Motorola Corporation

Other

Ira A Gerson

Mark A Jasiuk

Brett L Lindsley

Richard J Vilmur

David E Borth

Matthew A Hartman

Eric H Winter

Philip J Smanski

Richard E White

Orhan Karaali

Gerald Edward Corrigan

David R Conger

Joseph J Barlo

An input speech signal is encoded as one or more reflection coefficients. To reduce storage requirements, the reflection coefficients are scalar quantized by storing an N-bit code rather than the entire reflection coefficient. An exemplary value for N is 8. A table is provided having 2.sup.N reflection coefficient values. The N-bit code is used to look up reflection coefficient values from the table. To reduce spectral distortion due to scalar quantization, the reflection coefficient values in the table are non-linearly scaled.

Method of storing reflection coeffients in a vector quantizer for a

An improved speech coder provides a more natural sounding replication of speech by modifying the mean-squared error criterion for the selected speech coder parameters. Specifically, the modification emphasizes the signal components that the speech coder has difficulty matching, i.e. the high frequencies. This emphasis is constrained to certain limitations to avoid over-emphasizing the speech.

Speech coding method and apparatus using mean squared error modifier for

A Vector-Sum Excited Linear Predictive Coding (VSELP) speech coder provides improved quality and reduced complexity over a typical speech coder. VSELP uses a codebook which has a predefined structure such that the computations required for the codebook search process can be significantly reduced. This VSELP speech coder uses single or multi-segment vector quantizer of the reflection coefficients based on a Fixed-Point-Lattice-Technique (FLAT). Additionally, this speech coder uses a pre-quantizer to reduce the vector codebook search complexity and a high-resolution scalar quantizer to reduce the amount of memory needed to store the reflection coefficient vector codebooks. Resulting in a high quality speech coder with reduced computations and storage requirements.

Multi-segment vector quantizer for a speech coder suitable for use in a

Text may be converted to audible signals, such as speech, by first training a neural network 106 using recorded audio messages 204. To begin the training, the recorded audio messages are converted into a series of audio frames 205 having a fixed duration 213. Then, each audio frame is assigned a phonetic representation 203 and a target acoustic representation 208, where the phonetic representation 203 is a binary word that represents the phone and articulation characteristics of the audio frame, while the target acoustic representation 208 is a vector of audio information such as pitch and energy. After training, the neural network 106 is used in conversion of text into speech. First, text that is to be convened is translated to a series of phonetic frames 401 of the same form as the phonetic representations 208 and having the fixed duration 213. Then the neural network produces acoustic representations in response to context descriptions 207 that include some of the phonetic frames 401. The acoustic representations are then converted into a speech wave form by a synthesizer 107.

Method and apparatus for converting text into audible signals using a

In a speech coder (100), excitation source gain information (802) is transmitted along with a coding mode indicator. The coding mode indicator indicates how the gain information is to be interpreted. In one embodiment, the coding mode indicator can also be utilized to control which of a plurality of excitation sources (202, 206-208) are utilized when synthesizing the speech. The coding mode itself is selected as a function of the periodicity of an input speech signal.

Provision of speech coder gain information using multiple coding modes

A method for protecting information bits wherein input data bits, at least some of which are to be protected, are sorted based upon information determined from a subset of the input data bits. An error control coding technique is applied to at least some of the sorted bits. In the preferred embodiment, an input data stream of voice coder bits is separated into arrays of bits. A first array (302) comprises voice coder bits needing error protection, with the bits arranged in order of importance determined by voicing mode. The second array (303) comprises bits that will not be error protected. The bits from the first array are provided to the input of an encoder (304), then the encoded bits are combined (305) with the bits from the second array (303) to form a bit stream.

Error protection for multimode speech coders

A digital speech coding method uses an Rth-order filter to model the frequency response of multiple filters, thereby, providing a filter which offers the control of multiple filters without the complexity of multiple filters. The Rth-order filter can be used as a spectral noise weighting filter or a combination of a short-term predictor filter and a spectral noise weighting filter, referred to as the spectrally noise weighted synthesis filter, depending on which embodiment is employed. In general, the method models the frequency response of L Pth-order filters by a single Rth-order filter, where the order R&lt;L.times.P. Thus, this method increases the control of a speech coder filter without a corresponding increase in the complexity of the speech coder.

Method for generating a spectral noise weighting filter for use in a

A digital speech coder utilizes harmonic noise weighting to overcome some limitations of low-rate CELP-type speech coders in reproducing voiced speech. In addition to a short term correction factor, which constitutes spectral noise weighting as known in the art, a long term pitch correction factor is utilized to provide harmonic noise weighting. The inclusion of harmonic noise weighting in a speech coder more efficiently utilizes noise-masking properties of a speech signal, allowing synthesis of a higher quality speech at a given bit rate.

Digital speech coder and method utilizing harmonic noise weighting

A speech coder and decoder methodology wherein pitch excitation and codebook excitation source energies are represented by parameters that are readily transmissible with minimal transmission capacity requirements. The parameters are the long term energy value, a short term correction factor which is applied to the long term energy value to match the short term energy, and proportionality factor(s) that specify the relative energy contribution of the excitation sources to the short term energy value.

Digital speech coder having optimized signal energy parameters

An Rth-order filter models the frequency response of multiple filters, to provide a filter which offers the control of multiple filters without the complexity of multiple filters. The Rth-order filter can be used as a spectral noise weighting filter or a combination of a short-term predictor filter and a spectral noise weighting filter, referred to as the spectrally noise weighted synthesis filter, depending on which embodiment is employed. In general, the method models the frequency response of L Pth-order filters by a single Rth-order filter, where the order R&lt;L.times.P. Thus, this method increases the control of a speech coder filter without a corresponding increase in the complexity of the speech coder.

A digital speech coder includes a long-term filter (124) having an improved sub-sample resolution long-term predictor (FIG. 5 ) which allows for subsample resolution for the lag parameter L. A frame of N samples of input speech vector s(n) is applied to an adder (510). The output of the adder (510) produces the output vector b(n) for the long term filter (124). The output vector b(n) is fed back to a delayed vector generator block (530) of the long-term predictor. The nominal long-term predictor lag parameter L is also input to the delayed vector generator block (530). The long-term predictor lag parameter L can take on non-integer values, which may be multiples of one half, one third, one fourth or any other rational fraction. The delayed vector generator (530) includes a memory which holds past samples of b(n). In addition, interpolated samples of b(n) are also calculated by the delayed vector generator (530) and stored in its memory, at least one interpolated sample being calculated and stored between each past sample of b(n). The delayed vector generator (530) provides output vector q(n) to the long-term multiplier block (520), which scales the long-term predictor response by the long-term predictor coefficient .beta.. The scaled output .beta.q(n) is then applied to the adder (510) to complete the feedback loop of the recursive filter (124).

Digital speech coder having improved sub-sample resolution long-term

A speech encoder uses a soft interpolation decision for spectral parameters. For each frame, the encoder first calculates the residual energy for interpolated spectral parameters, and then calculates the residual energy for non-interpolated spectral parameters. The encoder then compares these residual energy calculations. If the encoder determines that the interpolated spectral parameters yields the lowest residual energy, it indicates to a far-end decoder to use the interpolated values for the current frame. Otherwise, it indicates to the far-end decoder to use the non-interpolated values for the current frame. The encoder signals the far-end decoder as to which spectral parameters (interpolated or non-interpolated values) to use by encoding and transmitting a special signalling bit.

Speech encoder using a soft interpolation decision for spectral

Lag information for use in a speech coder is developed by estimating lag values for the various subframes (201) of a speech coding frame (200) of information, and by then selecting lag values for each subframe that are both closely corresponding to the estimated lag values and that also observe the restrictions of a selected delta-coding routine. When a plurality of candidate sets of such information have been developed, they are compared against one another to identify that set which appears to provide the best set of lag values. This information is then available for framing and transmission. In one embodiment, the sets of candidate values are also selected to ensure provision for subsequent adjustment in either a positive or negative direction. With this adjustability capability so provided, closed-loop adjustments can be made with respect to the selected values to ensure that the ultimately transmitted coding for the lag value most closely corresponds to an ultimate output that most closely represents the speech signal to be represented.

Delta-coded lag information for use in a speech coder

An adaptive spectral postfilter in a synthesized speech platform has a denominator characteristic that corresponds to a preceding LPC filter stage, and a numerator characteristic that is developed as a function of the denominator characteristic through application of spectral smoothing techniques. This allows the numerator to track the denominator without the introduction of spectral distortion that would otherwise affect the processing in an adverse way.

Digital speech decoder having a postfilter with reduced spectral

In a Viterbi Algorithm decoder (204) as used to decode convolutionally encoded information, reliability information is developed for various path discard decisions made within the Viterbi Algorithm. These decisions are made for discard opportunities that impact one or more error detection windows (601). Based upon these metrics, a reliability factor sequence can be provided and compared against a fixed (or varying) threshold. When unreliability appears, appropriate action can be taken. For example, all of the information can be discarded, or only certain portions of the information can be discarded, as appropriate to the particular application.

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Hoffman Estates, IL, United States of America

Ira A Gerson