Abstract:
An apparatus for entering a flight plan into an aircraft navigation system, the apparatus comprising: an acoustic sampler adapted for sampling a microphone signal and generating an acoustic signal; a waypoint identifier adapted for generating an identified waypoint from the acoustic signal and the flight plan; and a navigation interface adapted for incorporating the identified waypoint into the flight plan and for transmitting and receiving navigation data to and from the aircraft navigation system.

Description:
BACKGROUND  
       [0001]     The present invention relates generally to the field of speech recognition and more specifically to the use of speech recognition to enter a flight plan into an aircraft navigation system.  
         [0002]     Recent advances in navigation devices for General Aviation (GA) aircraft have allowed these devices to convey a great deal of valuable information to the pilot. These devices share a common weakness, however, in their ability to accept detailed information back from the pilot. This weakness is particularly acute with regard to the entry of waypoints for a typical instrument flight plan.  
         [0003]     In typical current designs, panel space restrictions have forced avionics designers to use concentric knobs for waypoint identifier entry. Current procedures for entering a flight plan entail rotating a knob through the entire alpha-numeric alphabet for each character in each waypoint. For complex flight plans, such procedures are cumbersome and time consuming and significantly interfere with the pilot&#39;s need to scan instrument gauges, maintain visual separation from other aircraft, and attend to other critical tasks.  
         [0004]     Opportunities exist, therefore, to improve safety and efficiency in the piloting of GA aircraft by providing a speech recognition interface for entering a flight plan into the aircraft navigation system.  
       SUMMARY  
       [0005]     The opportunities described above are addressed, in one embodiment of the present invention, by an apparatus for entering a flight plan into an aircraft navigation system, the apparatus comprising: an acoustic sampler adapted for sampling a microphone signal and generating an acoustic signal; a waypoint identifier adapted for generating an identified waypoint from the acoustic signal and the flight plan; and a navigation interface adapted for incorporating the identified waypoint into the flight plan and for transmitting and receiving navigation data to and from the aircraft navigation system.  
         [0006]     Another aspect of the present invention is embodied by a method for entering a flight plan into an aircraft navigation system, the method comprising the acts of: sampling a microphone signal; generating an acoustic signal; generating an identified waypoint from the acoustic signal and the flight plan; incorporating the identified waypoint into the flight plan; and transmitting and receiving navigation data to and from the aircraft navigation system. 
     
    
     DRAWINGS  
       [0007]     These and other features, aspects, and advantages of the present invention will become better understood when the following detailed description is read with reference to the accompanying drawings in which like characters represent like parts throughout the drawings, wherein:  
         [0008]      FIG. 1  illustrates a block diagram in accordance with one embodiment of the present invention.  
         [0009]      FIG. 2  illustrates a block diagram in accordance with a more specific embodiment of the embodiment of  FIG. 1 .  
         [0010]      FIG. 3  illustrates a block diagram in accordance with a more specific embodiment of the embodiment of  FIG. 2 .  
         [0011]      FIG. 4  illustrates a block diagram in accordance with another more specific embodiment of the embodiment of  FIG. 2 .  
         [0012]      FIG. 5  illustrates a block diagram in accordance with another more specific embodiment of the embodiment of  FIG. 1 .  
         [0013]      FIG. 6  illustrates a block diagram in accordance with a more specific embodiment of the embodiment of  FIG. 5 . 
     
    
     DETAILED DESCRIPTION  
       [0014]     In accordance with one embodiment of the present invention,  FIG. 1  illustrates a block diagram of an apparatus  100  for entering a flight plan  170  into an aircraft navigation system  200 . Apparatus  100  comprises an acoustic sampler  130 , a waypoint identifier  150 , and a navigation interface  180 . In operation, acoustic sampler  130  samples a microphone signal  120  and generates an acoustic signal  140 ; waypoint identifier  150  generates an identified waypoint  160  from acoustic signal  140  and flight plan  170 ; and navigation interface  180  incorporates identified waypoint  160  into flight plan  170  and transmits and receives navigation data  190  to and from aircraft navigation system  200 . The transmitted portion of navigation data  190  includes, without limitation, flight plan  170 ; the received portion of navigation data  190  includes, without limitation, current aircraft position. To initialize flight plan  170 , waypoint identifier  150  generates a first identified waypoint from acoustic signal  140  and from the current aircraft position.  
         [0015]     In accordance with another embodiment of the present invention, acoustic sampler  130  additionally generates a speech flag signal  240  indicating which portions of acoustic signal  140  correspond to a combination of pilot speech and cabin noise and which portions correspond to cabin noise only. Waypoint identifier  150  then uses speech flag signal  240  to assist in generating identified waypoint  160 .  
         [0016]     In accordance with a more specific embodiment of the embodiment of  FIG. 1 ,  FIG. 2  illustrates a block diagram wherein waypoint identifier  150  comprises a vocabulary filter  270 , a geography filter  310 , and a waypoint constructor  330 . In operation, vocabulary filter  270  filters a vocabulary database  280  to yield a feasible vocabulary set  290 ; geography filter  310  filters a geography database  300  using flight plan  170  to yield a feasible waypoint set  320 ; and waypoint constructor  330  constructs identified waypoint  160  from feasible vocabulary set  290  and feasible waypoint set  320 . In some embodiments, acoustic signal  140  and speech flag signal  240  are also used by vocabulary filter  270  to filter vocabulary database  280 .  
         [0017]     In accordance with a more specific embodiment of the embodiment of  FIG. 2 , vocabulary database  280  comprises a phonetic alphabet  285 . Examples of phonetic alphabet  285  include, without limitation, the International Civil Aviation Organization alphabet wherein the words “alpha,” “bravo,” “charlie,” etc. respectively represent the letters “A,” “B,” “C,” etc.  
         [0018]     In accordance with a more specific embodiment of the embodiment of  FIG. 2 ,  FIG. 3  illustrates a block diagram wherein waypoint constructor  330  comprises a waypoint filter  360 , a model generator  380 , a feature extractor  340 , and a waypoint selector  400 . In operation, waypoint filter  360  filters feasible waypoint set  320  using feasible vocabulary set  290  to yield a candidate waypoint set  370 ; model generator  380  generates a waypoint model set  390  from candidate waypoint set  370 ; feature extractor  340  constructs a signal feature set  350  from acoustic signal  140 ; and waypoint selector  400  selects identified waypoint  160  by matching signal feature set  350  to an element of waypoint model set  390 .  
         [0019]     In accordance with a more detailed embodiment of the embodiment of  FIG. 3 , waypoint model set  390  comprises a set of hidden Markov word models. In some embodiments, each of the hidden Markov word models comprises a set of semi-hidden Markov triphone models. In some embodiments, waypoint selector  400  uses a Viterbi search method to match signal feature set  350  to an element of waypoint model set  390 . Hidden Markov word models, semi-hidden Markov triphone models, and Viterbi searches are techniques known to persons of ordinary skill in the art of speech recognition and are described in any modern text on speech recognition.  
         [0020]     In accordance with a more detailed embodiment of the embodiment of  FIG. 3 , feature extractor  340  uses a zero crossings with peak amplitudes (ZCPA) method. The ZCPA method is known to persons of ordinary skill in the art of speech recognition and is described in D. Kim, S. Lee, and R. M. Kil, “Auditory processing of speech signals for robust speech recognition in real-world noisy environments”, IEEE Trans. Speech Audio Processing, vol. 7, no. 1, pp. 55-69, January 1999.  
         [0021]     In accordance with another more specific embodiment of the embodiment of  FIG. 2 ,  FIG. 4  illustrates a block diagram wherein vocabulary filter  270  comprises a zero crossing detector  490  and a comparator  510 . In operation, zero crossing detector  490  detects zero crossings of acoustic signal  140  to yield a zero crossing set  500 . Comparator  510  compares zero crossing set  500  to zero crossing data from vocabulary database  280  to yield feasible vocabulary set  290 .  
         [0022]     In accordance with another more specific embodiment of the embodiment of  FIG. 1 ,  FIG. 5  illustrates a block diagram wherein acoustic sampler  130  comprises an analog-to-digital converter  210 , a speech detector  230 , a noise model  250 , and a subtracter  265 . In operation, analog-to-digital converter  210  converts microphone signal  120  to a raw acoustic signal  220 ; speech detector  230  generates speech flag signal  240  from raw acoustic signal  220 ; noise model  250  generates a noise estimate  260  from raw acoustic signal  220  and speech flag signal  240 ; and subtracter  265  subtracts noise estimate  260  from raw acoustic signal  220  to yield acoustic signal  140 .  
         [0023]     In accordance with a more detailed embodiment of the embodiment of  FIG. 5 , speech detector  230  generates speech flag signal  240  using a linked hidden Markov model. Use of linked hidden Markov models for this purpose is known to persons of ordinary skill in the art of speech recognition and is described in S. Basu, “A linked-HMM model for robust voicing and speech detection”, Proc. Int. Conf. Acoustic, Speech, and Signal Processing (ICASSP), vol. 1, pp. 816-819, 2003.  
         [0024]     In accordance with a more specific embodiment of the embodiment of  FIG. 5 ,  FIG. 6  illustrates a block diagram wherein noise model  250  comprises a noise extractor  410 , a magnitude calculator  430 , a phase calculator  450 , and a waveform constructor  470 . In operation, noise extractor  410  extracts a cabin noise signal  420  from raw acoustic signal  220  using speech flag signal  240 ; magnitude calculator  430  calculates an estimated magnitude set  440  from cabin noise signal  420 ; phase calculator  450  calculates an estimated phase set  460  from cabin noise signal  420 ; and waveform constructor  470  constructs noise estimate  260  from a set of noise signatures  480  using estimated magnitude set  440  and estimated phase set  460 .  
         [0025]     All of the elements described above of embodiments of the present invention may be implemented, by way of example, but not limitation, using singly or in combination any electric or electronic devices capable of performing the indicated functions. Examples of such devices include, without limitation: analog devices; analog computation modules; digital devices including, without limitation, small-, medium-, and large-scale integrated circuits, application specific integrated circuits (ASICs), and programmable logic arrays (PLAs); and digital computation modules including, without limitation, microcomputers, microprocessors, microcontrollers, and programmable logic controllers (PLCs).  
         [0026]     In some embodiments of the present invention, the elements described above are implemented as software components in a general purpose computer. In some embodiments, aircraft navigation system  200  is also a software component implemented in the same computer as apparatus  100 . Such software implementations produce a technical effect of recognizing pilot speech and entering a flight plan into an aircraft navigation system.  
         [0027]     While only certain features of the invention have been illustraed and described herein, many modifications and changes will occur to thoes skilled in the art. It is, therefore, to be underdstood that the appended claims are intended to cover all such modifications and changes as fall within the true spirt of the invention.