Patent Publication Number: US-10325592-B2

Title: Enhanced voice recognition task completion

Description:
TECHNICAL FIELD 
     The present invention relates to speech recognition systems for a vehicle, and more particularly, to speech recognition systems that respond to a wide variety of commands, or commands that are otherwise unpredictable. 
     INTRODUCTION 
     Voice recognition systems in vehicle are relied upon to handle an increasing range of tasks. Some tasks, such as vehicle navigation, necessary entail a large number of non-standard or specialized instructions such as street names, addresses, or names of points of interest, merely as examples. The large number of potential instructions requires robust speech recognition systems, as potential commands are varied and unpredictable. Accordingly, voice recognition success rates are typically lower. The relatively lower success rates typical of navigation systems may result in user frustration, and lower utilization of the voice recognition system. 
     SUMMARY 
     In at least one example, a method of recognizing speech in a vehicle includes receiving speech at a microphone installed to a vehicle, and determining whether the speech includes a navigation instruction. If the speech includes a navigation instruction, the speech may be sent to a remote facility. After sending the speech to the remote facility, a local speech recognition result, i.e., determined in the vehicle, is provided in the vehicle to the user. In at least some implementations described herein, the speech sent to the remote facility may be used to provide corrective action, for example, where the local speech recognition result is inadequate or the user experiences difficulty with the system. 
     In at least one implementation, a method of recognizing speech in a vehicle includes determining a success rate of speech recognition in a voice recognition task is below a predetermined threshold. The method may further include receiving speech at a microphone installed to a vehicle, and determining whether the speech is directed to the voice recognition task. In response to the determination that the speech is directed to the voice recognition task and that the success rate associated with the voice recognition task is below the predetermined threshold, the speech may be sent to a remote facility. A local speech recognition result in the vehicle after the speech is sent in step (c), the local speech recognition result determined in the vehicle. In at least some implementations described herein, the speech sent to the remote facility may be used to provide corrective action, as noted above. 
     In at least one example, a system for recognizing speech in a vehicle includes a microphone installed in the vehicle that is configured to receive a speech command from a user. The vehicle speech recognition system may be configured to determine a local speech recognition result from the speech command, and determine when the speech command includes a navigation instruction. The system may further include a remote server in communication with the vehicle that is configured to receive a sample of the speech command from the speech recognition system when the speech command includes a navigation instruction. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       One or more embodiments of the invention will hereinafter be described in conjunction with the appended drawings, wherein like designations denote like elements, and wherein: 
         FIG. 1  is a block diagram depicting an embodiment of a communications system that is capable of utilizing the method disclosed herein; and 
         FIG. 2  is a block diagram depicting an embodiment of an automatic speech recognition (ASR) system; and 
         FIG. 3  is a process flow diagram illustrating a process flow diagram for an example method of recognizing speech in a vehicle. 
     
    
    
     DETAILED DESCRIPTION OF THE ILLUSTRATED EMBODIMENT(S) 
     The example methods and systems described below may generally archive speech or provide corrective assistance where speech recognition systems are performing below a predetermined threshold. For example, where a vehicle speech recognition system is required to recognize non-standardized instructions such as formal names of contacts, street names, or other proper names, speech commands may be archived at the vehicle or sent to a remote facility. The speech commands that are archived or sent to the remote facility may then be used upon the detection of some user difficulty with the speech recognition system. Personnel at the remote facility may generally provide a backup or corrective assistance upon a detection of a user having difficulty with the speech recognition system. Moreover, speech may be archived or sent to the remote facility upon receipt in the vehicle, thereby allowing remote personnel to provide assistance as soon as a subsequent user difficulty is observed. 
     Communications System— 
     With reference to  FIG. 1 , there is shown an operating environment that comprises a mobile vehicle communications system  10  and that can be used to implement the method disclosed herein. Communications system  10  generally includes a vehicle  12 , one or more wireless carrier systems  14 , a land communications network  16 , a computer  18 , and a call center  20 . It should be understood that the disclosed method can be used with any number of different systems and is not specifically limited to the operating environment shown here. Also, the architecture, construction, setup, and operation of the system  10  and its individual components are generally known in the art. Thus, the following paragraphs simply provide a brief overview of one such communications system  10 ; however, other systems not shown here could employ the disclosed method as well. 
     Vehicle  12  is depicted in the illustrated embodiment as a passenger car, but it should be appreciated that any other vehicle including motorcycles, trucks, sports utility vehicles (SUVs), recreational vehicles (RVs), marine vessels, aircraft, etc., can also be used. Some of the vehicle electronics  28  is shown generally in  FIG. 1  and includes a telematics unit  30 , a microphone  32 , one or more pushbuttons or other control inputs  34 , an audio system  36 , a visual display  38 , and a GPS module  40  as well as a number of other vehicle system modules (VSMs)  42 . Some of these devices can be connected directly to the telematics unit such as, for example, the microphone  32  and pushbutton(s)  34 , whereas others are indirectly connected using one or more network connections, such as a communications bus  44  or an entertainment bus  46 . Examples of suitable network connections include a controller area network (CAN), a media oriented system transfer (MOST), a local interconnection network (LIN), a local area network (LAN), and other appropriate connections such as Ethernet or others that conform with known ISO, SAE and IEEE standards and specifications, to name but a few. 
     Telematics unit  30  is itself a vehicle system module (VSM) and can be implemented as an OEM-installed (embedded) or aftermarket device that is installed in the vehicle and that enables wireless voice and/or data communication over wireless carrier system  14  and via wireless networking. This enables the vehicle to communicate with call center  20 , other telematics-enabled vehicles, or some other entity or device. The telematics unit preferably uses radio transmissions to establish a communications channel (a voice channel and/or a data channel) with wireless carrier system  14  so that voice and/or data transmissions can be sent and received over the channel. By providing both voice and data communication, telematics unit  30  enables the vehicle to offer a number of different services including those related to navigation, telephony, emergency assistance, diagnostics, infotainment, etc. Data can be sent either via a data connection, such as via packet data transmission over a data channel, or via a voice channel using techniques known in the art. For combined services that involve both voice communication (e.g., with a live advisor or voice response unit at the call center  20 ) and data communication (e.g., to provide GPS location data or vehicle diagnostic data to the call center  20 ), the system can utilize a single call over a voice channel and switch as needed between voice and data transmission over the voice channel, and this can be done using techniques known to those skilled in the art. 
     According to one embodiment, telematics unit  30  utilizes cellular communication according to either GSM, CDMA, or LTE standards and thus includes a standard cellular chipset  50  for voice communications like hands-free calling, a wireless modem for data transmission, an electronic processing device  52 , one or more digital memory devices  54 , and a dual antenna  56 . It should be appreciated that the modem can either be implemented through software that is stored in the telematics unit and is executed by processor  52 , or it can be a separate hardware component located internal or external to telematics unit  30 . The modem can operate using any number of different standards or protocols such as LTE, EVDO, CDMA, GPRS, and EDGE. Wireless networking between the vehicle and other networked devices can also be carried out using telematics unit  30 . For this purpose, telematics unit  30  can be configured to communicate wirelessly according to one or more wireless protocols, including short range wireless communication (SRWC) such as any of the IEEE 802.11 protocols, WiMAX, ZigBee™, Wi-Fi direct, Bluetooth™, or near field communication (NFC). When used for packet-switched data communication such as TCP/IP, the telematics unit can be configured with a static IP address or can be set up to automatically receive an assigned IP address from another device on the network such as a router or from a network address server. 
     Processor  52  can be any type of device capable of processing electronic instructions including microprocessors, microcontrollers, host processors, controllers, vehicle communication processors, and application specific integrated circuits (ASICs). It can be a dedicated processor used only for telematics unit  30  or can be shared with other vehicle systems. Processor  52  executes various types of digitally-stored instructions, such as software or firmware programs stored in memory  54 , which enable the telematics unit to provide a wide variety of services. For instance, processor  52  can execute programs or process data to carry out at least a part of the method discussed herein. 
     Telematics unit  30  can be used to provide a diverse range of vehicle services that involve wireless communication to and/or from the vehicle. Such services include: turn-by-turn directions and other navigation-related services that are provided in conjunction with the GPS-based vehicle navigation module  40 ; airbag deployment notification and other emergency or roadside assistance-related services that are provided in connection with one or more collision sensor interface modules such as a body control module (not shown); diagnostic reporting using one or more diagnostic modules; and infotainment-related services where music, webpages, movies, television programs, videogames and/or other information is downloaded by an infotainment module (not shown) and is stored for current or later playback. The above-listed services are by no means an exhaustive list of all of the capabilities of telematics unit  30 , but are simply an enumeration of some of the services that the telematics unit is capable of offering. Furthermore, it should be understood that at least some of the aforementioned modules could be implemented in the form of software instructions saved internal or external to telematics unit  30 , they could be hardware components located internal or external to telematics unit  30 , or they could be integrated and/or shared with each other or with other systems located throughout the vehicle, to cite but a few possibilities. In the event that the modules are implemented as VSMs  42  located external to telematics unit  30 , they could utilize vehicle bus  44  to exchange data and commands with the telematics unit. 
     GPS module  40  receives radio signals from a constellation  60  of GPS satellites. From these signals, the module  40  can determine vehicle position that is used for providing navigation and other position-related services to the vehicle driver. Navigation information can be presented on the display  38  (or other display within the vehicle) or can be presented verbally such as is done when supplying turn-by-turn navigation. The navigation services can be provided using a dedicated in-vehicle navigation module (which can be part of GPS module  40 ), or some or all navigation services can be done via telematics unit  30 , wherein the position information is sent to a remote location for purposes of providing the vehicle with navigation maps, map annotations (points of interest, restaurants, etc.), route calculations, and the like. The position information can be supplied to call center  20  or other remote computer system, such as computer  18 , for other purposes, such as fleet management. Also, new or updated map data can be downloaded to the GPS module  40  from the call center  20  via the telematics unit  30 . 
     Apart from the audio system  36  and GPS module  40 , the vehicle  12  can include other vehicle system modules (VSMs)  42  in the form of electronic hardware components that are located throughout the vehicle and typically receive input from one or more sensors and use the sensed input to perform diagnostic, monitoring, control, reporting and/or other functions. Each of the VSMs  42  is preferably connected by communications bus  44  to the other VSMs, as well as to the telematics unit  30 , and can be programmed to run vehicle system and subsystem diagnostic tests. As examples, one VSM  42  can be an engine control module (ECM) that controls various aspects of engine operation such as fuel ignition and ignition timing, another VSM  42  can be a powertrain control module that regulates operation of one or more components of the vehicle powertrain, and another VSM  42  can be a body control module that governs various electrical components located throughout the vehicle, like the vehicle&#39;s power door locks and headlights. According to one embodiment, the engine control module is equipped with on-board diagnostic (OBD) features that provide myriad real-time data, such as that received from various sensors including vehicle emissions sensors, and provide a standardized series of diagnostic trouble codes (DTCs) that allow a technician to rapidly identify and remedy malfunctions within the vehicle. As is appreciated by those skilled in the art, the above-mentioned VSMs are only examples of some of the modules that may be used in vehicle  12 , as numerous others are also possible. 
     Vehicle electronics  28  also includes a number of vehicle user interfaces that provide vehicle occupants with a means of providing and/or receiving information, including microphone  32 , pushbutton(s)  34 , audio system  36 , and visual display  38 . As used herein, the term ‘vehicle user interface’ broadly includes any suitable form of electronic device, including both hardware and software components, which is located on the vehicle and enables a vehicle user to communicate with or through a component of the vehicle. Microphone  32  provides audio input to the telematics unit to enable the driver or other occupant to provide voice commands and carry out hands-free calling via the wireless carrier system  14 . For this purpose, it can be connected to an on-board automated voice processing unit utilizing human-machine interface (HMI) technology known in the art. The pushbutton(s)  34  allow manual user input into the telematics unit  30  to initiate wireless telephone calls and provide other data, response, or control input. Separate pushbuttons can be used for initiating emergency calls versus regular service assistance calls to the call center  20 . Audio system  36  provides audio output to a vehicle occupant and can be a dedicated, stand-alone system or part of the primary vehicle audio system. According to the particular embodiment shown here, audio system  36  is operatively coupled to both vehicle bus  44  and entertainment bus  46  and can provide AM, FM and satellite radio, CD, DVD and other multimedia functionality. This functionality can be provided in conjunction with or independent of the infotainment module described above. Visual display  38  is preferably a graphics display, such as a touch screen on the instrument panel or a heads-up display reflected off of the windshield, and can be used to provide a multitude of input and output functions. Various other vehicle user interfaces can also be utilized, as the interfaces of  FIG. 1  are only an example of one particular implementation. 
     Wireless carrier system  14  is preferably a cellular telephone system that includes a plurality of cell towers  70  (only one shown), one or more mobile switching centers (MSCs)  72 , as well as any other networking components required to connect wireless carrier system  14  with land network  16 . Each cell tower  70  includes sending and receiving antennas and a base station, with the base stations from different cell towers being connected to the MSC  72  either directly or via intermediary equipment such as a base station controller. Cellular system  14  can implement any suitable communications technology, including for example, analog technologies such as AMPS, or the newer digital technologies such as CDMA (e.g., CDMA2000) or GSM/GPRS. As will be appreciated by those skilled in the art, various cell tower/base station/MSC arrangements are possible and could be used with wireless system  14 . For instance, the base station and cell tower could be co-located at the same site or they could be remotely located from one another, each base station could be responsible for a single cell tower or a single base station could service various cell towers, and various base stations could be coupled to a single MSC, to name but a few of the possible arrangements. 
     Apart from using wireless carrier system  14 , a different wireless carrier system in the form of satellite communication can be used to provide uni-directional or bi-directional communication with the vehicle. This can be done using one or more communication satellites  62  and an uplink transmitting station  64 . Uni-directional communication can be, for example, satellite radio services, wherein programming content (news, music, etc.) is received by transmitting station  64 , packaged for upload, and then sent to the satellite  62 , which broadcasts the programming to subscribers. Bi-directional communication can be, for example, satellite telephony services using satellite  62  to relay telephone communications between the vehicle  12  and station  64 . If used, this satellite telephony can be utilized either in addition to or in lieu of wireless carrier system  14 . 
     Land network  16  may be a conventional land-based telecommunications network that is connected to one or more landline telephones and connects wireless carrier system  14  to call center  20 . For example, land network  16  may include a public switched telephone network (PSTN) such as that used to provide hardwired telephony, packet-switched data communications, and the Internet infrastructure. One or more segments of land network  16  could be implemented through the use of a standard wired network, a fiber or other optical network, a cable network, power lines, other wireless networks such as wireless local area networks (WLANs), or networks providing broadband wireless access (BWA), or any combination thereof. Furthermore, call center  20  need not be connected via land network  16 , but could include wireless telephony equipment so that it can communicate directly with a wireless network, such as wireless carrier system  14 . 
     Computer  18  can be one of a number of computers accessible via a private or public network such as the Internet. Each such computer  18  can be used for one or more purposes, such as a web server accessible by the vehicle via telematics unit  30  and wireless carrier  14 . Other such accessible computers  18  can be, for example: a service center computer where diagnostic information and other vehicle data can be uploaded from the vehicle via the telematics unit  30 ; a client computer used by the vehicle owner or other subscriber for such purposes as accessing or receiving vehicle data or to setting up or configuring subscriber preferences or controlling vehicle functions; or a third party repository to or from which vehicle data or other information is provided, whether by communicating with the vehicle  12  or call center  20 , or both. A computer  18  can also be used for providing Internet connectivity such as DNS services or as a network address server that uses DHCP or other suitable protocol to assign an IP address to the vehicle  12 . 
     Call center  20  is designed to provide the vehicle electronics  28  with a number of different system back-end functions and, according to the exemplary embodiment shown here, generally includes one or more switches  80 , servers  82 , databases  84 , live advisors  86 , as well as an automated voice response system (VRS)  88 , all of which are known in the art. These various call center components are preferably coupled to one another via a wired or wireless local area network  90 . Switch  80 , which can be a private branch exchange (PBX) switch, routes incoming signals so that voice transmissions are usually sent to either the live adviser  86  by regular phone or to the automated voice response system  88  using VoIP. The live advisor phone can also use VoIP as indicated by the broken line in  FIG. 1 . VoIP and other data communication through the switch  80  is implemented via a modem (not shown) connected between the switch  80  and network  90 . Data transmissions are passed via the modem to server  82  and/or database  84 . Database  84  can store account information such as subscriber authentication information, vehicle identifiers, profile records, behavioral patterns, and other pertinent subscriber information. Data transmissions may also be conducted by wireless systems, such as 802.11x, GPRS, and the like. Although the illustrated embodiment has been described as it would be used in conjunction with a manned call center  20  using live advisor  86 , it will be appreciated that the call center can instead utilize VRS  88  as an automated advisor or, a combination of VRS  88  and the live advisor  86  can be used. 
     Turning now to  FIG. 2 , there is shown an illustrative architecture for an ASR system  210  that can be used to enable the presently disclosed method. In general, a vehicle occupant vocally interacts with an automatic speech recognition system (ASR) for one or more of the following fundamental purposes: training the system to understand a vehicle occupant&#39;s particular voice; storing discrete speech such as a spoken nametag or a spoken control word like a numeral or keyword; or recognizing the vehicle occupant&#39;s speech for any suitable purpose such as voice dialing, menu navigation, transcription, service requests, vehicle device or device function control, or the like. Generally, ASR extracts acoustic data from human speech, compares and contrasts the acoustic data to stored subword data, selects an appropriate subword which can be concatenated with other selected subwords, and outputs the concatenated subwords or words for post-processing such as dictation or transcription, address book dialing, storing to memory, training ASR models or adaptation parameters, or the like. 
     ASR systems are generally known to those skilled in the art, and  FIG. 2  illustrates just one specific illustrative ASR system  210 . The system  210  includes a device to receive speech such as the telematics microphone  32 , and an acoustic interface  33  such as a sound card of the telematics unit  30  having an analog to digital converter to digitize the speech into acoustic data. The system  210  also includes a memory such as the telematics memory  54  for storing the acoustic data and storing speech recognition software and databases, and a processor such as the telematics processor  52  to process the acoustic data. The processor functions with the memory and in conjunction with the following modules: one or more front-end processors or pre-processor software modules  212  for parsing streams of the acoustic data of the speech into parametric representations such as acoustic features; one or more decoder software modules  214  for decoding the acoustic features to yield digital subword or word output data corresponding to the input speech utterances; and one or more post-processor software modules  216  for using the output data from the decoder module(s)  214  for any suitable purpose. 
     The system  210  can also receive speech from any other suitable audio source(s)  31 , which can be directly communicated with the pre-processor software module(s)  212  as shown in solid line or indirectly communicated therewith via the acoustic interface  33 . The audio source(s)  31  can include, for example, a telephonic source of audio such as a voice mail system, or other telephonic services of any kind. 
     One or more modules or models can be used as input to the decoder module(s)  214 . First, grammar and/or lexicon model(s)  218  can provide rules governing which words can logically follow other words to form valid sentences. In a broad sense, a grammar can define a universe of vocabulary the system  210  expects at any given time in any given ASR mode. For example, if the system  210  is in a training mode for training commands, then the grammar model(s)  218  can include all commands known to and used by the system  210 . In another example, if the system  210  is in a main menu mode, then the active grammar model(s)  218  can include all main menu commands expected by the system  210  such as call, dial, exit, delete, directory, or the like. Second, acoustic model(s)  220  assist with selection of most likely subwords or words corresponding to input from the pre-processor module(s)  212 . Third, word model(s)  222  and sentence/language model(s)  224  provide rules, syntax, and/or semantics in placing the selected subwords or words into word or sentence context. Also, the sentence/language model(s)  224  can define a universe of sentences the system  210  expects at any given time in any given ASR mode, and/or can provide rules, etc., governing which sentences can logically follow other sentences to form valid extended speech. 
     According to an alternative illustrative embodiment, some or all of the ASR system  210  can be resident on, and processed using, computing equipment in a location remote from the vehicle  12  such as the call center  20 . For example, grammar models, acoustic models, and the like can be stored in memory of one of the servers  82  and/or databases  84  in the call center  20  and communicated to the vehicle telematics unit  30  for in-vehicle speech processing. Similarly, speech recognition software can be processed using processors of one of the servers  82  in the call center  20 . In other words, the ASR system  210  can be resident in the telematics unit  30 , distributed across the call center  20  and the vehicle  12  in any desired manner, and/or resident at the call center  20 . 
     First, acoustic data is extracted from human speech wherein a vehicle occupant speaks into the microphone  32 , which converts the utterances into electrical signals and communicates such signals to the acoustic interface  33 . A sound-responsive element in the microphone  32  captures the occupant&#39;s speech utterances as variations in air pressure and converts the utterances into corresponding variations of analog electrical signals such as direct current or voltage. The acoustic interface  33  receives the analog electrical signals, which are first sampled such that values of the analog signal are captured at discrete instants of time, and are then quantized such that the amplitudes of the analog signals are converted at each sampling instant into a continuous stream of digital speech data. In other words, the acoustic interface  33  converts the analog electrical signals into digital electronic signals. The digital data are binary bits which are buffered in the telematics memory  54  and then processed by the telematics processor  52  or can be processed as they are initially received by the processor  52  in real-time. 
     Second, the pre-processor module(s)  212  transforms the continuous stream of digital speech data into discrete sequences of acoustic parameters. More specifically, the processor  52  executes the pre-processor module(s)  212  to segment the digital speech data into overlapping phonetic or acoustic frames of, for example, 10-30 ms duration. The frames correspond to acoustic subwords such as syllables, demi-syllables, phones, diphones, phonemes, or the like. The pre-processor module(s)  212  also performs phonetic analysis to extract acoustic parameters from the occupant&#39;s speech such as time-varying feature vectors, from within each frame. Utterances within the occupant&#39;s speech can be represented as sequences of these feature vectors. For example, and as known to those skilled in the art, feature vectors can be extracted and can include, for example, vocal pitch, energy profiles, spectral attributes, and/or cepstral coefficients that can be obtained by performing Fourier transforms of the frames and decorrelating acoustic spectra using cosine transforms. Acoustic frames and corresponding parameters covering a particular duration of speech are concatenated into unknown test pattern of speech to be decoded. 
     Third, the processor executes the decoder module(s)  214  to process the incoming feature vectors of each test pattern. The decoder module(s)  214  is also known as a recognition engine or classifier, and uses stored known reference patterns of speech. Like the test patterns, the reference patterns are defined as a concatenation of related acoustic frames and corresponding parameters. The decoder module(s)  214  compares and contrasts the acoustic feature vectors of a subword test pattern to be recognized with stored subword reference patterns, assesses the magnitude of the differences or similarities therebetween, and ultimately uses decision logic to choose a best matching subword as the recognized subword. In general, the best matching subword is that which corresponds to the stored known reference pattern that has a minimum dissimilarity to, or highest probability of being, the test pattern as determined by any of various techniques known to those skilled in the art to analyze and recognize subwords. Such techniques can include dynamic time-warping classifiers, artificial intelligence techniques, neural networks, free phoneme recognizers, and/or probabilistic pattern matchers such as Hidden Markov Model (HMM) engines. 
     HMM engines are known to those skilled in the art for producing multiple speech recognition model hypotheses of acoustic input. The hypotheses are considered in ultimately identifying and selecting that recognition output which represents the most probable correct decoding of the acoustic input via feature analysis of the speech. More specifically, an HMM engine generates statistical models in the form of an “N-best” list of subword model hypotheses ranked according to HMM-calculated confidence values or probabilities of an observed sequence of acoustic data given one or another subword such as by the application of Bayes&#39; Theorem. 
     A Bayesian HMM process identifies a best hypothesis corresponding to the most probable utterance or subword sequence for a given observation sequence of acoustic feature vectors, and its confidence values can depend on a variety of factors including acoustic signal-to-noise ratios associated with incoming acoustic data. The HMM can also include a statistical distribution called a mixture of diagonal Gaussians, which yields a likelihood score for each observed feature vector of each subword, which scores can be used to reorder the N-best list of hypotheses. The HMM engine can also identify and select a subword whose model likelihood score is highest. 
     In a similar manner, individual HMMs for a sequence of subwords can be concatenated to establish single or multiple word HMM. Thereafter, an N-best list of single or multiple word reference patterns and associated parameter values may be generated and further evaluated. 
     In one example, the speech recognition decoder  214  processes the feature vectors using the appropriate acoustic models, grammars, and algorithms to generate an N-best list of reference patterns. As used herein, the term reference patterns is interchangeable with models, waveforms, templates, rich signal models, exemplars, hypotheses, or other types of references. A reference pattern can include a series of feature vectors representative of one or more words or subwords and can be based on particular speakers, speaking styles, and audible environmental conditions. Those skilled in the art will recognize that reference patterns can be generated by suitable reference pattern training of the ASR system and stored in memory. Those skilled in the art will also recognize that stored reference patterns can be manipulated, wherein parameter values of the reference patterns are adapted based on differences in speech input signals between reference pattern training and actual use of the ASR system. For example, a set of reference patterns trained for one vehicle occupant or certain acoustic conditions can be adapted and saved as another set of reference patterns for a different vehicle occupant or different acoustic conditions, based on a limited amount of training data from the different vehicle occupant or the different acoustic conditions. In other words, the reference patterns are not necessarily fixed and can be adjusted during speech recognition. 
     Using the in-vocabulary grammar and any suitable decoder algorithm(s) and acoustic model(s), the processor accesses from memory several reference patterns interpretive of the test pattern. For example, the processor can generate, and store to memory, a list of N-best vocabulary results or reference patterns, along with corresponding parameter values. Illustrative parameter values can include confidence scores of each reference pattern in the N-best list of vocabulary and associated segment durations, likelihood scores, signal-to-noise ratio (SNR) values, and/or the like. The N-best list of vocabulary can be ordered by descending magnitude of the parameter value(s). For example, the vocabulary reference pattern with the highest confidence score is the first best reference pattern, and so on. Once a string of recognized subwords are established, they can be used to construct words with input from the word models  222  and to construct sentences with the input from the language models  224 . 
     Finally, the post-processor software module(s)  216  receives the output data from the decoder module(s)  214  for any suitable purpose. In one example, the post-processor software module(s)  216  can identify or select one of the reference patterns from the N-best list of single or multiple word reference patterns as recognized speech. In another example, the post-processor module(s)  216  can be used to convert acoustic data into text or digits for use with other aspects of the ASR system or other vehicle systems. In a further example, the post-processor module(s)  216  can be used to provide training feedback to the decoder  214  or pre-processor  212 . More specifically, the post-processor  216  can be used to train acoustic models for the decoder module(s)  214 , or to train adaptation parameters for the pre-processor module(s)  212 . 
     The method or parts thereof can be implemented in a computer program product embodied in a computer readable medium and including instructions usable by one or more processors of one or more computers of one or more systems to cause the system(s) to implement one or more of the method steps. The computer program product may include one or more software programs comprised of program instructions in source code, object code, executable code or other formats; one or more firmware programs; or hardware description language (HDL) files; and any program related data. The data may include data structures, look-up tables, or data in any other suitable format. The program instructions may include program modules, routines, programs, objects, components, and/or the like. The computer program can be executed on one computer or on multiple computers in communication with one another. 
     The program(s) can be embodied on computer readable media, which can be non-transitory and can include one or more storage devices, articles of manufacture, or the like. Exemplary computer readable media include computer system memory, e.g. RAM (random access memory), ROM (read only memory); semiconductor memory, e.g. EPROM (erasable, programmable ROM), EEPROM (electrically erasable, programmable ROM), flash memory; magnetic or optical disks or tapes; and/or the like. The computer readable medium may also include computer to computer connections, for example, when data is transferred or provided over a network or another communications connection (either wired, wireless, or a combination thereof). Any combination(s) of the above examples is also included within the scope of the computer-readable media. It is therefore to be understood that the method can be at least partially performed by any electronic articles and/or devices capable of carrying out instructions corresponding to one or more steps of the disclosed method. 
     Method— 
     Turning now to  FIG. 3 , a process flow diagram for an example method of completing a speech recognition task is shown. Process  300  may begin at block  305 , where a speech command is received in the vehicle  12 . For example, speech may be received at microphone  52  installed in or to the vehicle  12 . 
     Proceeding to block  310 , process  300  may determine whether corrective assistance may be needed in a speech recognition system or subsystem. In some examples, performance below a given threshold over time may be used to determine that corrective assistance would be beneficial. More specifically, an accuracy rate of an ASR system, e.g., of the vehicle  12 , may be below a prescribed threshold or there may be some other indication of consistent user difficulty. 
     In some examples, block  310  may simply query whether the domain of the speech command is one that typically suffers from reduced performance or accuracy, such as navigation or other speech domains that employ proper names, street names, city names, etc. In such examples, the vehicle  12  may use any means that is convenient to determine whether the domain of the speech relates to navigation. Merely as examples, the speech may be analyzed to determine the presence of an address, a point of interest, or other characteristics typical of a navigation speech command. 
     If the result of the query at block  310  is that corrective assistance is not needed, or the domain is not navigation, process  300  may proceed to block  315 , where a standard speech recognition flow or logic is used, i.e., without archiving the speech command as described further below in blocks  320 - 345 . From block  315 , process  300  may then terminate. 
     Alternatively, if the result of the query at block  310  is that corrective assistance is needed or would be useful, or the domain of the speech command is navigation, then process  300  may proceed to block  320 . At block  320 , the speech command may be archived, e.g., at the vehicle  12 . Merely as examples, the speech command may be archived as an .ogg or .wav file and may be stored in a memory installed in the vehicle  12 , e.g., as part of the telematics unit  30  or in ASR system  210 . Archived speech may be used to improve recognition of speech, at least in subsequent speech recognition sessions. For example, in a subsequent speech recognition session at the vehicle  12 , archived speech may be used to quickly compare to the subsequent speech. In this manner, vehicle  12  may provide improved speech recognition relatively quickly, and without needing to rely upon resources remote from the vehicle  12 , e.g., as provided by remote facility  80 . In some example approaches, the use of in-vehicle resources such as the archived speech may be used solely in speech recognition domains where accuracy or customer satisfaction is problematic, such as navigation. Process  300  may then proceed to block  325 . 
     At block  325 , the archived speech command may be sent to the remote facility  80 . The speech command may be sent to the remote facility  80  in any manner that is convenient. For example, it may be desirable to compress or otherwise minimize a size of the archived speech command before sending to the remote facility  80 , thereby reducing bandwidth usage of the vehicle  12 . 
     Proceeding to block  330 , the vehicle  12  may perform local speech recognition on the speech command, i.e., using the speech recognition system of vehicle  12  described above in  FIG. 2 , and present results to the user of the vehicle  12 . Process  300  may then proceed to block  335 . 
     At block  335 , process  300  may query whether the speech recognition results presented at block  330  adequately represented the intended speech command. For example, the vehicle  12  may determine whether the user of the vehicle  12  immediately accepted one of the presented results, indicating a successful recognition result, or instead had some difficulty with the results as presented. If the user rejected the results, or repeated the request, or repeated the request a predetermined number of times, this may provide an indication that the results of the speech recognition were not correct. Process  300  may proceed to block  345  if it is determined the recognition results were not correct or the user had some difficulty with the results. 
     Generally, block  335  may use analysis of how a user of the vehicle  12  responds to the speech recognition results presented at block  330  to determine whether the speech recognition results presented to the user were adequate. Where the user response indicates some difficulty with the results, e.g., by rejecting the results one or more times, or terminating the speech command session before it is successfully completed, process  300  may determine that the speech recognition results did not adequately capture the intended speech command. 
     Accordingly, where it is determined that the user has had some difficulty with the presented results, at block  345  a route request may be offered or transmitted to the vehicle  12  by the remote facility  80 . For example, personnel of the remote facility  80  may be notified of the difficulty that the user had in the vehicle  12  and may analyze the compressed speech command that was sent to the remote facility  80 . The personnel may review the speech command, e.g., by way of the archived command already sent to the remote facility at blocks  320 / 325 , and determine the intended request. Moreover, in some examples the remote facility  80  may review a record of archived speech received from the vehicle  12 . Accordingly, in the case where certain phrases or commands have resulted in a number of failures of the ASR system in the vehicle  12 , the remote facility  80  may review a history of previous commands to determine corrective action or particular commands that the ASR system of the vehicle  12  does not accurately identify. The remote facility  80  may transmit a result intended to answer the intended speech command directly to the vehicle  12 . For example, the remote facility  80  may be used to provide navigation services, e.g., by providing turn-by-turn directions to the vehicle  12 , since the vehicle  12  did not properly determine what the user request was. In this manner, where the user has some difficulty with a speech command, the user may generally automatically receive a route request or information that is likely to answer their initial query. Process  300  may then terminate. 
     If the recognition results presented to the user at block  330  are determined at block  335  to have been accepted by the user, or otherwise presented without substantial difficulty of the user, process  300  may proceed to block  340 . At block  340 , the navigation task is completed through an ordinary speech recognition process, i.e., the remote analysis of the archived navigation command need not be analyzed by personnel at the remote facility  80 . Thus, the speech recognition request, e.g., for navigation assistance, can be satisfied completely using on-board resources of the vehicle  12 , e.g., GPS and map data. 
     It is to be understood that the foregoing is a description of one or more embodiments of the invention. The invention is not limited to the particular embodiment(s) disclosed herein, but rather is defined solely by the claims below. Furthermore, the statements contained in the foregoing description relate to particular embodiments and are not to be construed as limitations on the scope of the invention or on the definition of terms used in the claims, except where a term or phrase is expressly defined above. Various other embodiments and various changes and modifications to the disclosed embodiment(s) will become apparent to those skilled in the art. All such other embodiments, changes, and modifications are intended to come within the scope of the appended claims. 
     As used in this specification and claims, the terms “e.g.,” “for example,” “for instance,” “such as,” and “like,” and the verbs “comprising,” “having,” “including,” and their other verb forms, when used in conjunction with a listing of one or more components or other items, are each to be construed as open-ended, meaning that the listing is not to be considered as excluding other, additional components or items. Other terms are to be construed using their broadest reasonable meaning unless they are used in a context that requires a different interpretation.