Qnx Software Systems Limited

Qnx Software Systems Co.

Qnx Software Systems (Wavemakers), Inc.

2236008 Ontario Limited

Rajeev Nongpiur

Phillip Alan Hetherington

Xueman Li

David Giesbrecht

Shreyas Anand Paranjpe

Frank Linseisen

Phillip A Heterington

Phillip A Hetherington

Background noise is modeled from an input signal comprising a desired signal and a plurality of undesired signals. At least one of the signals that comprise the input is processed to generate a signal-to-noise ratio. An articulation index is generated for the at least one of the signals that is processed. A spectrum of a speech segment is generated to improve intelligibility and quality of the speech segment based on the articulation index. A shaping logic may adjust the spectrum of the speech segment based on a comparison of the articulation index to a plurality of predetermined thresholds. Modeling of the background noise comprises modeling a tilt of the background noise.

Improving speech intelligibility utilizing an articulation index

A system improves speech intelligibility by reconstructing speech segments. The system includes a low-frequency reconstruction controller programmed to select a predetermined portion of a time domain signal. The low-frequency reconstruction controller substantially blocks signals above and below the selected predetermined portion. A harmonic generator generates low-frequency harmonics in the time domain that lie within a frequency range controlled by a background noise modeler. A gain controller adjusts the low-frequency harmonics to substantially match the signal strength to the time domain original input signal.

Speech enhancement through partial speech reconstruction

A multi-channel signal enhancement system reinforces signal content and improves the signal-to-noise ratio of a multi-channel signal. The system detects, tracks, and reinforces non-stationary periodic signal components of a multi-channel signal. The periodic signal components of the signal may represent vowel sounds or other voiced sounds. The system may detect, track, or attenuate quasi-stationary signal components in the multi-channel signal.

Multi-channel periodic signal enhancement system

A noise suppression system reduces low-frequency noise in a speech signal using linear predictive coefficients in an adaptive filter. A digital filter may update or adapt a limited set of linear predictive coefficients on a sample-by-sample basis. The linear predictive coefficients may be used to provide an error signal based on a difference between the speech signal and a delayed speech signal. The error signal represents an enhanced speech signal having attenuated and normalized low-frequency noise components.

Adaptive LPC noise reduction system

A speech enhancement system improves the speech quality and intelligibility of a speech signal. The system includes a time-to-frequency converter that converts segments of a speech signal into frequency bands. A signal detector measures the signal power of the frequency bands of each speech segment. A background noise estimator measures a background noise detected in the speech signal. A dynamic noise reduction controller dynamically models the background noise in the speech signal. The speech enhancement renders a speech signal perceptually pleasing to a listener by dynamically attenuating a portion of the noise that occurs in a portion of the spectrum of the speech signal.

Dynamic noise reduction using linear model fitting

A signal enhancement system reinforces signal content and improves the signal-to-noise ratio of a signal. The system detects, tracks, and reinforces non-stationary periodic signal components of a signal. The periodic signal components may represent vowel sounds or other voiced sounds. The system may detect, track, and attenuate quasi-stationary signal components in the signal.

Sub-band periodic signal enhancement system

A system improves the speech intelligibility and the speech quality of a speech segment. The system includes a dynamic controller that detects a background noise from an input by modeling a signal. A variable gain amplifier adjusts the variable gain of the amplifier in response to an output of dynamic controller. A shaping filter adjusts a speech signal by tilting portions of the speech signal of the dynamic controller.

Dynamic controller for improving speech intelligibility

A system extends the high-frequency spectrum of a narrowband audio signal in the time domain. The system extends the harmonics of vowels by introducing a non linearity in a narrow band signal. Extended consonants are generated by a random-noise generator. The system differentiates the vowels from the consonants by exploiting predetermined features of a speech signal.

High-frequency bandwidth extension in the time domain

A signal enhancement system improves the understandability of speech or other audio signals. The system reinforces selected parts of the signal, may attenuate selected parts of the signal, and may increase SNR. The system includes delay logic, a partitioned adaptive filter, and signal reinforcement logic. The partitioned adaptive filter may track and enhance the fundamental frequency and harmonics in the input signal. The partitioned filter output signals may approximately reproduce the input signal, delayed by an integer multiple of the period of the fundamental frequency of the input signal. The reinforcement logic combines the input signal and the filtered signals to produce an enhanced output signal.

Periodic signal enhancement system

An enhancement system extracts pitch from a processed speech signal. The system estimates the pitch of voiced speech by deriving filter coefficients of an adaptive filter and using the obtained filter coefficients to derive pitch. The pitch estimation may be enhanced by using various techniques to condition the input speech signal, such as spectral modification of the background noise and the speech signal, and/or reduction of the tonal noise from the speech signal.

Adaptive filter pitch extraction

A system extends the high-frequency spectrum of a narrow band audio signal in the time domain. The system extends the harmonics of vowels by introducing a non linearity in a narrow band signal. Extended consonants are generated by a random-noise generator. The system differentiates the vowels from the consonants by exploiting predetermined features of a speech signal.

A transient noise removal system removes or dampens undesired transients from speech. When the transient noise removal system receives a speech frame, the system performs a wavelet transform analysis. The speech frame may be represented by one or more wavelet coefficients across one or more wavelet levels. For a given wavelet level, the transient noise-removal system may determine a wavelet threshold. The transient noise removal system may compare the threshold corresponding to a wavelet level to the wavelet coefficients within that level. The transient noise removal system may attenuate each wavelet coefficient based on a comparison to a threshold.

Transient noise removal system using wavelets

An enhancement system improves the perceptual quality of a processed speech. The system includes a delay unit that delays a signal received through a discrete input. A spectral modifier linked to the delay unit is programmed to substantially flatten the spectral character of a background noise. An adaptive filter linked to the spectral modifier adapts filter characteristics to match a response of a non-delayed signal. A programmable filter is linked to the delay unit. The programmable filter has a transfer function functionally related to a transfer function of the adaptive filter.

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Rajeev Nongpiur