Abstract: To provide a method of specifying each of speakers of individual voices, based on recorded voices made by a plurality of speakers, with a simple system configuration, and to provide a system using the method. The system includes: microphones individually provided for each of the speakers; a voice processing unit which gives a unique characteristic to each pair of two-channel voice signals recorded with each of the microphones 10, by executing different kinds of voice processing on the respective pairs of voice signals, and which mixes the voice signals for each channel; and an analysis unit which performs an analysis according to the unique characteristics, given to the voice signals concerning the respective microphones through the processing by the voice processing unit, and which specifies the speaker for each speech segment of the voice signals.

Abstract: A method and apparatus identify a clean speech signal from a noisy speech signal. The noisy speech signal is converted into frequency values in the frequency domain. The parameters of at least one posterior probability of at least one component of a clean signal value are then determined based on the frequency values. This determination is made without applying a frequency-based filter to the frequency values. The parameters of the posterior probability distribution are then used to estimate a set of frequency values for the clean speech signal. A clean speech signal is then constructed from the estimated set of frequency values.

Abstract: A method to achieve signals which are essentially devoid of unwanted signal components uses a search and comparison process. Media signals are received through receiving means, the media signals containing unwanted signal components, a representation for the media signals is chosen, and the media signals are processed in such a way that the unwanted signal components are essentially removed and the remaining signal components are saved.

Abstract: Method and system for generating electromyographic or sub-audible signals (“SAWPs”) and for transmitting and recognizing the SAWPs that represent the original words and/or phrases. The SAWPs may be generated in an environment that interferes excessively with normal speech or that requires stealth communications, and may be transmitted using encoded, enciphered or otherwise transformed signals that are less subject to signal distortion or degradation in the ambient environment.

Abstract: Configurations disclosed herein include systems, methods, and apparatus that may be applied in a voice communications and/or storage application to remove, enhance, and/or replace the existing context.

Abstract: A method and apparatus are provided for reducing noise in a signal. Under one aspect of the invention, a correction vector is selected based on a noisy feature vector that represents a noisy signal. The selected correction vector incorporates dynamic aspects of pattern signals. The selected correction vector is then added to the noisy feature vector to produce a cleaned feature vector. In other aspects of the invention, a noise value is produced from an estimate of the noise in a noisy signal. The noise value is subtracted from a value representing a portion of the noisy signal to produce a noise-normalized value. The noise-normalized value is used to select a correction value that is added to the noise-normalized value to produce a cleaned noise-normalized value. The noise value is then added to the cleaned noise-normalized value to produce a cleaned value representing a portion of a cleaned signal.

Abstract: A system and method are provided that reduce noise in speech signals. The system and method decompose a noisy speech signal into a harmonic component and a residual component. The harmonic component and residual component are then combined as a sum to form a noise-reduced value. In some embodiments, the sum is a weighted sum where the harmonic component is multiplied by a scaling factor. In some embodiments, the noise-reduced value is used in speech recognition.

Abstract: A system, method and computer-readable medium are disclosed for using filters signal processing. The system includes a module that calculates a filter for each of a plurality of frequency bands, a module that groups the filters into a plurality of groups, a module that determines a representative filter for each group of the plurality of groups and a module that uses the representative filter of each group for frequency bands of the each group. The filters are temporal noise shaping filters (TNS) filters.

Abstract: A first determiner 121 tentatively determines whether the current processing unit represents a stationary noise period, based on stationary properties of a decoded signal. Based on the tentative determination result and a determination result of the periodicity of the decoded signal, a second determiner 124 determines whether the current processing unit represents a stationary noise period, thereby distinguishing a decoded signal including a stationary speech signal such as a stationary vowel from stationary noise and correctly identifying the stationary noise period.

Abstract: A gain-constrained noise suppression for speech more precisely estimates noise, including during speech, to reduce musical noise artifacts introduced from noise suppression. The noise suppression operates by applying a spectral gain G(m, k) to each short-time spectrum value S(m, k) of a speech signal, where m is the frame number and k is the spectrum index. The spectrum values are grouped into frequency bins, and a noise characteristic estimated for each bin classified as a “noise bin.” An energy parameter is smoothed in both the time domain and the frequency domain to improve noise estimation per bin. The gain factors G(m, k) are calculated based on the current signal spectrum and the noise estimation, then smoothed before being applied to the signal spectral values S(m, k).

Abstract: In an acoustic signal encoding apparatus (100), a tonal noise verification unit (110) verifies whether the input acoustic time-domain signals are tonal or noisy. If the input acoustic time-domain signals are tonal, tonal component signals are extracted by a tonal component extraction unit (121), and tonal component parameters are normalized and quantized in a normalization/quantization unit (122). The residual time-domain signals, obtained on extracting the tonal component signals from the acoustic time-domain signals, are transformed by an orthogonal transforming unit (131) into the spectral information, which spectral information is normalized and quantized by a normalization/quantization unit (132). A code string generating unit (140) generates a code string from the quantized tonal component parameters and the quantized residual component spectral information.

Abstract: Disclosed are methods and systems for detecting boundaries between areas of different languages in a body of text.

Abstract: Minimizing the effects of the requisite AGWN packets on transmission channel utilization without diminishing any of the aesthetic quality of the AGWN white noise on the voice or audio communication.

Abstract: Techniques for evaluating the audio quality of an audio test signal are disclosed. These techniques provide a quality analysis that takes into account spatial audio distortions between the audio test signal and a reference audio signal. These techniques involve, for example, determining a plurality of audio spatial cues for an audio test signal, determining a corresponding plurality of audio spatial cues for an audio reference signal, comparing the determined audio spatial cues of the audio test signal to the audio spatial cues of the audio reference signal, and determining the audio quality of the audio test signal.

Abstract: A band division noise suppressor suppressing noise sufficiently with a small amount of processing and a little voice distortion. In the band division noise suppressor, a band dividing section (101) divides an input voice signal into a low band voice signal and a high band voice signal. The low band voice signal is subjected to decimate at a decimation section (102), subjected to noise suppression at a low band noise suppressing section (103), and then interpolated at an interpolation section (104). On the other hand, the high band voice signal is subjected to noise suppression at a high band noise suppressing section (105). A band combination section (106) composes the bands of low-band and high-band voice signals subjected to noise suppression and outputs a voice signal subjected to noise suppression over the entire band.

Abstract: An “Interference Canceller” provides a computationally efficient real-time technique for removing stationary-tone interference from signals. Typical sources of stationary tone contamination of signals include noise from power wiring (i.e., 50/60 Hz or 400 Hz and their harmonics), frame or line frequencies from electronic devices, and noise from computer fans, hard disk drives, etc. In general, the Interference Canceller adaptively builds and updates a model of stationary tone interference in consecutive frames of an input signal. This adaptively updated model is then used to extrapolate and subtract noise from subsequent frames of the input signal to generate a “clean” output signal. This output signal exhibits significant attenuation of stationary tone interference without eliminating important portions of the underlying signal or distorting the underlying signal with artifacts such as musical noise or nonlinear distortions.

Abstract: Digital audio data with error detection bits added thereto is inputted to an error detecting and correcting device (4). The correcting device (4) corrects an error when the error is detected in the digital audio data. The digital audio data outputted from the error detecting and correcting device (4) is inputted to an impulse noise suppressing circuit (6). The suppressing circuit (6) operates for a predetermined time period when the correcting device (4) detects an error.

Abstract: The present invention uses a method of processing signals in which signals received from an array of sensors are subject to system having a first adaptive filter arranged to enhance a target signal and a second adaptive filter arranged to suppress unwanted signals. The output of the second filter is converted into the frequency domain, and further digital processing is performed in that domain. The invention is further enhanced by incorporating a third adaptive filter in the system and a novel method for performing improved signal processing of audio signals that are suitable for speech communication.

Abstract: A headset is constructed to generate an acoustically distinct speech signal in a noisy acoustic environment. The headset positions a pair of spaced-apart microphones near a user's mouth. The microphones each receive the user s speech, and also receive acoustic environmental noise. The microphone signals, which have both a noise and information component, are received into a separation process. The separation process generates a speech signal that has a substantial reduced noise component. The speech signal is then processed for transmission. In one example, the transmission process includes sending the speech signal to a local control module using a Bluetooth radio.

Abstract: A signal processing system enhances a speech input signal. A signal reconstruction circuit receives the speech input signal and extracts a spectral envelope. The signal reconstruction circuit generates an excitation signal based on the input signal, and generates a reconstructed speech signal based on the extracted spectral envelope and an excitation signal. A combining circuit combines the noise reduced signal and the reconstructed speech signal. Signal reconstruction and signal combinations may be based on a signal-to-noise ratio of the speech signal or another input.

Abstract: A system and method for separating a mixture of audio signal into desired audio signals (430) (e.g., speech) and a noise sign (440) is disclosed. Microphones (310, 320) are positioned to receive the mixed audio signals, and an independent component analysis (ICA) processes (212) the sound mixture using stability constraints. The ICA process (508) uses predefined characteristics of the desired speech signal to identify and isolate a target sound signal (430). Filter coefficients are adapted with a learning rule and filter weight update dynamics are stabilized to assist convergence to a stable separated ICA signal result. The separated signals may be peripherally-processed to further reduce noise effects using post-processing (214) and pre-processing (220, 230) techniques and information. The proposed system is designed and easily adaptable for implementation on DSP units or CPUs in audio communication hardware environments.

Abstract: A method and device within a speech processing unit (SPU) for reducing scheduling delay between the SPU and a radio network node. Within the SPU, data packets are processed in a plurality of time slots that are subunits of frames. The device receives timing information from the node that identifies a beginning and an ending of processing periods in the node. The timing information is utilized to select a time slot within each frame as a target time slot. The target time slot has a position within each frame such that the scheduling delay between the ending of a processing period in the node and the beginning of the target time slot is minimized. Data packets for a particular channel are assigned to the target time slot to reduce the scheduling delay. The phase of the frame is then adjusted by erasing superfluous data packets.

Abstract: In one of many possible embodiments, a method includes providing an audio output signal to an output device for broadcast to a user, receiving audio input, the audio input including user voice input provided by the user and audio content broadcast by the output device in response to receiving the audio output signal, applying at least one predetermined calibration setting, and filtering the audio input based on the audio output signal and the predetermined calibration setting. In some examples, the calibration setting may be determined in advance by providing a calibration audio output signal to the output device for broadcast, receiving calibration audio input, the calibration audio input including calibration audio content broadcast by the output device in response to receiving the calibration audio output signal, and determining the calibration setting based on at least one difference between the calibration audio output signal and the calibration audio input.

Abstract: An automated speech recognition filter is disclosed. The automated speech recognition filter device provides a speech signal to an automated speech platform that approximates an original speech signal as spoken into a transceiver by a user. In providing the speech signal, the automated speech recognition filter determines various models representative of a cumulative signal degradation of the original speech signal from various devices along a transmission signal path and a reception signal path between the transceiver and a device housing the filter. The automated speech platform can thereby provide an audio signal corresponding to a context of the original speech signal.

Abstract: The present invention provides a process for separating a good quality information signal from a noisy acoustic environment. The separation process uses a set of at least two spaced-apart transducers to capture noise and information components. The transducer signals, which have both a noise and information component, are received into a separation process. The separation process generates one channel that is substantially only noise, and another channel that is a combination of noise and information. An identification process is used to identify which channel has the information component. The noise signal is then used to set process characteristics that are applied to the combination signal to efficiently reduce or eliminate the noise component. In this way, the noise is effectively removed from the combination signal to generate a good qualify information signal. The information signal may be, for example, a speech signal, a seismic signal, a sonar signal, or other acoustic signal.

Abstract: An apparatus for canceling an echo signal in a mobile terminal of a mobile communication system. A double talk detector (DTD) receives a first signal by canceling an estimated echo signal from a signal received through a microphone, outputs the first signal, and outputs the first and a second signal comprising a background noise signal and a residual echo signal during a non-double talk. An Auto-Regressive (AR) analysis and inverse filtering unit receives the second signal from the DTD, and whitens the second signal. A pitch analysis and inverse filtering unit receives the whitened signal, and cancels a pitch value remaining therein by performing pitch analysis and inverse filtering on the whitened signal. A noise canceller receives the pitch-cancelled whitened signal and the first signal output from the DTD, canceling a residual echo signal and a background noise signal from the first signal using the pitch-cancelled whitened signal.

Abstract: For determining an estimate of a need for information units for encoding a signal, a measure for the distribution of the energy in the frequency band is taken into account in addition to the admissible interference for a frequency band and an energy of the frequency band. With this, a better estimate of the need for information units is obtained, so that coding can be done more efficiently and more accurately.

Abstract: The present invention includes a method for speech encoding and decoding and a design of speech coder and decoder. The characteristic of speech encoding method relies on the type of data with high compression rate after the whole speech data is compressed. The present invention is able to lower the bit rate of the original speech from 64 Kbps to 1.6 Kbps and provide a bit rate lower than the traditional compression method. It can provide good speech quality, and attain the function of storing the maximum speech data with minimum memory. As to the speech decoding method, some random noises are appropriated added into the exciting source, so that more speech characteristics can be simulated to produce various speech sounds. In addition, the present invention also discloses a coder and a decoder designed by application specific integrated circuit, and the structural design is optimized according to the software.

Abstract: A method and apparatus for noise suppression is described herein. The channel gain is controlled based on a degree of variability of the background noise. The noise variability estimate is used in conjunction with a variable attenuation concept to produce a family of gain curves that are adaptively suited for a variety of combinations of long-term peak SNR and noise variability. More specifically, a measure of the variability of the background noise is used to provide an optimized threshold that reduces the occurrence of non-stationary background noise entering into the transition region of the gain curve.

Abstract: An audio encoder regulates quality and bitrate with a control strategy. The strategy includes several features. First, an encoder regulates quantization using quality, minimum bit count, and maximum bit count parameters. Second, an encoder regulates quantization using a noise measure that indicates reliability of a complexity measure. Third, an encoder normalizes a control parameter value according to block size for a variable-size block. Fourth, an encoder uses a bit-count control loop de-linked from a quality control loop. Fifth, an encoder addresses non-monotonicity of quality measurement as a function of quantization level when selecting a quantization level. Sixth, an encoder uses particular interpolation rules to find a quantization level In a quality or bit-count control loop. Seventh, an encoder filters a control parameter value to smooth quality. Eighth, an encoder corrects model bias by adjusting a control parameter value in view of current buffer fullness.

Abstract: The present invention provides a method and apparatus for accelerated handwritten symbol recognition in a pen based tablet computer. In one embodiment, handwritten symbols are translated into machine readable characters using special purpose hardware. In one embodiment, the special purpose hardware is a recognition processing unit (RPU) which performs feature extraction and recognition. A user inputs the handwritten symbols and software recognition engine preprocesses the input to a reduced form. The data from the preprocessor is sent to the RPU which performs feature extraction and recognition. In one embodiment, the RPU has memory and the RPU operates on data in its memory. In one embodiment, the RPU uses a hidden Markov model (HMM) as a finite state machine that assigns probabilities to a symbol state based on the preprocessed data from the handwritten symbol. In another embodiment, the RPU recognizes collections of symbols, termed “wordlets,” in addition to individual symbols.

Abstract: A method for improving noise robustness in speech recognition, wherein a front-end is used for extracting speech feature from an input speech and for providing a plurality of scaled spectral coefficients. The histogram of the scaled spectral coefficients is normalized to the histogram of a training set using Gaussian approximations. The normalized spectral coefficients are then converted into a set of cepstrum coefficients by a decorrelation module and further subjected to ceptral domain feature-vector normalization.

Abstract: A sound encoder and sound decoder that encode and decode, respectively, variable length codes on a frame by frame basis, the coding including main codes and auxiliary codes in which auxiliary codes are multiplexed or demultiplexed in a same fixed order to determine the order of multiplexing and demultiplexing the main codes which are used to determine where the codes are to be placed in the sound code.

Abstract: The presence of speech in a filtered speech signal is detected for the purpose of suspending noise level calculations during periods of speech. A received speech signal is split into a plurality of subband signals. A subband variable gain is determined for each subband based on an estimation of the noise level in the received voice signal and on an envelope of the received signal in each subband. Each subband signal is multiplied by the subband variable gain for that subband. The subband signals are combined to produce an output voice signal.

Abstract: The present invention relates to a mobile set integrating a memory efficient data storage system for the real time recording of voice conversations, data transmission and the like. The data recorder has the capacity to selectively choose the most relevant time frames of a conversation for recording, while discarding time frames that only occupy additional space in memory without holding any conversational data. The invention executes a series of logic steps on each signal including a voice activity detector step, frame comparison step, and sequential recording step. A mobile set having a modified architecture for performing the methods of the present invention is also disclosed.

Abstract: A speech communication apparatus which is used with a microphone being fixed to a predetermined position in the vicinity of the mouth in such a manner as to prevent the transmission of uncomfortable noise such as sneezing, coughing or throat-clearing noise to a partner. There is provided a speech communication apparatus including a speech communication microphone, a speaker and a communication unit for amplifying an output signal from the speech communication microphone, the speech communication apparatus includes the communication unit having an amplifier for amplifying an input signal and outputting the input signal so amplified, and a controller for controlling the gain of the amplifier in response to an excessive input signal, wherein the controller controls the gain of the amplifier such that a reproduced sound of an excessive input signal is reduced to a predetermined level only for a predetermined period of time when the excessive input signal is detected.

Abstract: Various time-domain noise suppression methods and devices for suppressing a noise signal in a speech signal are provided. For example, a time-domain noise suppression method comprises estimating a plurality of linear prediction coefficients for the speech signal, generating a prediction error estimate based on the plurality of prediction coeficients, generating an estimate of the speech signal based on the plurality of linear prediction coefficients, using a voice activity detector to determine voice activity in the speech signal, updating a plurality of noise parameters based on the prediction error and if the voice activity detector determines no voice activity in the speech signal, generating an estimate of the noise signal based on the plurality of noise parameters, and passing the speech signal through a filter derived from the estimate of the noise signal and the estimate of the speech signal to generate a clean speech signal estimate.

Abstract: Speech/non-speech determining section 103 makes a speech/non-speech determination of whether a speech spectrum is of a speech interval with a speech included or of a non-speech interval with only a noise and no speech included. Noise spectrum estimating section 104 estimates a noise spectrum based on the speech spectrum determined as the non-speech interval. SNR estimating section 105 obtains speech signal power from the speech interval and noise signal power from the non-speech interval in the speech spectrum, and calculates SNR from a ratio of two values. Based on the speech/non-speech determination and a value of SNR, suppression coefficient control section 106 outputs a suppression lower limit coefficient to spectrum subtraction section 107. Spectral subtraction section 107 subtracts an estimated noise spectrum from the input speech spectrum, and outputs a speech spectrum with a noise suppressed.

Abstract: A method and apparatus for speech processing in a distributed speech recognition system having a front-end and a back-end. The speech processing steps in the front-end are as follows: extracting speech features from a speech signal and normalizing the speech features in order to alter the power of the noise component in the modulation spectrum in relation to the power of the signal component, especially with frequencies above 10 Hz. A low-pass filter is then used to filter the normalized modulation spectrum in order to improve the signal-to-noise ratio (SNR) in the speech signal. The combination of feature vector normalization and low-pass filtering is effective in noise removal, especially in a low SNR environment.

Abstract: An apparatus for detecting at least one tone having a known frequency and duration in an input signal. The input signal is input over a period of time which is divided into frame portions including at least an initial frame portion and a last frame portion. An energy signal indicative of the energy of the input signal during each frame portion is generated. A signal filter receives the energy signal and generates a noise indicator for each frame portion based on whether noise is detected in the energy signal. A dynamic threshold determiner generates an energy threshold for each frame portion. The energy threshold for the initial frame portion is generated based on a minimum expected value of the energy signal for a subsequent frame portion. The energy thresholds for frame portions subsequent to the initial frame portion are generated based on values of the energy signals during previous frame portions and the noise indicator.

Abstract: In a speech recognition platform, a masking unit 17 can be utilized to mask noisy content within an audio sample. By masking such noise in a dynamic but predictable manner, valid content can be preserved while largely overcoming the random and detrimental presence of noise. In one embodiment, speech recognition features are extracted pursuant to a hierarchical process that localizes, at least to some extent, some of the resultant features from other resultant features. As a result, noisy or otherwise unreliable information corresponding to the audio sample will not be leveraged unduly across the entire feature set. In another embodiment, an average energy value for processed samples is calculated with individual energy values that are downwardly weighted when such individual energy values are likely representative of noise.

Abstract: The present invention proposes a new method and a new apparatus for enhancement of audio source coding systems utilizing high frequency reconstruction (HFR). It utilizes adaptive filtering to reduce artifacts due to different tonal characteristics in different frequency ranges of an audio signal upon which HFR is performed. Tie present invention is applicable to both speech coding and natural audio coding systems.

Abstract: A speech enhancement system for the reduction of background noise comprises a time-to-frequency transformation unit to transform frames of time-domain samples of audio signals to the frequency domain, background noise reduction means to perform noise reduction in the frequency domain, and a frequency-to-time transformation unit to transform the noise reduced signals back to the time-domain. In the background noise reduction means for each frequency component a predicted background magnitude is calculated in response to the measured input magnitude from the time-to-frequency transformation unit and to the previously calculated background magnitude, whereupon for each of said frequency components the signal-to-noise ratio is calculated in response to the predicted background magnitude and to said measured input magnitude and the filter magnitude for said measured input magnitude in response to the signal-to-noise ratio.

Abstract: A speech processing apparatus and method are provided for processing an input speech signal to compensate for the effects of noise in the input speech signal. The method and apparatus divide the input speech signal into a plurality of sequential time frames and a set of spectral parameters are extracted for each time frame, which parameters are representative of the input signal during the time frame. The system then processes the input speech by scaling the parameters for each frame in dependence upon a measure of the signal to noise ratio for the input frame. In this way, the effects of additive noise on the input signal can be reduced.

Abstract: A method and apparatus are provided for identifying a noise environment for a frame of an input signal based on at least one feature for that frame. Under one embodiment, the noise environment is identified by determining the probability of each of a set of possible noise environments. For some embodiments, the probabilities of the noise environments for past frames are included in the identification of an environment for a current frame. In one particular embodiment, a count is generated for each environment that indicates the number of past frames for which the environment was the most probable environment. The environment with the highest count is then selected as the environment for the current frame.

Abstract: A method of determining a codec mode for encoding a frame in a communications system, the method comprising the steps of: receiving a sequence of signal samples arranged in frames; analysing a current frame to select a codec mode appropriate for the current frame; predicting the characteristics of a subsequent frame using lookahead samples from the subsequent frame; and determining a codec mode for the current frame and the subsequent frame which suits the current frame and also suits a subsequent frame based on the predicted characteristics.

Abstract: A scalable audio codec processes, quantizes and encodes audio signals into an embedded audio bitstream of bit-planes each having a data unit. The data unit has a beginning refinement bits partition, a second significance bits partition, a third sign boundary mark bits partition, and a fourth sign bits partition. The second and fourth partitions form a boundary for the third partition. The quantizing uses a variable length coding algorithm. The third partition is an invalid codeword for a predetermined encoding method being used to encode. The codec uses a decoder to decode the embedded audio bitstream of bit-planes using Reversible exponential Golomb (Exp-Golomb) codes in a Reversible Variable Length Code (RVLC) algorithm to produce quantized data of weighted subbands. An inverse quantizer dequantizes the quantized data into audio signals.

Abstract: A background sound sending side multiplexes and sends, in a multiplexer, uttered encoded speech data generated in a speech sending section and encoded background sound data outputted from a background sound storing section. Simultaneously, a background sound reproducing section, reproduces encoded background sound data and reproduced background sound signal is superposed on received speech in a receiving section and outputted from a receiver. A background sound receiving side demultiplexes, in a demultiplexer, received multiplexed data into received encoded speech data and encoded background sound data which are decoded in the receiving section and the background sound reproducing section respectively, and in the receiving section, a sound in which received speech and background sound are superposed is outputted from a receiver.

Abstract: An automated speech recognition filter is disclosed. The automated speech recognition filter device provides a speech signal to an automated speech platform that approximates an original speech signal as spoken into a transceiver by a user. In providing the speech signal, the automated speech recognition filter determines various models representative of a cumulative signal degradation of the original speech signal from various devices along a transmission signal path and a reception signal path between the transceiver and a device housing the filter. The automated speech platform can thereby provide an audio signal corresponding to a context of the original speech signal.

Abstract: In a method for signalling a noise substitution when coding an audio signal, the time-domain audio signal is first transformed into the frequency domain to obtain spectral values. The spectral values are subsequently grouped together to form groups of spectral values. On the basis of a detection establishing whether a group of spectral values is a noisy group or not, a codebook is allocated to a non-noisy or tonal group by means of a codebook number for redundancy coding of the same. If a group is noisy, an additional codebook number which does not refer to a codebook is allocated to it in order to signal that this group is noisy and therefore does not have to be redundancy coded. By signalling noise substitution by means of a Huffman codebook number for noisy groups of spectral values, which are e.g.