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IEEE International Conference on Acoustics, Speech, and Signal Processing

作者： Lashkari, K Miki, T DoCoMo USA Labs Inc San Jose CA 95110 USA

ISBN: (纸本)0780374029

This paper presents a new Analysis-by-Synthesis (AbS) technique for joint optimization of the excitation and model parameters based on minimizing the closed loop synthesis error instead of the linear prediction error. By minimizing the synthesis error, the analysis and synthesis stages become more compatible. Using a gradient search in the root domain, model parameters for a given excitation are optimized to minimize the error between the original and the synthesized speech. Since the optimization starts from the LPC solution, the synthesis error is guaranteed to be lower than that obtained using the LPC coefficients. For multipulse LPC, there is a 0.5-1 dB improvement in the segmental SNR for male and female speakers over 4 to 6 second long sentences. Listening tests and objective MOS scores confirm the improved speech quality. By adding an extra optimization step, the technique can be incorporated into the LPC, multi-pulse LPC and CELP-type speech coders.

关键词： speech coding vocoders linear predictive coding optimisation speech enhancement speech synthesis minimisation gradient methods search problems joint optimization parametric speech coders analysis-by-synthesis technique excitation parameters model parameters closed loop synthesis error minimization gradient search multipulse LPC segmental SNR listening tests objective MOS scores improved speech quality CELP-type speech coders

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Classification of Speaker Accent using Hybrid DWT-LPC Features and K-Nearest Neighbors in Ethnically Diverse Malaysian English

Classification of Speaker Accent using Hybrid DWT-LPC Featur...

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IEEE Symposium on Computer Applications and Industrial Electronics (ISCAIE)

作者： Yusnita, M. A. Paulraj, M. P. Yaacob, Sazali Shahriman, A. B. Univ Teknol MARA Fac Elect Engn Permatang Pauh 13500 P Pinang Malaysia Univ Malaysia Perlis Sch Mechatron Engn Ulu Pauh 02600 Malaysia

ISBN: (纸本)9781467330336;9781467323024

Accent is a major cause of variability in automatic speaker-independent speech recognition systems. Under certain circumstances, this event introduces unsatisfactory performance of the systems. In order to circumvent this deficiency, accent analyzer in preceding stage could be a smart solution. This paper proposes a rather new approach of hybrid way to optimize the extraction of accent from speech utterances over other facets using linear predictive coefficients (LPC) derived from discrete wavelet transform (DWT). The constructed features were used to model an accent recognizer, implemented based on K-nearest neighbors. Experimental results showed that the hybrid dyadic-X DWT-LPC features were highly correlated to the Malay, Chinese and Indian accents of Malaysian English speakers through an increase of classification rate of 9.28% over the conventional LPC method.

关键词： Discrete Wavelet Transform linear predictive coding Accent Classification K-nearest Neighbors Malaysian English

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Speech recognition chip for monosyllables

Speech recognition chip for monosyllables

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Asia and South Pacific Design Automation Conference (ASP-DAC 2001)

作者： Nakamura, K Zhu, Q Maruoka, S Horiyama, T Kimura, S Watanabe, K Nara Inst Sci & Technol Grad Sch Informat Sci Nara 6300101 Japan

ISBN: (纸本)0780366336

In the paper, we present a real-time speech recognition chip for monosyllables such as A, B,.,., etc. The chip recognizes up to 64 monosyllables based on the Hidden Markov Model (HMM), which is a well known speaker-independent recognition method. The chip accepts a short-speech frame including 256 16-bit digitized samples corresponding to 11.6 msec period, and outputs the 6-bit symbol code of monosyllables for 16 short-frames (corresponding to 185.6 msec), A learning circuit to update HMM parameters for the recognition chip has also been designed, and the recognition chip includes an interface to the learning circuit. We have fabricated the recognition chip by VDEC Rohm 0.6 mum process on a 4.5 mm x 4.5 mm chip. We have also made a layout of the entire circuit including the learning circuit by VDEC Rohm 0.35 mum process on a 4.9 mm x 4.9 mm chip.

关键词： Algorithm design and analysis Circuits Feature extraction Hardware Hidden Markov models linear predictive coding Speech analysis Speech coding Speech recognition Vectors

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Voiced/Unvoiced Classification Recovery in the Speech Decoder Based on GMM

Voiced/Unvoiced Classification Recovery in the Speech Decode...

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9th International Conference on Signal Processing

作者： Wei Xuan Dang Xiaoyan Cui Huijuan Tang Kun Tsinghua Univ Dept Elect Engn State Key Lab Microwave & Digital Commun Beijing 100084 Peoples R China

ISBN: (纸本)9781424421787

Voiced/Unvoiced (V/U) classification is an important parameter in low bit-rate speech coding algorithms. An algorithm that recovers the V/U classification from the linear prediction coding (LPC) coefficients and the gain in the speech decoder is proposed. Two Gaussian mixture models (GMM) are employed to model the joint probability of these parameters and to perform the V/U estimation. Experiments show the performance improvements of the proposed algorithm over the V/U classifier used in mixed excitation LPC vocoder (MELP). The proposed algorithm operates only at the receiving end and saves all the bits originally used for V/U quantization.

关键词： Decoding linear predictive coding Speech coding Databases Pattern recognition Quantization Speech synthesis Cepstral analysis Probability distribution Laboratories

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Variable dimension matrix quantization of LSP parameters for very low bit rate vocoder below 300bps

Variable dimension matrix quantization of LSP parameters for...

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9th International Conference on Signal Processing

作者： Min Gang Yang Ji-bin Chen Yan-pu Zhang Xiong-wei Institute of communications engineering People''s Liberation Army University of Science and Technology China Xian Communication Institute China

ISBN: (纸本)9781424421787

This paper examines the efficient quantization of LSP parameters for very low bit rate vocoder below 300bps, a new quantization scheme called variable dimension matrix quantization (VDMQ) is presented In the VDMQ scheme, the extracted LSP parameters matrix with variable dimension is quantized directly without dimension conversion. Based on the distance measure definition between low LSP matrices with different dimension, the optimal codeword is deduced Theoretical analysis and experiment results show that the VDMQ scheme performs better than the segment quantization and matrix quantization scheme at very low bit rate. Also, the codebook storage is almost reduced by 90%. The VDMQ scheme provides a new effective approach for efficient LSP parameters quantization at very low bit rate.

关键词： Bit rate Vocoders Speech Vector quantization linear predictive coding Programmable logic arrays Performance analysis Wireless communication Artificial satellites Underwater communication

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Design and performance of a 4.0 kbit/s speech coder based on Frequency-Domain Interpolation

Design and performance of a 4.0 kbit/s speech coder based on...

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7th IEEE Workshop on Speech coding

作者： Bhaskar, U Nandkumar, S Swaminathan, K Hughes Network Syst Germantown MD 20876 USA

ISBN: (纸本)0780364163

The 4.0 kbit/s speech codec described in this paper is based on a Frequency Domain Interpolative (FDI) coding technique, which belongs to the class of prototype waveform Interpolation (PM;I) coding techniques. The codec also has an integrated voice activity detector (VAD) and a noise reduction capability. The input signal is subjected to LPC analysis and the prediction residual is separated into a slowly evolving waveform (SEW) and a rapidly evolving waveform (REW) components. The SEW magnitude component is quantized using a hierarchical predictive vector quantization approach. The REW magnitude is quantized using a gain and a sub-band based shape. SEW and REW phases are derived at the decoder using a phase model. based on a transmitted measure of voice periodicity. The spectral (LSP) parameters are quantized using a combination of scalar and vector quantizers. The 4.0 kbits/s coder has an algorithmic delay of 60 ms and an estimated floating point complexity of 21.5 MIPS. The performance of this coder has been evaluated using in-house MOS tests under various conditions such as background noise, channel errors, self-tandem, and DTX mode of operation. and has been shown to be statistically equivalent to ITU-T G.729 kbps codec across all conditions tested.

关键词： Automatic testing Delay estimation Detectors Fault detection Frequency domain analysis Interpolation linear predictive coding Noise reduction Prototypes Speech codecs

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Online Machine Learning Experiments in HTML5 48

Online Machine Learning Experiments in HTML5

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48th IEEE Frontiers in Education Conference (FIE)

作者： Dixit, Abhinav Shanthamallu, Uday Shankar Spanias, Andreas Berisha, Visar Banavar, Mahesh ASU Sch ECEE SenSIP Ctr Tempe AZ 85287 USA Clarkson Univ Dept ECE Potsdam NY 13676 USA

ISBN: (纸本)9781538611746

This work in progress paper describes software that enables online machine learning experiments in an undergraduate DSP course. This software operates in HTML5 and embeds several digital signal processing functions. The software can process natural signals such as speech and can extract various features, for machine learning applications. For example in the case of speech processing, LPC coefficients and formant frequencies can be computed. In this paper, we present speech processing, feature extraction and clustering of features using the K-means machine learning algorithm. The primary objective is to provide a machine learning experience to undergraduate students. The functions and simulations described provide a user-friendly visualization of phoneme recognition tasks. These tasks make use of the Levinson-Durbin linear prediction and the K-means machine learning algorithms. The exercise was assigned as a class project in our undergraduate DSP class. The description of the exercise along with assessment results is described.

关键词： Machine Learning Speech recognition linear predictive coding Online labs

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A comparison between speech signal representation using linear prediction and Gabor transform 9

A comparison between speech signal representation using line...

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9th Asia-Pacific Conference on Communications held in conjunction with the 6th Malaysia International Conference on Communications (MICC 2003)

作者： Tahir, SM Sha'ameri, AZ Univ Teknol Malaysia Fac Elect Engn Digital Signal Proc Lab Skudai 81310 Malaysia

ISBN: (纸本)0780381149

Feature extraction from speech representation is one of the processes in speech recognition. Parametric modeling. is a dominant approach to model speech signals. Within a localized interval, speech representation is equivalent to a noise driven output from an all-pole system that can be estimated using linear prediction. Besides the characteristics of speech, temporal variability of speech signal model is also due to the computation of linear prediction coefficients. Thus, an alternative representation is proposed based on the Gabor coefficients. In this paper, a comparison is made with the linear prediction coefficients to show the consistency of the parameters that are generated for implementation in the speech recognition system.

关键词： Cepstral analysis Digital signal processing Feature extraction linear predictive coding Nonlinear filters predictive models Random processes Signal representations Speech processing Speech recognition

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Line/Polygon Classification: A Study of the Complexity of Geometric Computation

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IEEE Computer Graphics and Applications 1981年第2期1卷 75-84页

作者： Tilove, Robert B. University of Rochester United States

Illuminating the techniques of computational geometry, an analysis of two LPC algorithms compares their efficiency for handling polygon-clipping problems.

关键词： linear predictive coding Computer graphics Application software Algorithm design and analysis Computer applications Computer aided manufacturing CADCAM Computational geometry Solids Interference

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Effect of the vocal tract yielding sidewall on inverse filter analysis of the glottal waveform

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Journal of Voice 1988年第4期2卷 271-278页

作者： Milenkovic, Paul Mo, Feng Department of Electrical and Computer Engineering University of Wisconsin Madison WI United States

The inverse filter is a serial cascade of filter elements with a transfer function that cancels the effect of the poles of the vocal tract transfer function on the acoustic waveform to reveal the underlying glottal volume velocity waveform. Inaccuracies in the glottal wave reconstruction derived from an all-zero inverse filter can be attributed to deviations of the vocal tract transfer function from an all-pole model. Presented is an analysis of the error stemming from the effect of the yielding vocal tract sidewalls on the vocal tract transfer function. Predictions about the resulting artifacts in the estimated glottal volume velocity are derived from an acoustic model. These predictions are confirmed by applying a linear predictive coding (LPC) inverse filter analysis method to vowels synthesized using a transmission line model of the vocal tract containing yielding sidewall parameters as well as natural productions of nonnasalized vowels. © 1988 Raven Press, Ltd., New York.

关键词： Inverse filter linear predictive coding Vocal tract Yielding Wall

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