Texas Instruments Corporation

Telogy Networks, Inc.

Bogdan R Kosanovic

Yimin Zhang

Zoran Mladenovic

Charles Fosgate

Dunling Li

Edward B Morgan

Frank Fruth

Jianzhong Xu

Joseph A Crupi

Negendra Kumar

Saqib Ali

Echo cancellation is provided in a telephone device by calculating a metric value indicative of a similarity between a representation of an incoming signal from a far end talker and a representation of an outgoing signal from a near end talker. A threshold value is derived based on the metric value. A portion of the outgoing signal is removed by using the threshold value to determine an amount to remove from the outgoing signal with continuous, real-time updating of the threshold value.

Clipping based on cepstral distance for acoustic echo canceller

Monitoring voice quality passively using line echo cancellation data across a telecommunications network and reporting monitoring data to a central network management system. Network is monitored for potential voice quality issues for pro-active isolation of problems prior to customer complaints about the problems. Line echo cancellation related and non-related data for IP and other networks is gathered and correlated together to provide voice quality assessments of network performance.

Intelligent voice network monitoring using echo cancellation statistics

A method and system for ordering a priority for a function to receive any type of processing resources in a system that includes a plurality of functions. The invention includes identifying a plurality of instances of the functions that use processing resources. The invention then determines an importance of at least one of said instances by using fuzzy logic in a fuzzy inference system.

Intelligent realtime management of processing resources

The invention presents a software agent that optimizes processing resources for multiple instances of a software module that are executing simultaneously. The agent allocates and distributes processing resources, such as MIPS (millions of instruction cycles per second), to software functions executing on a core and controls resource distributions and module functions in a manner such that maximum processing capacity is utilized but not exceeded. The agent schedules the enabling and disabling of software module instance functions using a prioritization scheme that allocates MIPS to functions as the functions are enabled. An exemplary embodiment optimizes MIPS resources for multiple instances of an echo cancellation unit operating on a DSP (digital signal processor) core.

Realtime management of processing resources

A method is disclosed for allocating processing resources, such as instruction execution which can be measured in MIPs or memory capacity, or other resources of a processor itself or resources used in the process of performing operations, such as memory resources, busses, drivers and the like, to functions in a queue waiting to be executed. This method includes the steps of determining the amount of processor resources available to be assigned, determining an estimate of the amount of resources needed for each function waiting in the queue to execute, and allocating the available resources to the functions using a hierarchical priority scheme. The hierarchical priority scheme assigns priority based on the environmental conditions, the achieved performance, and the amount of resource recently consumed by the function.

Method for resource management in a real-time embedded system

An apparatus is disclosed for allocating processing resources, such as instruction execution which can be measured in MIPs or memory capacity, or other resources of a processor itself or resources used in the process of performing operations, such as memory resources, busses, drivers and the like, to functions in a queue waiting to be executed. This apparatus includes a capacity determining device for determining an amount of the processor resource available to be assigned, a load determining device for determining an estimate of an amount of the resource needed for each function waiting in the queue to execute, a prioritization device for prioritizing each of the functions in the queue waiting to be executed, and an allocating device, which receives information from the capacity determining device, the load determining device, and the prioritization device, for allocating the available resource to the functions based on a hierarchical priority scheme.

Apparatus for resource management in a real-time embedded system

A method for identification of memory assignment conflicts in the assignment of memory location addresses to a set of buffers. Programs run in embedded processors using buffers in a fixed storage space need to be mapped to addresses which do not overlap or create conflicts. The process of assigning start and end addresses for buffers can be tedious and error prone if performed without automation. The present invention presents a tool that automates the task of mapping the memory buffers and heaps to physical space. The tool utilizes a memory buffer allocation table created by the programer. The table designates the locations, sizes and overlays of all the buffers and heaps. The tool checks the validity of the memory map specified. If it is found to be invalid, the user is notified of the error. Otherwise, a memory table is created which will serve as 'hooks' for runtime buffer manipulation.

Microprocessor memory space allocation management

A state machine for attenuating the transition into and out of NLP state to reduce voice clipping and to reduce echo leak in a voice over packet signal transmission. The state machine interposes two additional transitional states between the NLP active state and the NLP inactive state to eliminate the sharp transition of NLP activity. An NLP entering state is used to gradually reduce the mixing ratio of echo and voice to attenuate the transition from passage of echo in the NLP inactive state to the suppression of echo in the NLP active state. An NLP exiting state is used to gradually increase (ramping the change) the mixing ratio of echo and voice to attenuate the transition from suppression of echo in the NLP active state to passage of echo in the NLP inactive state. The rate of increase/decrease, the transition rate is determined based upon the signal parameters, including the presence of double talk and a transition rate indicator based unon these factors is generated in software to control the transition rate.

Double talk, NLP and comfort noise

A method of converging a step size control for an adaptive filter of a communication channel including: (1) initializing a nominal step size value and a penalty point value; (2) combining the nominal step size value and the penalty point value to generate a step size value; and (3) dynamically changing the step size value in response to a characteristic measure of a quality of the communication channel. The step size value is changed by adjusting the nominal step size value, the penalty point value, or both. In a preferred embodiment the penalty point value is adjusted dependant on: (1) a tone originating from the far end (2) full convergence (3) the power level of a residual error signal (4) the channel's near-end background noise and/or (5) weak double-talk in the communication channel. The nominal step size value is adjusted when an achieved initial combined loss is about 15 dB or greater and is reset by divergence.

Step size convergence control

Echo return loss is analyzed to determine if the near end connection of a communication link has hybrid induced echo. If the echo return loss is above a threshold value for a predetermined period, than no echo or very little echo is present. The lack of echo is treated as a four wire connection and the near end signal is processed accordingly. If the foreground and background filter update relationship indicates the presence of a hybrid or if the echo return loss drops below a second threshold, the condition of the near end signal is treated as a two wire hybrid induced echo. The analysis of the near end signal continues and treatment of the signal may switch between four wire and two wire any number of times during a communication link.

Echo analysis for identification of hybrid induced echo in a communication link

A method of estimating an echo return loss of a communication link measures the peak power value of a signal received from a far end of a communication link and the corresponding peak power value of a signal received from the near end of the communication link. When the near end signal is free from near end voice and excessive noise, the near end corresponding peak will be the echo of the far end power. The far end power is monitored and when a peak is detected, a period, which can be equal to a filter length period, is initiated. When the period has run, the delay line attached to the near end is polled to determine the peak power in the delay line. This peak power will correspond to the far end peak. If a peak, exceeding the first peak is detected before the period has run, the period is reinitiated. The echo return loss estimate is calculated as a ratio of the far-end peak power value to the near-end peak power value. The measured far-end signal is the payload information that the communication link was established to convey and the measured near-end signal is the echo of the payload.

Dynamically estimating echo return loss in a communication link

A method of discriminating noise and voice energy in a communication signal. A signal is measured in a plurality of block periods, which are sampled to obtain a measurement of the block energy value for the signal. The blocks are compared to a noise threshold and to a voice threshold to discriminate between noise and voice. The thresholds for noise and voice are periodically updated based on the minimum and maximum energy levels measured for block energies. In a preferred embodiment, the voice energy threshold and noise energy threshold values are updated according to a formula where the revised thresholds are based upon a factor of the minimum and maximum energy levels of the current block and the most recent past block and the average energy of the previous blocks. Updating of threshold levels allows for more accurate estimation of noise and voice during changes in either noise, voice or both to avoid missclassification of noise and/or voice.

Adaptive two-threshold method for discriminating noise from speech in a communication signal

In a system in which user equipment is connected to a packet network and a speech recognition application server is also connected to the packet network for performing speech recognition on speech data from the user equipment, a speech recognition system selectively performs feature extraction at a user end before transmitting speech data to be recognized. The feature extraction is performed only for speech which is to be recognized.

Speech recognition over packet networks

A method of estimating background noise in a signal. The signal is divided into blocks of equal predetermined length. The minimum energy of the signal during the length of each block is determined. The minimum energy determined for the current block is compared to a previous determination of minimum energy. If the current minimum energy exceeds a predetermined maximum energy level, the current block minimum energy is discarded and the previous determination remains unchanged. If the current block minimum energy is below the previous determination, the previous estimate is reduced by the difference between the previous determination and current minimum energy. If the current energy is above the previous determination but below the maximum, the previous estimate is increased by half of the difference between the current energy and the previous estimate. The increase factor may also be adjusted to increase the current estimated energy level by a factor of any amount between and including 0 and 1. The estimation of minimum energy, or background energy, therefore decreases in direct proportion to a drop in minimum energy determination but increases only as a partial factor of new determinations.

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Germantown, MD, United States of America

Bogdan R Kosanovic