Abstract:
An analog signal is received from an acoustic transducer. The analog signal is converted into digital data. A determination is made as to whether acoustic activity exists within the digital data. The digital data is stored in a temporary memory storage device and a count is maintained of an amount of digital data in the temporary memory storage device. When the count exceeds a predetermined threshold, at least some of the digital data is transmitted from the temporary memory storage device to a processor.

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
       [0001]    This patent claims benefit under 35 U.S.C. §119(e) to U.S. Provisional Application No. 62/105,900 entitled “Low Power Voice Trigger for Acoustic Apparatus and Method” filed Jan. 21, 2015, the content of which is incorporated herein by reference in its entirety. 
     
    
     TECHNICAL FIELD 
       [0002]    This application relates to acoustic devices and, more specifically, to the operation of these devices. 
       BACKGROUND OF THE INVENTION 
       [0003]    Different types of acoustic devices have been used through the years. One type of device is a microphone. In a microelectromechanical system (MEMS) microphone, a MEMS die includes a diagram and a back plate. The MEMS die is supported by a substrate and enclosed by a housing (e.g., a cup or cover with walls). A port may extend through the substrate (for a bottom port device) or through the top of the housing (for a top port device). In any case, sound energy traverses through the port, moves the diaphragm and creates a changing potential of the back plate, which creates an electrical signal. Microphones are deployed in various types of devices such as personal computers or cellular phones. 
         [0004]    Microphones are used in various applications that utilize voice trigger applications. In previous approaches, an acoustic activity detector detects a voice signal and sends out a signal to wake up a digital signal processor (DSP) for the detection of key phrases in the voice. Once the key phrase is found, all input speech data can be processed. Consequently, any time that the acoustic activity detector is triggering, the DSP is constantly searching for key phrases using power. Mobile and wearable devices have small batteries and can easily deplete these power levels are drained by the repeated triggering described above. 
         [0005]    The problems of previous approaches have resulted in some user dissatisfaction with these previous approaches. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0006]    For a more complete understanding of the disclosure, reference should be made to the following detailed description and accompanying drawings wherein: 
           [0007]      FIG. 1  comprises a block diagram of a microphone that provides a low power operation for voice trigger operations according to various embodiments of the present invention; 
           [0008]      FIG. 2  comprises a block diagram of state transition diagram showing the operation of a microphone that provides a low power operation for voice trigger operations according to various embodiments of the present invention; 
           [0009]      FIG. 3  comprises a graph that shows power consumption levels during the operation of a microphone that provides a low power operation for voice trigger operations according to various embodiments of the present invention. 
       
    
    
       [0010]    Skilled artisans will appreciate that elements in the figures are illustrated for simplicity and clarity. It will further be appreciated that certain actions and/or steps may be described or depicted in a particular order of occurrence while those skilled in the art will understand that such specificity with respect to sequence is not actually required. It will also be understood that the terms and expressions used herein have the ordinary meaning as is accorded to such terms and expressions with respect to their corresponding respective areas of inquiry and study except where specific meanings have otherwise been set forth herein. 
       DETAILED DESCRIPTION 
       [0011]    The present approaches provide approaches for the low power operation of a microphone during voice triggering applications. The output of the acoustic activity detector inside of the microphone is stored in internal memory (e.g., a random access memory (RAM)) via direct memory access (DMA) techniques. When the memory device reaches a predetermined capacity, a digital signal processor (DSP) (or other processing device) is woken up and the stored data is clocked from the internal memory device to the DSP via DMA (e.g., at a high frequency) via some data bus (e.g., an advanced high-speed bus (AHB)). 
         [0012]    Power consumption is reduced (especially in noisy environments) because in the approaches presented herein the DSP is periodically activated for processing small fragments of data very quickly to determine if a key phrase was detected. Also, the system is enabled to deactivate the DSP at times when acoustic activity is detected. Additionally, the present approaches allow for the periodic wake up and sleep of the DSP in noisy environments when the acoustic activity detector (AAD) would (in previous systems) be triggering. 
         [0013]    In many of these embodiments, microphone output triggered by an acoustic activity detector (AAD) is clocked into memory. When the data input into the memory reaches a predetermined value, the data is clocked out of the memory at a high frequency to a digital signal processor (DSP) via a data bus. If any part of a predetermined phrase is found by the DSP, the DSP processes more data stored in the memory to determine if the key phrase was received. If the entire phrase is recovered, the entire system (e.g., the DSP and associated consumer electronic devices it may be coupled to) is awakened. If the entire phrase is not recovered, the DSP returns to a sleep (low power) mode of operation. 
         [0014]    Referring now to  FIG. 1 , one example of a microphone (or microphone assembly)  100  is described. The microphone  100  includes a charge pump  102 , a microelectromechanical system (MEMS) device  104 , a sigma delta converter  106 , an acoustic activity detector (AAD) module  108 , a buffer  110 , a trigger control module  112 , a decimator  114 , a direct memory access (DMA) control module  116 , a memory controller  118 , a memory  120  (e.g., a RAM), and a digital signal processor (DSP)  122 . It will be appreciated that at least some of these components may be disposed on an application specific integrated circuit (ASIC). It will also be appreciated that other sound transducers such as piezoelectric devices or others may be used in place of the MEMS device. 
         [0015]    The charge pump  102  is a voltage or current source that is used to charge the MEMS device  104 . The MEMS device  104  includes a diaphragm and a back plate, and converts sound energy into electrical signals. The sigma delta converter  106  converts analog electrical signals into pulse density modulation (PDM) data. 
         [0016]    The AAD module  108  determines whether voice is detected in the incoming signal from the MEMS device  104 . These functions may be accomplished by various techniques known to those skilled in the art. The buffer  110  stores data, and in one example provides 250 ms of delay. The trigger control module  112  is triggered to release data when human voice is detected by the AAD module  108 . The decimator  114  converts the PDM data into PCM data. The DMA control module  116  controls the flow of data to and from the memory  120 , and to the DSP  122 . The memory controller  118  keeps a record of the amount of data that the DMA control module has loaded into the memory  120  and informs the DMA control module  116  when this amount exceeds a predetermined value. The DSP  122  determines whether particular trigger words or phrases are present in the data. 
         [0017]    It will be appreciated that these elements may be implemented in any combination of computer hardware and/or software. For instance, many if not all of these elements may be implemented using computer instructions executed on a processor. It will be further appreciated that these components may be disposed within a single assembly or covering structure. 
         [0018]    In one example of the operation of the system of  FIG. 1 , charge pump  102  charges the MEMS device  104 , which converts sound energy to an analog electrical signal. The analog electrical signal is converted into a digital PDM signal by the sigma delta converter  106 . The converted signal is stored in the buffer  110 . The AAD module  108  detects the presence of human voice in the signal and triggers the trigger control module  112  to release the data in the buffer  110  to the decimator  114 . The decimator  114  converts the data into pulse code modulation (PCM) data. The DMA control module stores the data into memory  120  (shown by path labeled  130 ). The memory controller  118  monitors the amount of data that has been stored in the memory  120 . When the amount reaches a predetermined value, the DMA causes data to be transmitted in a burst from the memory  120  to the DSP  122  (this data flow is indicted by the arrows labeled  132 ). This data transfer is accomplished by a bus  124 , which in one example is an advanced high-speed bus (AHB). Other examples are possible. 
         [0019]    The DSP  122  looks for any part of the key phrase. If any part is detected (even if in the later half of the phrase), the DSP  122  looks further back in the data to see if the beginning of the phrase was recorded to correlate for key word recognition. The above steps may be repeated if the memory  120  reaches the predetermined threshold again. It will be appreciated that various types of digital data (e.g., PDM, PCM and SoundWire). 
         [0020]    Referring now to  FIG. 2 , one example of a state transition diagram showing microphone operation is described. It will be appreciated that the state transitions shown in  FIG. 2 , utilize the components shown in  FIG. 1 . In this example, the system moves between a sensing mode state  202 , a write-to-RAM state  204 , a wake-up state  206 , a key phrase recognition state  208 , a look-back state  210 , and a system wake-up state  212 . At steps  202  and  204  the DSP is asleep. 
         [0021]    Beginning with state  202 , the system senses sound energy, for example, using a MEMS device (but other transducers such as piezoelectric transducers can also be used). When voice activity is determined by the AAD module, control moves to state  204  where the data is written to memory, for example, a RAM. 
         [0022]    When RAM reaches a predetermined capacity, control continues at step  206 , where the DSP is woken up and a burst of data is transmitted from the RAM to the DSP using the DMA control module and a data bus. When the DSP receives the data, control continues at step  208 , where key phrase recognition is performed. When no part of the predetermined key phrase is determined, control returns to step  202 . When part of the phrase is determined, control continues with step  210 . 
         [0023]    At step  210 , the DSP looks back in RAM for the entire phrase (assuming step  208  did not find the whole phrase). If the rest of the phrase is not found, control returns to step  202 . If the phrase is found, the system is woken up to perform further processing since the key phrase was found. 
         [0024]    Referring now to  FIG. 3 , one example of a graph showing the power levels used by the present approaches is described. As shown, DSP power amounts consumed (represented by the upwardly extending bars  302 ) represent the power used by the DSP when DMA transfer is used as described herein. The boxes labeled  304  represent power not used or consumed in the present approaches, but consumed in previous approaches (i.e., when DMA transfer was not used). The power amounts  304  are not consumed by the approaches described here because the DSP is not activated all the time (or most of the time) and searching for key phrases. In other words, power amounts  304  were used in previous systems, but not in the present approaches. 
         [0025]    It will be appreciated that while the higher frequency processing of greater amounts of data will require more power at some small intervals in time, it will allow the processing of data in significantly less periods of time. And, this mode of operation uses significantly less power than previous approaches. 
         [0026]    Put another way, although the peak values of amounts  302  are higher than the peak value of power amounts  304 , peak values  302  are consumed over very small periods or intervals of time, while power amounts  304  are consumed over comparatively much greater and longer periods or intervals of time. Thus, the total power consumed by power amounts  302  is significantly less than the power consumed by amounts  304 . 
         [0027]    Also, this mode of operation requires significantly less power consumption than previous voice triggers in noisy situations or environments when ambient noise levels are constantly triggering the AAD module. 
         [0028]    Preferred embodiments of this invention are described herein, including the best mode known to the inventors for carrying out the invention. It should be understood that the illustrated embodiments are exemplary only, and should not be taken as limiting the scope of the invention.