapsulation Chaos Speech analysis Data analysis Signal analysis Phase change materials linear predictive coding Reactive power

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Glottal closure instant detection using Lines of Maximum Amplitudes (LOMA) of thewavelet transform

Glottal closure instant detection using Lines of Maximum Amp...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Nicolas Sturmel Christophe d'Alessandro Francois Rigaud LIMSI/CNRS ORSAY CEDEX FRANCE

The Lines Of Maximum Amplitude (LOMA) of the wavelet transform are used for glottal closure instant detection. Following Kadambe & al. (1992), the wavelet transform modulus maxima can be used for singularity detection. The LOMA method extends this idea. All the lines chaining maxima of a wavelet transform across scales are built. Then a back-tracking procedure allows for selection of the optimal line for each pitch period, the top of which indicates the GCI. The LOMA method is then evaluated by comparing its results to the DYPSA (Naylor & al.) algorithm, with the option of using inverse filtering as preprocessing. The LOMA method compares favorably to DYPSA, particularly on accuracy. One of the advantage of the LOMA method is its ability to deal with variations in the glottal source parameters.

关键词： Wavelet transforms linear predictive coding Speech analysis Filtering algorithms Speech processing Speech synthesis Frequency synthesizers Nonlinear filters Delay Robustness

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