Data processing: speech signal processing – linguistics – language – Speech signal processing – For storage or transmission
Reexamination Certificate
1998-11-24
2001-05-29
Dorvil, Richemond (Department: 2641)
Data processing: speech signal processing, linguistics, language
Speech signal processing
For storage or transmission
C204S201000, C204S226000
Reexamination Certificate
active
06240386
ABSTRACT:
BACKGROUND
1. Technical Field
The present invention relates generally to speech encoding and decoding in voice communication systems; and, more particularly, it relates to various noise compensation techniques used with code-excited linear prediction coding to obtain high quality speech reproduction through a limited bit rate communication channel.
2. Description of Prior Art
Signal modeling and parameter estimation play significant roles in communicating voice information with limited bandwidth constraints. To model basic speech sounds, speech signals are sampled as a discrete waveform to be digitally processed. In one type of signal coding technique called LPC (linear predictive coding), the signal value at any particular time index is modeled as a linear function of previous values. A subsequent signal is thus linearly predictable according to an earlier value. As a result, efficient signal representations can be determined by estimating and applying certain prediction parameters to represent the signal.
Applying LPC techniques, a conventional source encoder operates on speech signals to extract modeling and parameter information for communication to a conventional source decoder via a communication channel. Once received, the decoder attempts to reconstruct a counterpart signal for playback that sounds to a human ear like the original speech.
A certain amount of communication channel bandwidth is required to communicate the modeling and parameter information to the decoder. In embodiments, for example where the channel bandwidth is shared and real-time reconstruction is necessary, a reduction in the required bandwidth proves beneficial. However, using conventional modeling techniques, the quality requirements in the reproduced speech limit the reduction of such bandwidth below certain levels.
Speech signals contain a significant amount of noise content. Traditional methods of coding noise often have difficulty in properly modeling noise which results in undesirable interruptions, discontinuities, and during conversation. Analysis by synthesis speech coders such as conventional code-excited linear predictive coders are unable to appropriately code background noise, especially at reduced bit rates. A different and better method of coding the background noise is desirable for good quality representation of background noise.
Further limitations and disadvantages of conventional systems will become apparent to one of skill in the art after reviewing the remainder of the present application with reference to the drawings.
SUMMARY OF THE INVENTION
Various aspects of the present invention can be found in a speech encoding system using an analysis by synthesis coding approach on a speech signal. The encoder processing circuit identifies a speech parameter of the speech signal using a speech signal analyzer. The speech signal analyzer may be used to identify multiple speech parameters of the speech signal. Upon processing these speech parameters, the speech encoder system classifies the speech signal as having either active or inactive voice content. Upon classification of the speech signal as having voice active content, a first coding scheme is employed for representing the speech signal. This coding information may be later used to reproduce the speech signal using a speech decoding system.
In certain embodiments of the invention, a weighted filter may filter the speech signal to assist in the identification of the speech parameters. The speech encoding system processes the identified speech parameters to determine the voice content of the speech signal. If voice content is identified, code-excited linear prediction is used to code the speech signal in one embodiment of the invention. If the speech signal is identified as voice inactive, then a random excitation sequence is used for coding of the speech signal. Additionally for voice inactive signals, an energy level and a spectral information are used to code the speech signal. The random excitation sequence may be generated in a speech decoding system of the invention. The random excitation sequence may alternatively be generated at the encoding end of the invention or be stored in a codebook. If desired, the manner by which the random excitation sequence was generated may be transmitted to the speech decoding system. However, in other embodiments of the invention the manner by which the random excitation sequence was generated may be omitted.
Further aspects of the invention may be found in a speech codec that performs the identification of noise in a speech signal and subsequently performs coding and decoding of the speech signal using noise compensation. Noise within the speech signal includes any noise-like signal in the speech signal, e.g. background noise or even the speech signal itself having a substantially noise-like characteristic. The noise insertion is used to assist in reproducing the speech signal in a manner that is substantially perceptually indistinguishable from the original speech signal.
The detection and compensation of the noise within both the raw speech signal and the reproduced speech signal may be performed in a distributed manner in various parts of the speech codec. For example, detection of noise in the speech signal may be performed solely in a decoder of the speech codec. Altematively, it may be performed partially in an encoder and the decoder. The compensation of noise of the reproduced speech signal may also be performed in such a distributed manner.
Other aspects, advantages and novel features of the present invention will become apparent from the following detailed description of the invention when considered in conjunction with the accompanying drawings.
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Benyassine Adil
Gao Yang
Su Huan-Yu
Thyssen Jes
Conexant Systems Inc.
Dorvil Richemond
Nolan Daniel A
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