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Proceedings ArticleDOI

Efficient coding of LPC parameters by temporal decomposition

Bishnu S. Atal
- Vol. 8, pp 81-84
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TLDR
The aim is to determine the extent to which the bit rate of LPC parameters can be reduced without sacrificing speech quality.
Abstract
This paper describes a method for efficient coding of LPC log area parameters. It is now well recognized that sample-by-sample quantization of LPC parameters is not very efficient in minimizing the bit rate needed to code these parameters. Recent methods for reducing the bit rate have used vector and segment quantization methods. Much of the past work in this area has focussed on efficient coding of LPC parameters in the context of vocoders which put a ceiling on achievable speech quality. The results from these studies cannot be directly applied to synthesis of high quality speech. This paper describes a different approach to efficient coding of log area parameters. Our aim is to determine the extent to which the bit rate of LPC parameters can be reduced without sacrificing speech quality. Speech events occur generally at non-uniformly spaced time intervals. Moreover, some speech events are slow while others are fast. Uniform sampling of speech parameters is thus not efficient. We describe a non-uniform sampling and interpolation procedure for efficient coding of log area parameters. A temporal decomposition technique is used to represent the continuous variation of these parameters as a linearly-weighted sum of a number of discrete elementary components. The location and length of each component is automatically adapted to speech events. We find that each elementary component can be coded as a very low information rate signal.

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Citations
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Low Bit Rate Speech Coding

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Hierarchical temporal decomposition: a novel approach to efficient compression of spectral characteristics of speech.

TL;DR: The method models the articulatory dynamics employing a hierarchical error minimization algorithm which does not use Singular Value Decomposition to comply with the desired coding requirements, such as compression ratio, accuracy, delay, and computational complexity.
Book ChapterDOI

Speech Recognition of Assamese Numerals Using Combinations of LPC - Features and Heterogenous ANNs

TL;DR: A fully automated and effective method of detection of Assamese numerals captured under varied recording conditions and moods is presented here.
Journal ArticleDOI

Group-based spatio-temporal video analysis and abstraction using wavelet parameters

TL;DR: This paper utilizes event-based temporal decomposition technique to resolve the overlapping arrangement of the video signal that is known to be one of the main concerns in video analysis via conventional frame-based schemes.
References
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Book

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TL;DR: This paper presents a meta-modelling framework for digital Speech Processing for Man-Machine Communication by Voice that automates the very labor-intensive and therefore time-heavy and expensive process of encoding and decoding speech.
Book

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John E. Markel, +1 more
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Journal ArticleDOI

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TL;DR: Application of this method for efficient transmission and storage of speech signals as well as procedures for determining other speechcharacteristics, such as formant frequencies and bandwidths, the spectral envelope, and the autocorrelation function, are discussed.
Journal ArticleDOI

Predictive Coding of Speech at Low Bit Rates

TL;DR: A new class of speech coders are described which allow one to realize the precise optimum noise spectrum which is crucial to achieving very low bit rates, but also represent the important first step in bridging the gap between waveform coders and vocoders without suffering from their limitations.