Abstract: An audio decoding system performs frame loss concealment (FLC) when portions of a bit stream representing an audio signal are lost within the context of a digital communication system. The audio decoding system employs two different FLC methods: one designed to perform well for music, and the other designed to perform well for speech. When a frame is deemed lost, the audio decoding system analyzes a previously-decoded audio signal corresponding to previously-decoded frames of an audio bit-stream. Based on the results of the analysis, the lost frame is classified as either speech or music. Using this classification, other signal analysis, and knowledge of the employed FLC methods, the audio decoding system selects the appropriate FLC method which then performs FLC on the lost frame.

Abstract: A method for performing packet loss concealment (PLC) and/or frame erasure concealment (FEC) in a speech decoder of a voice communication system. In accordance with the method, if a segment of an encoded speech signal is determined to be bad, an excitation signal is derived by scaling a random sequence of samples, and long-term and short-term predictive parameters are derived based on parameters associated with a previously-decoded segment. The excitation signal is then filtered by a long-term synthesis filter and a short-term synthesis filter under the control of the respective long-term and short-term predictive parameters. If the number of consecutively-received bad segments exceeds a predetermined threshold, the decoded speech signal is gradually reduced.

Abstract: A system and method for encoding and decoding speech signals that includes a specially-designed Code Excited Linear Prediction (CELP) encoder and a vector quantization (VQ) based Noise Feedback Coding (NFC) decoder or that includes a specially-designed VQ-based NFC encoder and a CELP decoder. The VQ based NFC decoder may be a VQ based two-stage NFC (TSNFC) decoder. The specially-designed VQ-based NFC encoder may be a specially-designed VQ based TSNFC encoder. In each system, the encoder receives an input speech signal and encodes it to generate an encoded bit stream. The decoder receives the encoded bit stream and decodes it to generate an output speech signal. A system and method is also described in which a single decoder receives and decodes both CELP-encoded audio signals as well as VQ-based NFC-encoded audio signals.

Abstract: The invention improves the encoding and decoding of speech by focusing the encoding on the perceptually important characteristics of speech. The system analyzes selected features of an input speech signal, and first performing a common frame based speech coding of an input speech signal. The system then performs a speech coding based on either a first speech coding mode or a second speech coding mode. The selection of a mode is based on characteristics of the input speech signal. The first speech coding mode uses a first framing structure and the second speech coding mode uses a second framing structure.

Abstract: In a Noise Feedback Coding (NFC) system operable in a ZERO-STATE condition and a ZERO-INPUT condition, the NFC system including at least one filter having a filter memory, a method of updating the filter memory. The method comprises: (a) producing a ZERO-STATE contribution to the filter memory when the NFC system is in the ZERO-STATE condition; (b) producing a ZERO-INPUT contribution to the filter memory when the NFC system is in the ZERO-INPUT condition; and (c) updating the filter memory as a function of both the ZERO-STATE contribution and the ZERO-INPUT contribution.

Abstract: The invention improves the encoding and decoding of speech by focusing the encoding on the perceptually important characteristics of speech. The system analyzes selected features of an input speech signal, and first performing a common frame based speech coding of an input speech signal. The system then performs a speech coding based on either a first speech coding mode or a second speech coding mode. The selection of a mode is based on characteristics of the input speech signal. The first speech coding mode uses a first framing structure and the second speech coding mode uses a second framing structure.

Abstract: A communication device receives an encoded signal from a primary input source. The encoded signal includes periods of speech and periods of non-speech. The communication device includes a decoder to decode the received signal to produce a decoded signal. A detector of the communication device detects the periods of speech and the periods of non-speech within the decoded signal. A controller of the communication device provides the decoded signal to an output of the communication device during the periods of speech. The controller interrupts the decoded signal during the periods of non-speech and provides an alternate input from a secondary input source to the communication device.

Abstract: A distortion removal system for reducing the quantization distortion that results from quantization of a signal by sample-by-sample quantization techniques is disclosed. The distortion removal system uses the signal previously quantized with the sample-by-sample quantization techniques to determine an expected quantization distortion. The expected quantization distortion is determined for each of a plurality of frames of the signal. The expected quantization distortion is removed from each of the frames of the signal.

Abstract: Speech coding systems include multi-rate speech codecs having an encoder and a decoder. Silence description coding for multi-rate speech coding systems that employ discontinued transmission is performed in either the encoder or the decoder of the multi-rate speech codec. It may also be performed in a distributed manner wherein it is performed partially in the encoder and partially in the decoder. The silence description coding is performed on a speech signal having a substantially non-speech-like characteristic. Voice activity detection classifies the speech signal as being either substantially speech-like or substantially non-speech-like. The silence description coding is selected from a plurality of coding modes. In certain embodiments of the invention, the silence description coding is a source coding mode that operates at a bit rate that fits within a bit rate budget as determined by all of the available source coding modes within the plurality of coding modes.

Abstract: A method of performing an excitation Vector Quantization (VQ) in a Noise Feedback Coding environment involves reorganizing a calculation of an energy of an error vector for each of a plurality of candidate excitation vectors of a codebook. The energy of the error vector is a cost function that is minimized during a search of the codebook for a best candidate excitation VQ vector. The reorganization includes expanding a Mean Squared Error (MSE) term of the error vector, excluding an energy term that is invariant to the candidate excitation vector, and pre-computing energy terms of ZERO-STATE responses of the candidate excitation vectors that are invariant to sub-vectors of a subframe. Another method searches a signed codebook. Both methods use correlation techniques.

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: A method for robust speech classification in speech coding and, in particular, for robust classification in the presence of background noise is herein provided. A noise-free set of parameters is derived, thereby reducing the adverse effects of background noise on the classification process. The speech signal is identified as speech or non-speech. A set of basic parameters is derived for the speech frame, then the noise component of the parameters is estimated and removed. If the frame is non-speech, the noise estimations are updated. All the parameters are then compared against a predetermined set of thresholds. Because the background noise has been removed from the parameters, the set of thresholds is largely unaffected by any changes in the noise. The frame is classified into any number of classes, thereby emphasizing the perceptually important features by performing perceptual matching rather than waveform matching.

Abstract: Typical communication systems operate with a single channel decoder, and hence would have to settle for the performance from the single channel decoder regardless of the conditions of the communications channel. The present invention uses a hybrid channel decoder comprising multiple channel decoders, each configured to optimize the quality of the re-constructed signal for different channel conditions. Therefore, the desired decoder can be selected as conditions of the communications channel, or the data signal, change over time, so as to optimize the re-constructed data signal. In embodiments, the data signal is a speech signal.

Abstract: A speech compression system capable of encoding a speech signal into a bitstream for subsequent decoding to generate synthesized speech is disclosed. The bitstream comprises a type component and a gain component. The type component is representative of a type classification of a frame of speech signal that is transmitted. The type component comprises a first type and second type. The gain component represents an adaptive codebook gain and a fixed codebook gain component comprises a fixed codebook gain component and an adaptive codebook gain component exclusively encoded as separate components of the bitstream as a function of the bit rate when the type classification is the second type.

Abstract: The invention improves the encoding and decoding of speech by focusing the encoding on the perceptually important characteristics of speech. The system analyzes selected features of an input speech signal, and first performing a common frame based speech coding of an input speech signal. The system then performs a speech coding based on either a first speech coding mode or a second speech coding mode. The selection of a mode is based on characteristics of the input speech signal. The first speech coding mode uses a first framing structure and the second speech coding mode uses a second framing structure.

Abstract: A noise feedback coding (NFC) system and method that utilizes a simple and relatively inexpensive general structural configuration, but achieves improved flexibility with respect to controlling the shape of coding noise. The NFC system and method utilizes an all-zero noise feedback filter that is configured to approximate the response of a pole-zero noise feedback filter.

Abstract: A method for performing packet loss concealment (PLC) and/or frame erasure concealment (FEC) in a speech decoder of a voice communication system. In accordance with the method, if a segment of an encoded speech signal is determined to be bad, an excitation signal is derived by scaling a random sequence of samples, and long-term and short-term predictive parameters are derived based on parameters associated with a previously-decoded segment. The excitation signal is then filtered by a long-term synthesis filter and a short-term synthesis filter under the control of the respective long-term and short-term predictive parameters. If the number of consecutively-received bad segments exceeds a predetermined threshold, the decoded speech signal is gradually reduced.

Abstract: A method for adaptive long-term filtering of an audio signal, such as a decoded speech signal. The method includes measuring a smoothed periodicity of an audio signal segment, such as an audio frame, wherein the smoothed periodicity is measured by low-pass filtering an instantaneous periodicity of the audio signal segment. The periodicity of the audio signal segment is then increased in a manner that depends upon whether the smoothed periodicity is less than a predetermined threshold. By utilizing a smoothed periodicity measurement in this fashion, more accurate control of the post-filter is provided as compared to conventional solutions. Additionally, the method includes deriving filters by interpolating between filter responses of adjacent audio signal segments to minimize distortion at segment boundaries.

Abstract: The invention provides a speech coding system with input signal transformation that may reduce or essentially eliminate “silence noise” from the input or speech signal. The speech coding system may comprise an encoder disposed to receive an input signal. The encoder ramps the input signal to a zero-level when a portion of the input signal comprises silence noise.

Abstract: A multi-rate speech codec supports a plurality of encoding bit rate modes by adaptively selecting encoding bit rate modes to match communication channel restrictions. In higher bit rate encoding modes, an accurate representation of speech through CELP (code excited linear prediction) and other associated modeling parameters are generated for higher quality decoding and reproduction. For each bit rate mode selected, pluralities of fixed or innovation subcodebooks are selected for use in generating innovation vectors. The speech coder distinguishes various voice signals as a function of their voice content. For example, a Voice Activity Detection (VAD) algorithm selects an appropriate coding scheme depending on whether the speech signal comprises active or inactive speech. The encoder may consider varying characteristics of the speech signal including sharpness, a delay correlation, a zero-crossing rate, and a residual energy.