Abstract:
A pitch estimation system including a low-frequency band noise detector (LBND) operative to detect the presence of low-frequency band noise in a first audio frame, a frequency-domain pitch estimator operative to calculate a pitch estimation of a second audio frame from at least one spectral peak in the second audio frame, and a pitch estimator controller operative to cause the pitch estimator to exclude from the spectrum of the second audio frame at least one low-frequency spectral peak below a predefined threshold where low-frequency band noise is present in the first audio frame.

Description:
FIELD OF THE INVENTION 
   The present invention relates to speech processing in general, and more particularly to pitch estimation of speech segments in the presence of low-frequency band noise. 
   BACKGROUND OF THE INVENTION 
   Pitch estimation in speech processing can be used to distinguish between voiced and unvoiced speech segments and to represent the tone of voiced speech. Since voiced speech can be approximated using a periodic signal, pitch may be estimated by measuring the signal period or its inverse, which is referred to as the fundamental frequency or pitch frequency. Where a periodic signal cannot be used to approximate a speech segment, the speech segment may be designated as unvoiced. 
   A variety of techniques have been developed for pitch estimation in both the time domain and the frequency domain. While both time-domain and frequency-domain methods of pitch determination are subject to instability and error, and accurate pitch determination is computationally intensive, frequency-domain methods are generally more tolerant with respect to the deviation of real speech data from the exact periodic model. 
   The Fourier transform of a periodic signal, such as voiced speech, has the form of a train of impulses, or peaks, in the frequency domain. This impulse train corresponds to the line spectrum of the signal, which can be represented as a sequence {(a i ,θ i )}, where θ i  are the frequencies of the peaks, and a i  are the respective complex-valued line spectral amplitudes. To determine whether a given segment of a speech signal is voiced or unvoiced, and to calculate the pitch if the segment is voiced, the time-domain signal is first multiplied by a finite smooth window. The Fourier transform of the windowed signal is then given by 
               X   ⁡     (   θ   )       =       ∑   k     ⁢       a   k     ⁢     W   ⁡     (     θ   -     θ   k       )             ,         
where W(θ) is the Fourier transform of the window. Frequency-domain pitch estimation is typically based on analyzing the locations and amplitudes of the peaks in the transformed signal X(θ).
 
   Given any pitch frequency, the line spectrum corresponding to that pitch frequency could contain line spectral components at multiples of that frequency only. It therefore follows that any frequency appearing in the line spectrum should be a multiple of the pitch frequency. Consequently, pitch frequency could be found as the maximal integer divider of the frequencies of spectral peaks appearing in the transformed signal. However, the presence of background noise and other deviations from the periodic model causes spectral peaks to move away from their exact prescribed locations, and spurious spectral peaks to appear at unpredictable locations as well. 
   It follows from the periodic model that changing of pitch frequency results in relatively minor changes in the low frequency spectral line locations and relatively significant deviations of the high frequency spectral line locations. Consequently, low frequency spectral peaks have greater influence on pitch estimation than do high frequency spectral peaks. For this reason, the accuracy of frequency-domain pitch estimation deteriorates significantly in the presence of low-frequency band noise. Low-frequency band noise is often present in the passenger compartment of a moving or idling automobile, thus severely limiting the applicability of known frequency-domain pitch estimation methods in mobile environments. 
   SUMMARY OF THE INVENTION 
   The present invention provides for low-frequency band noise detection and compensation in support of frequency-domain pitch estimation of speech segments. A low-frequency band noise detector is provided, and low-frequency spectral peaks below a predefined threshold are excluded from frequency-domain pitch estimation calculations only if low-frequency band noise is detected. 
   In one aspect of the present invention a pitch estimation system is provided including a low-frequency band noise detector (LBND) operative to detect the presence of low-frequency band noise in a first audio frame, a frequency-domain pitch estimator operative to calculate a pitch estimation of a second audio frame from at least one spectral peak in the second audio frame, and a pitch estimator controller operative to cause the pitch estimator to exclude from the spectrum of the second audio frame at least one low-frequency spectral peak located below a predefined frequency threshold where low-frequency band noise is present in the first audio frame. 
   In another aspect of the present invention the LBND is operative to determine the spectrum of the first audio frame, calculate a measure R curr  of the relative spectral components level in the frequency band [0, F c ] of the first audio frame, where F c  is a predefined threshold value, calculate an integrative measure R of the relative spectral components level in the frequency band [0, F c ] of a plurality of audio frames from the R curr  values of each of the plurality of audio frames, and determine that low-frequency band noise is present if R&gt;R 0 , where R 0  is a predefined threshold value. 
   In another aspect of the present invention the predefined threshold value is between about 270 Hz and about 330 Hz. 
   In another aspect of the present invention the predefined threshold value is about 300 Hz. 
   In another aspect of the present invention the predefined threshold value F c  is between about 330 Hz and about 430 Hz. 
   In another aspect of the present invention the predefined threshold value F c  is about 380 Hz. 
   In another aspect of the present invention the integrative measure R is calculated using the formula R←F(R, R curr ). 
   In another aspect of the present invention the first audio frame is a non-speech frame. 
   In another aspect of the present invention the second audio frame is a speech frame. 
   In another aspect of the present invention the first audio frame precedes the second audio frame. 
   In another aspect of the present invention the system further includes a voice activity detector (VAD) operative to detect whether the first audio frame is a speech frame or a non-speech frame, and where the LBND is operative where the first audio frame is a non-speech frame. 
   In another aspect of the present invention a pitch estimation method is provided including detecting the presence of low-frequency band noise in a first audio frame, and calculating a pitch estimation of a second audio frame from at least one spectral peak in the second audio frame associated with a frequency above a predefined frequency threshold where low-frequency band noise is present in the first audio frame. 
   In another aspect of the present invention the detecting step includes determining the spectrum of the first audio frame, calculating a measure R curr  of the relative spectral components level in the frequency band [0, F c ] of the first audio frame, where F c  is a predefined threshold value, calculating an integrative measure R of the relative spectral components level in the frequency band [0, F c ] of a plurality of audio frames from the R curr  values of each of the plurality of audio frames, and determining that low-frequency band noise is present if R&gt;R 0 , where R 0  is a predefined threshold value. 
   In another aspect of the present invention the calculating step includes calculating where the predefined threshold value is between about 270 Hz and about 330 Hz. 
   In another aspect of the present invention the calculating step includes calculating where the predefined threshold value is about 300 Hz. 
   In another aspect of the present invention the calculating a measure R curr  step includes calculating where the predefined threshold value F c  is between about 330 Hz and about 430 Hz. 
   In another aspect of the present invention the calculating a measure R curr  step includes calculating where the predefined threshold value F c  is about 380 Hz. 
   In another aspect of the present invention the calculating an integrative measure step includes calculating using the formula R←F(R, R curr ). 
   In another aspect of the present invention the detecting step includes detecting for a non-speech frame. 
   In another aspect of the present invention the calculating step includes calculating for a speech frame. 
   In another aspect of the present invention the detecting step includes detecting for the first audio frame that precedes the second audio frame. 
   In another aspect of the present invention the method further includes detecting whether the first audio frame is a speech frame or a non-speech frame, and where the first detecting step includes detecting where the first audio frame is a non-speech frame. 
   In another aspect of the present invention a computer program embodied on a computer-readable medium is provided, the computer program including a first code segment operative to detect the presence of low-frequency band noise in a first audio frame, and a second code segment operative to calculate a pitch estimation of a second audio frame from at least one spectral peak in the second audio frame above a predefined threshold where low-frequency band noise is present in the first audio frame. 
   In another aspect of the present invention the computer program further includes a third code segment operative to cause the second code segment to exclude from the spectrum of the second audio frame at least one low-frequency spectral peak below a predefined threshold where low-frequency band noise is present in the first audio frame. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The present invention will be understood and appreciated more fully from the following detailed description taken in conjunction with the appended drawings in which: 
       FIG. 1  is a simplified graphical illustration of automobile passenger compartment noise and babble noise spectra, useful in understanding the present invention; 
       FIGS. 2A ,  2 B, and  2 C are simplified graphical illustrations of pitch contours estimated from, respectively, a clean speech signal, the speech signal plus babble noise, and the speech signal plus automobile noise, useful in understanding the present invention; 
       FIG. 3  is a simplified block diagram illustration of a pitch estimation system incorporating a low-frequency band noise detector, constructed and operative in accordance with a preferred embodiment of the present invention; 
       FIG. 4A  is a simplified flowchart illustration of a method of operation a low-frequency band noise detector, operative in accordance with a preferred embodiment of the present invention; 
       FIG. 4B  is a simplified flowchart illustration of a method of operation a pitch estimator controller, operative in accordance with a preferred embodiment of the present invention; and 
       FIGS. 5A ,  5 B, and  5 C are simplified graphical illustrations of pitch contours estimated from, respectively, a clean speech signal, the speech signal plus babble noise, and the speech signal plus automobile noise after application of the present invention. 
   

   DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
   In the present invention a digitized audio signal is preferably divided into frames of appropriate duration and relative offset, such as 25 ms and 10 ms respectively, for subsequent processing. Pitch is preferably estimated once for each frame, with the obtained sequence of pitch values being referred to as the pitch contour of the digitized audio signal. 
   Reference is now made to  FIG. 1 , which is a simplified graphical illustration of automobile passenger compartment noise and babble noise spectra, useful in understanding the present invention. In  FIG. 1  an amplitude spectrum of automobile passenger compartment noise of a moving or idling car is shown as a solid line  100 . By contrast, an amplitude spectrum of babble noise of the same intensity is shown as a dashed line  102 . It may be seen that the most prominent spectral components of the automobile noise are located below 380 Hz, while most of the babble noise spectrum energy resides above this frequency. 
   Reference is now made to  FIGS. 2A ,  2 B, and  2 C, which are simplified graphical illustrations of pitch contours estimated from, respectively, a clean speech signal, the speech signal plus babble noise, and the speech signal plus automobile noise, useful in understanding the present invention. In  FIGS. 2A ,  2 B, and  2 C, pitch is measured in samples corresponding to an 8 KHz sampling rate. Pitch values for unvoiced frames are set to zero. It may be seen in  FIG. 2C  relative to  FIGS. 2A and 2B  how pitch estimation accuracy using spectral peaks will be degraded under automobile noise conditions. Gross pitch errors and wrong voiced/unvoiced decisions appear on the pitch contour obtained from the speech signal affected by the background automobile noise. 
   Reference is now made to  FIG. 3 , which is a simplified block diagram illustration of a pitch estimation system incorporating a low-frequency band noise detector, constructed and operative in accordance with a preferred embodiment of the present invention. In the system of  FIG. 3 , one or more frames of an audio stream are received at a voice activity detector (VAD)  300  which detects whether or not a received frame contains speech using conventional techniques, where non-speech frames represent silence or background noise. Speech frames are passed to a pitch estimator  302 , which may employ any known frequency-domain pitch estimation method, such as that which is described in U.S. patent application Ser. No. 09/617,582, being assigned to the assignee of the present application. 
   Non-speech frames are passed to a low-frequency band noise detector (LBND)  304  which determines whether or not low-frequency band noise is present. A preferred method of operation of LBND  304  is described in greater detail hereinbelow with reference to  FIG. 4A . LBND  304  then provides a signal to a pitch estimator controller (PEC)  306  indicating whether or not low-frequency band noise is present. PEC  306  then modifies the mode of operation of pitch estimator  302  in accordance with the signal received from LBND  304 . A preferred method of operation of PEC  306  is described in greater detail hereinbelow with reference to  FIG. 4B . 
   Reference is now made to  FIG. 4A , which is a simplified flowchart illustration of a method of operation a low-frequency band noise detector, such as LBND  304  of  FIG. 3 , operative in accordance with a preferred embodiment of the present invention. In the method of  FIG. 4  the spectrum of a non-speech frame is determined, and a measure R curr  of the relative spectral components level in the frequency band [0, F c ] is calculated, where F c  is a predefined threshold value, such as any value between about 330 Hz and about 430 Hz (e.g., about 380 Hz). A variable R is maintained which is a weighted average of the R curr  values obtained from individual non-speech frames. R is an integrative measure of R curr  values of multiple non-speech frames, and is preferably updated using the latest R curr  value in the formula R←F(R, R curr ). It may be determined that low-frequency band noise is present if R&gt;R 0 , where R 0  is a predefined threshold value, and a signal may be generated indicating whether or not low-frequency band noise is present. 
   For example, let S(k), k=1, . . . , L be a power spectrum of a non-speech frame sampled at positive FFT frequencies. Let K c  be F c  rounded to the nearest FFT frequency point index. Then R curr =0 if (ΣS(k))/L&lt;500, otherwise 
             R   curr     =         max   ⁢           ⁢     S   ⁡     (   k   )           0   &lt;   k   &lt;     K   c         /         max   ⁢           ⁢   S   ⁢     (   k   )           K   c     &lt;   k   &lt;   L       .             
The averaged measure update formula is R←(0.99R+0.01R curr ). The threshold value is R 0 =1.9. R may be initialized to R=R 0 .
 
   Reference is now made to  FIG. 4B , which is a simplified flowchart illustration of a method of operation of a pitch estimator controller, such as PEC  306  of  FIG. 3 , operative in accordance with a preferred embodiment of the present invention. If no low-frequency band noise has been detected, PEC  306  sets pitch estimator  302  to use any of the spectral peaks of a speech frame in any frequency range in its pitch estimation calculations. Conversely, if low-frequency band noise has been detected, PEC  306  sets pitch estimator  302  to exclude low-frequency spectral peaks below a predefined threshold, such as any value between about 270 Hz and about 330 Hz (e.g., about 300 Hz), from its pitch estimation calculations. Pitch estimator  302  preferably continues to operate in accordance with the most recent settings made by PEC  306  based on the low-frequency band noise analysis of the most recent non-speech frame. 
   Reference is now made to  FIGS. 5A ,  5 B, and  5 C, which are simplified graphical illustrations of pitch contours estimated from, respectively, a clean speech signal, the speech signal plus babble noise, and the speech signal plus automobile noise after application of the present invention, useful in understanding the present invention.  FIG. 5C  shows how pitch estimation accuracy using spectral peaks may be improved when compared to  FIG. 2C  by applying the system and method of the present invention.  FIG. 5A  and  FIG. 5B  show, when compared to  FIG. 2A  and  FIG. 2B  respectively, that high pitch estimation accuracy achieved in absence of low band noise is not significantly affected by applying the system and method of the present invention. 
   It is appreciated that one or more of the steps of any of the methods described herein may be omitted or carried out in a different order than that shown, without departing from the true spirit and scope of the invention. 
   While the methods and apparatus disclosed herein may or may not have been described with reference to specific computer hardware or software, it is appreciated that the methods and apparatus described herein may be readily implemented in computer hardware or software using conventional techniques. 
   While the present invention has been described with reference to one or more specific embodiments, the description is intended to be illustrative of the invention as a whole and is not to be construed as limiting the invention to the embodiments shown. It is appreciated that various modifications may occur to those skilled in the art that, while not specifically shown herein, are nevertheless within the true spirit and scope of the invention.