A method of speech signal compression, by variable rate coding of frames of digitized speech samples, comprising the steps of: determining a level of speech activity for a frame of digitized speech samples; selecting an encoding rate from a set of rates based upon said determined level of speech activity within said frame; coding said frame according to a predetermined coding format for said selected rate wherein each rate has a corresponding different coding format; providing for said frame a corresponding output data packet at said selected rate.

Variable rate vocoder

In this paper, two short-time spectral amplitude estimators of the speech signal are derived based on a parametric formulation of the original generalized spectral subtraction method. The objective is to improve the noise suppression performance of the original method while maintaining its computational simplicity. The proposed parametric formulation describes the original method and several of its modifications. Based on the formulation, the speech spectral amplitude estimator is derived and optimized by minimizing the mean-square error (MSE) of the speech spectrum. With a constraint imposed on the parameters inherent in the formulation, a second estimator is also derived and optimized. The two estimators are different from those derived in most modified spectral subtraction methods, which are predominantly nonstatistical. When tested under stationary white Gaussian noise and semistationary Jeep noise, they showed improved noise suppression results.

A parametric formulation of the generalized spectral subtraction method

A system and method for reviewing inputted voice instructions in a vehicle-based telematics control unit. The system includes a microphone, a speech recognition processor, and an output device. The microphone receives voice instructions from a user. Coupled to the microphone is the speech recognition processor that generates a voice signal by performing speech recognition processing of the received voice instructions. The output device outputs the generated voice signal to the user. The system also includes a user interface for allowing the user to approve the outputted voice signal, and a communication component for wirelessly sending the generated voice signal to a server over a wireless network upon approval by the user.

Real time display of system instructions

The invention relates to a method for normalising a speech recognition system to a long-time spectrum in order to eliminate interfering influences such as different microphone, room and speaker characteristics even before the classifier is reached. The cepstral features which are used in known speech recognition systems are normalised by subtracting the mean value of the cepstral vector components from the respective cepstral vector. The method is advantageously expanded by adaptive normalisation by sliding mean-value estimation with a sliding window with respect to time and an adaptive time constant. This makes it possible to achieve a speaker-specific mean-value subtraction.

Speech recognition method with adaptation of the speech characteristics

A system and method for reducing the amount of repetitive data sent by a server to a client for vehicle navigation. The system includes a computer-based vehicle unit located in a vehicle, a gateway configured to wirelessly send and receive trip information to and from the vehicle unit, and a computer-based server in communication with the gateway over a network. The vehicle unit wirelessly receives signals from a computer-based server that includes the desired navigation information in packet form. The vehicle unit includes a user interface component that presents the received navigation information and records user requests. The server processes the requests, generates a trip plan according to the navigation information and sends the generated trip plan back to the vehicle unit via a gateway when a request has been completed.

System and method for reducing the amount of repetitive data sent by a server to a client for vehicle navigation

The authors present the results of a study designed to investigate the effects of subtractive-type noise reduction algorithms on LPC-based spectral parameter estimation as related to the performance of speech processors operating with input SNRs of 15 dB and below. Subtractive noise preprocessing greatly improves the SNR, but system performance improvement is not commensurate. LPC spectral estimation is affected by the character of the residual noise which exhibits greater variance and spectral granularity than the original broadband noise. The study shows that removing less than the full amount of noise and whitening it improves spectral estimation and speech device performance. Techniques and performance results are presented. >

The effects of subtractive-type speech enhancement/noise reduction algorithms on parameter estimation for improved recognition and coding in high noise environments

A fast self-adapting algorithm to remove broadband noise in the cepstral domain is presented. Noise removal is accomplished by cepstral subtraction in a manner which allows subtraction factors to be derived adaptively, based on the local signal-to-noise ratio (SNR) of each signal frame. Finite averaging noise estimates are used to minimize the adaptation time. The algorithm yields good speech quality with little spectral distortion. The algorithm has proven to be a useful and efficient tool for speech processing in the fast-changing F-15/F-16 aircraft cockpit environment. >

Fast self-adapting broadband noise removal in the cepstral domain

An algorithm is presented to determine the pitch of a signal in a very noisy environment adaptively and reliably. This algorithm is adaptive to input signal from frame to frame on both the correlative criterion and the energy criterion. The correlative criterion assumes that the input signal has a slowly time-varying property on adjacent frames. The energy criterion assumes that the input signal has some nonsignal frames to compute the statistics of noise energy. This algorithm has been useful in speech processing and speech coding. Implementation of this algorithm is simple and straightforward. >

C.S. Wu

Papers

The effects of subtractive-type speech enhancement/noise reduction algorithms on parameter estimation for improved recognition and coding in high noise environments

Fast self-adapting broadband noise removal in the cepstral domain

Adaptive pitch detection algorithm for noisy signals