Data processing: speech signal processing – linguistics – language – Speech signal processing – For storage or transmission
Reexamination Certificate
2001-04-04
2004-10-05
Vo, Nguyen T. (Department: 2655)
Data processing: speech signal processing, linguistics, language
Speech signal processing
For storage or transmission
C704S225000, C375S285000, C375S254000, C375S346000
Reexamination Certificate
active
06801889
ABSTRACT:
BACKGROUND OF THE INVENTION
The invention concerns a process for reducing noise signals in telecommunications (TC) systems for the transmission of acoustic useful signals, in particular human speech.
A known process for noise reduction is so-called “spectral subtraction”, that is described in the publication “A new approach to noise reduction based on auditory masking effects” by S. Gustafsson and P. Jax, ITG Conference, Dresden, 1998, for example. This involves a spectral noise reduction method in which an acoustic masking threshold (for example following the MPEG standard) is taken into consideration.
During natural communication between humans, the amplitude of the spoken language is usually adapted to the acoustic environment automatically. In the case of speech communication between distant locations, however, the interlocutors are not in the same acoustic surroundings and each is not therefore aware of the acoustic situation at the location of the other interlocutor. The problem therefore gets worse if, because of his/her acoustic environment, one of the parties is forced to speak very loudly while the other party in a quiet acoustic environment produces voice signals with lower amplitude.
Noise problems are particularly acute in new communication systems applications, for example mobile telephones, in which the terminals are made so small that a direct spatial juxtaposition between loudspeaker and microphone cannot be avoided. Because of the direct sound transmission, in particular structure-borne noise between loudspeaker and microphone the acoustic interference signal can have the same order of magnitude as the useful signal of the speaker at the respective terminal or its amplitude can even exceed this signal. Such a noise problem also occurs to a significant degree in the case of several terminals arranged spatially adjacent to each other, for example in an office or conference room with a number of telephone connections, since a coupling takes place from each loudspeaker signal to each microphone.
Added to this is the problem that on a telecommunications channel “electronically generated” noise also occurs and is transmitted as background along with the useful signal. In order to increase comfort while making a telephone call, one therefore endeavours to keep each type of noise as low as possible in comparison to the useful signal.
Finally, one also endeavours to reduce or completely suppress interference signals such as undesirable background noise (traffic noise, factory noise, office noise, canteen noise, aircraft noise, etc.).
In the known compander process, such as described in DE 42 29 912 A1, the degree of noise reduction is determined by a fixed, predetermined transfer function. First of all, the compander has the property of transmitting voice signals at a specific (previously set) “normal speech signal level” (sometimes referred to as normal loudness) virtually unchanged from its input to the output. If, however, the input signal now becomes too loud, for example because a speaker comes too close to its microphone, then a dynamic compressor limits the output level to virtually the same value as in the normal case, by reducing the actual gain in the compander linearly with increasing input loudness. Due to this characteristic the speech at the output of the compander system remains more or less at the same loudness—irrespective of how widely the input loudness fluctuates. On the other hand, if a signal with a level that is lower than the normal level is now applied to the input of the compander, then the signal is additionally attenuated by reducing the gain in order to transmit background noise that is attenuated as far as possible. The compander thus consists of two partial functions, a compressor for the speech signal levels that are higher than or equal to a normal level, and an expander for signal levels that are lower than the normal level.
In the case of the above-mentioned spectral subtraction, to this end the noise is first measured in the speech pauses and continuously stored in a memory in the form of a power spectral density. The power spectral density is obtained via a Fourier transformation. When speech occurs, the stored noise spectrum is subtracted from the current disturbed speech spectrum “as best current estimated value”, then transformed back into the time domain in order by this means to obtain a noise reduction for the disturbed signal.
A disadvantage of such methods is the complicated determination of this acoustic masking threshold and the execution of all computing operations associated with this method. A further disadvantage of spectral subtraction is that due to the process of a basically inaccurate spectral noise estimate and subsequent subtraction, errors which are perceptible as “musical tones”, also occur in the output signal.
With extended spectral signal processing, which is also described in the citation mentioned at the beginning, the power spectral densities are estimated for the noise and for the speech itself with the aid of a spectral subtraction. Knowing these partial spectra, a spectral acoustic masking threshold R
T
(f) is then calculated for the human ear with the aid of MPEG Standard rules, for example. Using this masking threshold and the estimated spectra for noise and speech, and following a simple rule, a filter passband curve H(f) is calculated, which is configured so that essential spectral components of the speech are transmitted with as little modification as possible and spectral components of the noise are reduced as much as possible.
The original disturbed speech signal is then passed only through this filter to obtain a noise reduction for the disturbed signal by these means. The advantage of this method is now that “nothing is added to or subtracted from” the disturbed signal and therefore errors in the estimations are less perceptible or even scarcely perceptible. A disadvantage is again the considerably greater computing power.
A particular disadvantage of all these known methods is the fact that the incoming original signal undergoes a signal processing process prior to the actual subtraction of a noise signal that is always simulated, and is therefore basically corrupted.
SUMMARY OF THE INVENTION
In contrast, the object of the present invention is to present a process with least possible complexity having the features described at the outset, in which a noise reduction or noise suppression is achieved in an uncomplicated technical manner, and in which the original signal remains uncorrupted right up to the actual noise subtraction. At the same time, with simple means, in particular with less computing power than previously, the process should enable an overall acoustic impression to be produced, which is as agreeable as possible to the human ear and which, according to taste, can be matched to individual requirements. Finally, the new process should be capable of being implemented completely independently of the speech signal processing requirements and thus enable simple optimisation to the spectral processing requirements of noise signals.
This object is achieved according to the invention in both a simple and effective manner by the following process steps:
(a) Determining by means of speech pause detection when a speech pause is contained in the mixture of useful signals and interference signals to be transmitted, or when a speech pause is present;
(b) Branching the incoming TC signal from the main signal path and using a Fourier transformation on the branched TC signal to generate a frequency spectrum of the branched TC signal;
(c) Storing in a buffer memory the last frequency spectrum recorded during the last speech pause;
(d) Using an inverse Fourier transformation on the last respective recorded frequency spectrum to generate a simulated noise signal;
(e) Subtracting the simulated noise signal in the time domain from the current incoming TC signal.
Due to the separate simulation of the noise signal in the frequency domain independently of a processing of the original speech signal, the
Alcatel
Brant Dmitry
Vo Nguyen T.
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