Signal noise reduction by spectral subtraction using linear...

Details Signal noise reduction by spectral subtraction using linear... Signal noise reduction by spectral subtraction using linear...

1998-05-27

2001-01-16

Tse, Young T. (Department: 2734)

Pulse or digital communications

Receivers

Interference or noise reduction

C375S285000, C704S225000, C704S226000, C708S404000, C455S063300, C455S067700

Reexamination Certificate

active

06175602

ABSTRACT:

FIELD OF THE INVENTION
The present invention relates to communications systems, and more particularly, to methods and apparatus for mitigating the effects of disruptive background noise components in communications signals.
BACKGROUND OF THE INVENTION
Today, the use of hands-free equipment in mobile telephones and other communications devices is increasing. A well known problem associated with hands-free solutions, particularly in automobile applications, is that of disruptive background noise being picked up at a hands-free microphone and transmitted to a far-end user. In other words, since the distance between a hands-free microphone and a near-end user can be relatively large, the hands-free microphone picks up not only the near-end user's speech, but also any noise which happens to be present at the near-end location. For example, in an automobile telephone application, the near-end microphone typically picks up surrounding traffic, road and passenger compartment noise. The resulting noisy near-end speech can be annoying or even intolerable for the far-end user. It is thus desirable that the background noise be reduced as much as possible, preferably early in the near-end signal processing chain (e.g., before the received near-end microphone signal is input to a near-end speech coder).
As a result, many hands-free systems include a noise reduction processor designed to eliminate background noise at the input of a near-end signal processing chain.
FIG. 1
is a high-level block diagram of such a hands-free system
100
. In
FIG. 1
, a noise reduction processor
110
is positioned at the output of a hands-free microphone
120
and at the input of a near-end signal processing path (not shown). In operation, the noise reduction processor
110
receives a noisy speech signal x from the microphone
120
and processes the noisy speech signal x to provide a cleaner, noise-reduced speech signal S
NR
which is passed through the near-end signal processing chain and ultimately to the far-end user.
One well known method for implementing the noise reduction processor
110
of
FIG. 1
is referred to in the art as spectral subtraction. See, for example, S. F. Boll, Suppression of Acoustic Noise in Speech using Spectral Subtraction,
IEEE Trans. Acoust. Speech and Sig. Proc
., 27:113-120, 1979, which is incorporated herein by reference. Generally, spectral subtraction uses estimates of the noise spectrum and the noisy speech spectrum to form a signal-to-noise (SNR) based gain function which is multiplied with the input spectrum to suppress frequencies having a low SNR. Though spectral subtraction does provide significant noise reduction, it suffers from several well known disadvantages. For example, the spectral subtraction output signal typically contains artifacts known in the art as musical tones. Further, discontinuities between processed signal blocks often lead to diminished speech quality from the far-end user perspective.
Many enhancements to the basic spectral subtraction method have been developed in recent years. See, for example, N. Virage, Speech Enhancement Based on Masking Properties of the Auditory System,
IEEE ICASSP. Proc
. 796-799 vol. 1, 1995; D. Tsoukalas, M. Paraskevas and J. Mourjopoulos, Speech Enhancement using Psychoacoustic Criteria,
IEEE ICASSP. Proc
., 359-362 vol. 2, 1993; F. Xie and D. Van Compernolle, Speech Enhancement by Spectral Magnitude Estimation—A Unifying Approach,
IEEE Speech Communication
, 89-104 vol. 19, 1996; R. Martin, Spectral Subtraction Based on Minimum Statistics,
UESIPCO, Proc
., 1182-1185 vol. 2, 1994; and S. M. McOlash, R. J. Niederjohn and J. A. Heinen, A Spectral Subtraction Method for Enhancement of Speech Corrupted by Nonwhite, Nonstationary Noise,
IEEE IECON. Proc
., 872-877 vol. 2, 1995.
While these methods do provide varying degrees of speech enhancement, it would nonetheless be advantageous if alternative techniques for addressing the above described spectral subtraction problems relating to musical tones and inter-block discontinuities could be developed. Consequently, there is a need for improved methods and apparatus for performing noise reduction by spectral subtraction.
SUMMARY OF THE INVENTION
The present invention fulfills the above-described and other needs by providing improved methods and apparatus for performing noise reduction by spectral subtraction. According to exemplary embodiments, spectral subtraction is carried out using linear convolution, causal filtering and/or spectrum dependent exponential averaging of the spectral subtraction gain function. Advantageously, systems constructed in accordance with the invention provide significantly improved speech quality as compared to prior art systems without introducing undue complexity.
According to the invention, low order spectrum estimates are developed which have less frequency resolution and reduced variance as compared to spectrum estimates in conventional spectral subtraction systems. The spectra according to the invention are used to form a gain function having a desired low variance which in turn reduces the musical tones in the spectral subtraction output signal. According to exemplary embodiments, the gain function is further smoothed across blocks by using input spectrum dependent exponential averaging. The low resolution gain function is interpolated to the full block length gain function, but nonetheless corresponds to a filter of the low order length. Advantageously, the low order of the gain function permits a phase to be added during the interpolation. The gain function phase, which according to exemplary embodiments can be either linear phase or minimum phase, causes the gain filter to be causal and prevents discontinuities between blocks. In exemplary embodiments, the casual filter is multiplied with the input signal spectra and the blocks are fitted using an overlap and add technique. Further, the frame length is made as small as possible in order to minimize introduced delay without introducing undue variations in the spectrum estimate.
In one exemplary embodiment, a noise reduction system includes a spectral subtraction processor configured to filter a noisy input signal to provide a noise reduced output signal. The gain function of the spectral subtraction processor is computed based on an estimate of a spectral density of the input signal and on an estimate of a spectral density of a noise component of the input signal. Further, a block of samples of the noise reduced output signal is computed based on a respective block of samples of the input signal and on a respective block of samples of the gain function, and an order of the block of computed samples of the output signal is greater than a sum of an order of the respective block of samples of the input signal and an order of the respective block of samples of the gain function.
In exemplary embodiments, the block of computed samples of the output signal is computed based on a correct convolution of the respective block of samples of the input signal and the respective block of samples of the gain function. For example, a block of N samples of the output signal is computed based on a block of L samples of the input signal and on a block of M samples of the gain function, wherein the sum of L and M is less than N. The block of M samples of the gain function can be computed, for example, using spectral estimation based on the L samples of the input signal. According to exemplary embodiments, the spectral estimation is carried out using either a Bartlett method or a Welch method. Successive blocks of the output signal are fitted using an overlap and add method, and a phase is added to the gain function so that the spectral subtraction processor provides causal filtering. Advantageously, the gain function can have either linear phase or minimum phase.
An exemplary method according to the invention includes the steps of computing an estimate of a spectral density of an input signal and an estimate of a spectral density of a noise component of the input signal, and using spectral subtra

Affiliated with

Also associated with

Rating

Signal noise reduction by spectral subtraction using linear... does not yet have a rating. At this time, there are no reviews or comments for this patent.

If you have personal experience with Signal noise reduction by spectral subtraction using linear..., we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Signal noise reduction by spectral subtraction using linear... will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFUS-PAI-O-2473141