Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating, distributing, and using speech recognition models are disclosed. The methods, systems, and apparatus include actions of receiving a speech data representation of an utterance and obtaining feature data extracted from the speech data representation of the utterance. Additional actions include obtaining a transcription of the utterance using the feature data and identifying contact information associated with the transcription. Further actions include determining that a network connection exists and initiating communication using the contact information based on determining that a network connection exists.

Description:
CROSS REFERENCE TO RELATED APPLICATIONS 
     This application is a divisional application of U.S. patent application Ser. No. 13/614,444, filed Sep. 13, 2012 and a continuation of U.S. patent application Ser. No. 13/661,347, filed Oct. 26, 2012. Both the above divisional application and the continuation application are continuation applications of U.S. patent application Ser. No. 13/614,444, filed Sep. 13, 2012, which is a continuation application of U.S. patent application Ser. No. 13/423,595, filed Mar. 19, 2012, which is a continuation application of U.S. patent application Ser. No. 13/401,932, filed on Feb. 22, 2012, which is a continuation application of U.S. patent application Ser. No. 12/981,396, filed on Dec. 29, 2010, which is a continuation application of U.S. patent application Ser. No. 11/869,275, filed on Oct. 9, 2007, which is a continuation application of U.S. patent application Ser. No. 11/137,058, filed May 25, 2005, which is a continuation of U.S. patent application Ser. No. 09/726,971, filed on Nov. 30, 2000. The disclosures of the foregoing applications are incorporated herein by reference in their entirety. 
    
    
     FIELD OF THE INVENTION 
     The present invention is directed to speech recognition techniques and, more particularly, to methods and apparatus for generating speech recognition models, distributing speech recognition models and performing speech recognition operations, e.g., voice dialing and word processing operations, using speech recognition models. 
     BACKGROUND OF THE INVENTION 
     Speech recognition, which includes both speaker independent speech recognition and speaker dependent speech recognition, is used for a wide variety of applications. 
     Speech recognition normally involves the use of speech recognition models or templates that have been trained using speech samples provided by one or more individuals. Commonly used speech recognition models include Hidden Markov Models (HMMS). An example of a common template is a dynamic time warping (DTW) template. In the context of the present application “speech recognition model” is intended to encompass both speech recognition models as well as templates which are used for speech recognition purposes. 
     As part of a speech recognition operation, speech input is normally digitized and then processed. The processing normally involves extracting feature information, e.g., energy and/timing information, from the digitized signal. The extracted feature information normally takes the form of one or more feature vectors. The extracted feature vectors are then compared to one or more speech recognition models in an attempt to recognize words, phrases or sounds. 
     In speech recognition systems, various actions, e.g., dialing a telephone number, entering information into a form, etc., are often performed in response to the results of the speech recognition operation. 
     Before speech recognition operations can be performed, one or more speech recognition models need to be trained. Speech recognition models can be either speaker dependent or speaker independent. Speaker dependent (SD) speech recognition models are normally trained using speech from a single individual and are designed so that they should accurately recognize the speech of the individual who provided the training speech but not necessarily other individuals. Speaker independent (SI) speech recognition models are normally generated from speech provided from numerous individuals or from text. The generated speaker independent speech recognition models often represent composite models which take into consideration variations between different speakers, e.g., due to differing pronunciations of the same word. Speaker independent speech recognition models are designed to accurately identify speech from a wide range of individuals including individuals who did not provide speech samples for training purposes. 
     In general, model training involves one or more individuals speaking a word or phrase, converting the speech into digital signal data, and then processing the digital signal data to generate a speech recognition model. Model training frequently involves an iterative process of computing a speech recognition model, scoring the model, and then using the results of the scoring operation to further improve and retrain the speech recognition model. 
     Speech recognition model training processes can be very computationally complex. This is true particularly in the case of SI models where audio data from numerous speakers is normally processed to generate each model. For this reason, speech recognition models are often generated using a relatively powerful computer systems. 
     Individual speech recognition models can take up a considerable amount of storage space. For this reason, it is often impractical to store speech recognition models corresponding to large numbers of words or phrases, e.g., the names of all the people in a mid-sized company, or large dictionary in a portable device or speech recognizer where storage space, e.g., memory, is limited. 
     In addition to limits in storage capacity, portable devices are often equipped with limited processing power. Speech recognition, like the model training process, can be a relatively computationally complex process and can there for be time consuming given limited processing resources. Since most users of a speech processing system expect a prompt response from the system, to satisfy user demands speech processing often needs to be performed in real or near real time. As the number of potential words which may be recognized increases, so does the amount of processing required to perform a speech recognition operation. Thus, devices with limited processing power which may be able to perform a speech recognition operation involving recognizing, e.g., 20 possible names in near real time, may not be fast enough to perform a recognition operation in near real time where the number of names is increased to 100 possible names. 
     In the case of voice dialing and other applications where the recognition results need to be generated in near real time, e.g., with relatively little delay, the limited processing power of portable devices often limits the size of the vocabulary which can be considered as possible recognition outcomes. 
     In addition to the above implementation problems, implementers of speech recognition systems are often confronted with logistical problems associated with collecting speech samples to be used for model training purposes. This is particularly a problem in the case of speaker independent speech recognition models where the robustness of the models are often a function of the number of speech samples used for training and the differences between the individuals providing the samples. In applications where speech recognition models are to be used over a wide geographical region, it is particularly desirable that speech samples be collected from the various geographic regions where the models will ultimately be used. In this manner, regional speech differences can be taken into account during model training. 
     Another problem confronting implementers of speech recognition systems is that older speech recognition models may include different feature information than current speech recognition models. When updating a system to use newer speech recognition models, previously used models in addition to speech recognition software may have to be revised or replaced. This frequently requires speech samples to retrain and/or update the older models. Thus the problems of collecting training data and training speech recognition models discussed above are often encountered when updating existing speech recognition systems. 
     In systems using multiple speech recognition devices, speech model incompatibility may require the extraction of different speech features for different speech recognition devices when the devices are used to perform a speech recognition operation on the same speech segment. Accordingly, in some cases it is desirable to be able to supply the speech to be processed to multiple systems so that each system can perform its own feature extraction operation. 
     In view of the above discussion, it is apparent that there is a need for new and improved methods and apparatus relating to a wider range of speech recognition issues. For example, there is a need for improvements with regard to the collecting of speech samples for purposes of training speech recognition models. There is also a need for improved methods of providing users of portable devices with limited processing power, e.g., notebook computers and personal data assistants (PDAs) speech recognition functionality. Improved methods of providing speech recognition functionality in systems where different types of speech recognition models are used by different speech recognizers is also desirable. Enhanced methods and apparatus for updating speech recognition models are also desirable. 
     SUMMARY OF THE INVENTION 
     The present invention is directed to methods and apparatus for generating, distributing, and using speech recognition models. In accordance with the present invention, a shared, e.g., centralized, speech processing facility is used to support speech recognition for a wide variety of devices, e.g., notebook computers, business computer systems personal data assistants, etc. The centralized speech processing facility of the present invention may be located at a physically remote site, e.g., in a different room, building, or even country, than the devices to which it provides speech processing and/or speech recognition services. The shared speech processing facility may be coupled to numerous devices via the Internet and/or one or more other communications channels such as telephone lines, a local area network (LAN), etc. 
     In various embodiments, the Internet is used as the communications channel via which model training data is collected and/or speech recognition input is received by the shared speech processing facility of the present invention. Speech files may be sent to the speech processing facility as electronic mail (E-mail) message attachments. The Internet is also used to return speech recognition models and/or information identifying recognized words or phrases included in the processed speech. The speech recognition models may be returned as E-mail message attachments while the recognized words may be returned as text in the body of an E-mail message or in a text file attachment to an E-mail message. 
     Thus, via the Internet, devices with audio capture capability and Internet access can record and transmit to the centralized speech processing facility of the present invention digitized speech, e.g., as speech files. The speech processing facility then performs a model training operation or speech recognition operation using the received speech. A speech recognition model or data message including the recognized words, phases or other information is then returned depending on whether a model training or recognition operation was performed, to the device which supplied the speech. 
     Thus, the speech processing facility of the present invention can be used to provide speech recognition capabilities and/or to augment a device&#39;s speech processing capability by performing speech recognition model training operations and/or additional speech recognition operations which can be used to supplement local speech recognition attempts. 
     For example, in various embodiments of the present invention, the generation of speech recognition models to be used locally is performed by the remote speech processing facility. In one such embodiment, when the local computer device needs a speech recognition model to be trained, the local computer system collects the necessary training data, e.g., speech samples from the system user and text corresponding to the retrieved speech samples and then transmits the training data, e.g., via the Internet, to the speech processing facility of the present invention. The speech processing facility then generates one or more speech recognition models and returns them to the local computer system for use in local speech recognition operations. 
     In various embodiments, the shared speech processing facility updates a training database with the speech samples received from local computer systems. In this way, a more robust set of training data is created at the remote speech processing facility as part of the model training and/or updating process without imposing addition burdens on individual devices beyond those needed to support services being provided to a use of an individual device, e.g., notebook computer or PDA. As the training database is augmented, speaker independent speech recognition models may be retrained periodically using the updated training data and then transmitted to those computer systems which use speech recognition models corresponding to those models which are retrained. In this manner, multiple local systems can benefit from one or more different users initiating the retraining of speech recognition models to enhance recognition results. 
     As discussed above, in various embodiments, the remote speech processing facility of the present invention is used to perform speech recognition operations and then return the recognition results or take other actions based on the recognition results. For example, in one embodiment business computer systems capture speech from, e.g., customers, and then transmit the speech or extracted speech information to the shared speech processing facility via the Internet. The remote speech processing facility performs speech recognition operations on the received speech and/or received extracted speech information. The results of the recognition operation, e.g., recognized words in the form of, e.g., text, are then returned to the business computer system which supplied the processed speech or speech information. The business system can then use the information returned by the speech processing facility, e.g., recognized text, to fill in forms or perform other services such as automatically respond to verbal customer inquires. Thus, the remote speech processing method of the present invention can be used to supply speech processing capabilities to customers, e.g., businesses, who can&#39;t, or do not want to, support local speech processing operations. 
     In addition to providing speech recognition capabilities to systems which can&#39;t perform speech recognition locally, the speech processing facility of the present invention is used in various embodiments to augment the speech recognition capabilities of various devices such as notebook computers and personal data assistants. In such embodiments the remote speech processing facility may be used to perform speech recognition when the local device is unable to obtain a satisfactory recognition result, e.g., because of a limited vocabulary or limited processing capability. 
     In one particular exemplary embodiment, a notebook computer attempts to perform a voice dialing operation on received speech using locally stored speech recognition models prior to contracting the speech processing facility of the present invention. If the local speech recognition operation fails to result in the recognition of a name, the received speech or extracted feature information is transmitted to the remote speech processing facility. If the local notebook computer can&#39;t perform a dialing operation the notebook computer also transmits to the remote speech processing facility a telephone number where the user of the notebook computer can be contacted by telephone. The remote speech processing facility performs a speech recognition operation using the received speech and/or extracted feature information. If the speech recognition operation results in the recognition of a name with which a telephone number is associated the telephone number is retrieved from the remote speech processing facility&#39;s memory. The telephone number is returned to the device requesting that the voice dialing speech recognition operation be performed unless a contact telephone number was provided with the speech and/or extracted feature information. In such a case, the speech processing facility uses telephone circuitry to initiate one telephone call to the telephone number retrieved from memory and another telephone call to the received contact telephone number. When the two calls are answered, they are bridged thereby completing the voice dialing operation. 
     In addition to generating new speech recognition models to be used in speech processing operations and providing speech recognition services, the centralized speech processing facility of the present invention can be used for modernizing existing speech recognition system but upgrading speech recognition models and the speech recognition engine used therewith. In one particular embodiment, speech recognition models or templates are received via the Internet from a system to be updated along with speech corresponding to the modeled words. The received models or templates and/or speech are used to generate updated models which include different speech characteristic information or have a different model format than the existing speech recognition models. The updated models are returned to the speech recognition systems along with, in some cases, new speech recognition engine software. 
     In one particular embodiment, speech recognition templates used by voice dialing systems are updated and replaced with HMMs generated by the central processing system of the present invention. 
     At the time the templates are replaced, the speech recognition engine software is also replaced with a new speech recognition engine which uses HMMs for recognition purposes. 
     Various additional features and advantages of the present invention will be apparent from the detailed description which follows. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  illustrates a communication system implemented in accordance with an exemplary embodiment of the present invention. 
         FIG. 2  illustrates the communications system of  FIG. 1  in greater detail. 
         FIG. 3  illustrates a computer system for use in the communications system illustrated in  FIG. 1 . 
         FIG. 4  illustrates memory which may be used as the memory of a computer in the system illustrated in  FIG. 1 . 
         FIG. 5  illustrates a voice dialing customer record implemented in accordance with the present invention. 
         FIG. 6  illustrates a voice dialing IP device which may be used in the system illustrated in  FIG. 1 . 
         FIG. 7  illustrates a model training routine of the present invention. 
         FIG. 8  illustrates an exemplary voice dialing routine of the present invention. 
         FIG. 9  illustrates a local voice dialing subroutine of the present invention. 
         FIG. 10  illustrates a remote voice dialing routine implemented in accordance with the present invention. 
         FIG. 11  illustrates a call establishment routine of the present invention. 
         FIG. 12  illustrates a model generation routine of the present invention. 
         FIG. 13  illustrates a speech processing facility implemented in accordance with one embodiment of the present invention. 
         FIG. 14  illustrates a speech recognition routine that can be executed by the speech processing facility of  FIG. 13 . 
     
    
    
     DETAILED DESCRIPTION 
     As discussed above, the present invention is directed to methods and apparatus for generating speech recognition models, distributing speech recognition models and performing speech recognition operations, e.g., voice dialing and word processing operations, using speech recognition models. 
       FIG. 1  illustrates a communications system  100  implemented in accordance with the present invention. As illustrated, the system  100  includes a business premises  10  and customer premises  12 ,  14 ,  16 . Each one of the premises  10 ,  12 ,  14 ,  16  represents a customer or business site. While only one business premise  10  is shown, it is to be understood that any number of business and customer premises may be included in the system  100 . The various premises  10 ,  12 ,  14 ,  16 ,  18  are coupled together and to a shared speech processing facility  18  of the present invention via the Internet  20  and a telephone network  22 . Connections to the Internet  20  may be via digital subscriber lines (DSL), cable modems, cable lines, high speed data links, e.g., Ti links, dial-up lines, wireless connections or a wide range of other communications channels. The premises  10 ,  12 ,  14 ,  16 ,  18  may be connected to the speech processing facility via a LAN or other communications channel instead of, or in addition to, the Internet. 
     While businesses have frequently contracted for high speed Internet connections, e.g., T1 links and other high speed services, which may be on during all hours of business service, residential customers are now also moving to relatively high speed Internet connections which are “always on”. As part of such services, a link to the Internet is maintained while the computer user has his/her computer on avoiding delays associated with establishing an Internet connection when data needs to be sent or received over the Internet. Examples of such Internet connections include cable modem services and DSL services. Such services frequently support sufficient bandwidth for the transmission of audio signals. As the speed of Internet connections increases, the number of Internet service subscribers capable of transmitting audio signals in real or near real time will continue to increase. 
     The speech processing facility  18  is capable of receiving speech from the various premises  10 ,  12 ,  14 ,  16  and performing speech processing operations thereon. The operations may include speech model training, e.g., generation, operations and/or speech recognition operations. The results of the speech processing operation may be returned to the customer or business premises from which the speech originated. Alternatively, the speech processing facility may use the results of the speech processing operation to initiate an action such as voice dialing. In addition, received speech or data generated from received speech, such as feature vectors, may be forwarded by the speech processing facility  18  to other devices in the system  100  for use by the receiving device. 
     The system  100  is illustrated in greater detail in  FIG. 2 . In particular,  FIG. 2  provides a more detailed illustration of the first customer premises  12 , telephone network  22 , and business premises  10 . 
     The first customer premises  12  includes a computer system  50  and a telephone  56 . The computer system  50  is coupled to the Internet  30 , e.g., by a physical communications line  51  or by a wireless connection via antenna  52 . Optionally, the computer system  50  may also be coupled to the telephone system  22  by telephone line  54 , e.g., when computer telephony capabilities are supported. Telephone  56  which is also located at the first customer premises is coupled to the telephone system  22 . Thus, a person located at the first customer premises  12  may, assuming the computer system  50  supports telephony capability, make and/or receive calls using either the computer  50  or telephone  56 . 
     Business premises  10  includes a computerized business system  58  which is coupled to the Internet  30  and a telephone system  66 . Both the computerized business system  58  and telephone system  66  are coupled to the telephone network  22 . This allows customers to interact with the computer system  58  and a sales representative or operator working at the telephone system  66 . The computerized business system  58  includes a processor, i.e., CPU  59 , memory  62 , input/output device  64  and speech recognition (SR) circuitry  60 . Speech recognition circuitry  60  can perform speech recognition operations on speech obtained from a customer using speech recognition routines and models stored in memory  62 . Sales and purchasing information may be stored in memory  62  in addition to the speech recognition routines and speech recognition models. 
     Telephone network  22  includes first and second telephone switches which function as signal switching points (SSPs)  74 ,  76 . The telephone switches  74 ,  76  are coupled to each other via link  80  which may be, e.g., a T1 or other high bandwidth link. The telephone network also includes a voice dialing intelligent peripheral (VD IP) device  70  and a conference calling IP  78 . 
     VD IP  70  is coupled to the Internet  30  via a network interface  72  and to the first switch  74  via a voice and signaling connection. VD IP  70  includes circuitry for performing voice dialing operations. Voice dialing operations include speech recognition operations and the placing of a call in response to the outcome of a speech recognition operation. Voice dialing IP  70  may include, for each voice dialing service subscriber supported by the VD IP  70 , a voice dialing directory which includes speech recognition models of names of people who may be called, with associated telephone numbers to be dialed when the name is recognized. 
     Conference calling IP  78  is coupled to both the Internet  30  and SSP  76 . The connection to the SSP  76  includes both voice and signaling lines. The conference calling IP  78  can, in response to information received via SSP  76  or the Internet  30 , initiate calls to one or more individuals and bridge the initiated calls. 
       FIG. 3  illustrates the computer system  50  which may be used at one or more customer premises, in greater detail. The computer  50  may be, e.g., a personal computer (PC), notebook computer, or personal data assistant (PDA). As illustrated the computer  50  includes memory  302 , a processor  304 , display device  314 , input device  316 , telephony circuit  308 , network interface card (NIC)  318 , modem  320  and audio signal processing circuitry  322  which are coupled together via bus  313 . While not illustrated in  FIG. 3 , in the case where wireless Internet access is supported, modem  320  may be coupled to antenna  52  shown in  FIG. 2 . 
     Processor  304 , under direction of routines stored in memory  302 , controls the operation of the computer  50 . Information and data may be displayed to a user of the device  50  via display  314  while data may be manually entered into the computer via input device, e.g., keyboard  316 . The NIC  318  can be used to couple the computer  50  to a local area network (LAN) or other computer network. Modem  320  may be, e.g., a DSL modem, cable modem or other type of modem which can be used to connect the computer system to the Internet  30 . Thus, via modem  320  the computer  50  can receive data from, and transmit data to, other devices coupled to the Internet  30 . 
     To provide the computer system  50  with the ability to perform various telephone functions such as dial a telephone number and host telephone calls, the computer system  50  includes telephony circuit  308 . An audio input device, e.g., microphone  310 , provides audio input to the telephone circuit as well as audio signal processing circuitry  322 . An audio output device, e.g., speaker  306 , allows a user of the system to hear audio signals output by telephony circuit  308 . Telephony circuit  308  includes an option connection to telephone network  22 . When the optional connection to the telephone network  22  is not used, the telephony circuit  308  may still receive and send audio signals via the Internet  30 . 
     In order to support digital recording, speech recognition model training, and speech recognition operations, audio signal processing circuitry  322  is provided. Processing circuitry  322  includes a feature extractor circuit  324 , a digital recording circuit  326 , a speech recognition circuit  328 , and a model training circuit  330  which are all coupled to bus  313 . The feature extractor  324  and digital recording circuit  326  are also coupled to the audio input device for receiving there from audio input to be processed. 
     Extracted feature information and digital recordings generated by circuits  324  and  326 , respectively can be stored in memory  302 . Memory  302  is also used to store various routines and data used by the various components of the computer system  50 . 
       FIG. 4  illustrates exemplary contents of memory  302  in detail. As illustrated the memory  302  includes speech recognition routines  402 , speaker independent speech recognition models (SI SRMS)  404 , speaker dependent speech recognition models (SD SRMS)  406 , model training routine  408 , stored speech data  410 , a voice dialing routine  416 , a word processor routine  418  which includes a speech recognition interface, and voice dialing data  420 . 
     Speech data  410  includes extracted feature information  412 , e.g., feature vectors, and digital recordings of speech  414 . The feature information  412  and/or recordings  414  represent speech information which can be transmitted via the Internet for use in model training and/or speech recognition operations. The voice dialing data  420 , used during voice dialing operations, includes a speaker dependent voice dialing record  422  and a speaker independent voice dialing customer record  424 . One or both of these records  422 ,  424  may be used to perform voice dialing operations. 
     Referring now to  FIG. 5 , there is illustrated an exemplary voice dialing customer record  520 . As illustrated the voice dialing customer record  520  includes a customer ID  501  which may be, e.g., the customer&#39;s home telephone number. It also includes a plurality of dialing entries represented by rows  510 ,  512 ,  514 ,  516 . Each dialing entry includes a text version of a name  502  which may be spoken to initiate dialing, a speech recognition model  504  corresponding to the name  502  in the entry, a telephone number  506  to be dialed in the event that the name is recognized and, optionally, a speech recording  508  of the name. After a name is recognized the voice dialing routine may play the recording associated with the recognized name  508  back to the system user as part of a confirmation message such as “calling” followed by the playback of the recording. Alternatively, an audio version of the recognized name may be generated from the text version  502  of the recognized name for confirmation message purpose. 
     In addition to the name and telephone number information included in the voice dialing customer record  520 , the record also includes information  520 , e.g., a world wide web Internet address, identifying a remote speech processing facility to be used in the event that a match is not identified between the models in the record and spoken speech being processed for voice dialing purposes or in the event that speech recognition models are to be updated or generated. The memory also includes a contact telephone number  522  where the user can be reached when the computer system&#39;s telephone connection is not enabled. 
     When the voice dialing customer record  520  includes speaker dependent speech recognition models, it may be used as the SD voice dialing customer record  422  shown in  FIG. 4 . When the voice dialing customer record  520  includes speaker independent speech recognition models, it may be used as the SD voice dialing customer record  424 . 
     Having described the computer system  50  in detail, speech processing facility  18  will now be discussed with reference to  FIG. 13 . Much of the circuitry shown in the  FIG. 13  embodiment of the facility  18  is similar to that previously discussed with regard to the computer system  50 . However, in the case of processors, buses, etc. the speech processing facility  18  is generally equipped with higher capacity devices, e.g., fast processors, a large amount of memory, high bandwidth bus, redundant LAN, telephone and Internet connections, etc. 
     As illustrated the speech processing system  18  includes memory  1302 , a processor  1304 , display device  1314 , input device  1316 , telephony/call initiation circuit  1308 , network interface card (NIC)  1318 , modem  1320  and audio signal processing circuitry  1322  which are coupled together via bus  1313 . Processor  1304 , under direction of routines stored in memory  1302 , controls the operation of the system  18 . Information and data may be displayed to a system administrator via display  1314  while data may be manually entered into the system  18  via input device  1316 . The NIC  1318  can be used to couple the system to a local area network (LAN) or other computer network. Modem  1320  may be, e.g., a DSL modem, cable modem or other type of modem which can be used to connect the computer system to the Internet  30 . Thus, via modem  1320  the system  18  can receive data from, and transmit data to, other devices coupled to the Internet  30 . 
     To provide the system  18  with the ability to perform various telephone functions such as dial a telephone number and bridge telephone calls, the system  18  includes telephony/call initiation circuit  1308 . 
     In order to support speech recognition model training, and speech recognition operations audio signal processing circuitry  1322  is provided. Processing circuitry  1322  includes a feature extractor circuit  1324 , a speech recognition circuit  1328 , and a model training circuit  1330  which are all coupled to bus  1313 . Thus, the components of the audio signal processing circuitry  1322  can receive audio signals and extracted speech feature information via bus  1313 . Extracted feature information, received speech, and generated speech recognition models can be stored in memory  1302 . Memory  1302  is also used to store various routines and data used by the various components of the system  18 . 
     The contents of the memory  1302  may include voice dialing data including voice dialing customer records for multiple customers. The memory  1302  also includes various speech recognition, call initiation and model training routines. In addition, the memory  1302  includes a training database  1209  which is a collection of speech samples used for training speech recognition models, a model store  1213  for storing generated speech recognition models and a system/model update list which includes information on remote systems which are serviced by the speech processing system. the information includes, e.g., system identification and contact information such as an E-mail address, the type of speech recognition models used by the individual systems, the words in each systems&#39; speech recognition vocabulary, and information on when to update the each systems speech recognition models. 
     Use of the speech processing facility to perform various operations, e.g., voice dialing, speech recognition model training and speech recognition operations, will be discussed in detail below. 
     While speech processing facility  18  can support a wider range of speech processing operations including voice dialing, specific telephone switch peripheral devices such as VD IP  70  may be dedicated to supporting voice dialing operations. An exemplary voice dialing IP  70  which may be used as the voice dialing IP of  FIG. 2  is shown in detail in  FIG. 6 . The VD IP  70  can support voice dialing operations in response to speech received via a conventional telephone connection or via the Internet  30 . Thus, the computer system  50  can use the VD IP  70  to perform a voice dialing operation. This can be done by E-mailing the VD-IP  70  a voice dialing request message including speech in an attached file. 
     The VD IP  70  includes a speech recognizer circuit  602 , switch I/O interface  607 , network interface  610 , processor  608  and memory  612 . The processor  608  is responsible for controlling the overall operation of the voice dialing IP  70  under control of routines stored in memory  612 . Memory  612  includes a speech recognition routine  613  which may be loaded into the speech recognizer circuit  602 , a voice dialing routine  614  and a call setup routine  615 . The voice dialing routine  614  is responsible for controlling the supply of audio signals to the speech recognizer circuit  602  and controlling various operations in response to recognition results supplied by the recognizer circuit  602 . 
     Speech recognizer  602  is coupled to a switch, e.g., SSP and receives voice signals therefrom. The speech recognizer circuit  602  uses speech recognition models stored in the memory  612  and the speech recognition routine  613  to perform a speech recognition operation on audio signals received from a telephone switch or from the Internet via network interface  610 . Speech recognition models used by the speech recognizer  602  may be speaker independent and/or speaker dependent models. The speech recognition models are retrieved from the personal dialer and corporate records  618 ,  620  based on a customer identifier which identifiers the particular customer whose speech is to be processed. 
     The voice dialing routine  614  receives information from the speech recognition circuit  602  which indicates the outcome of a speech recognition operation, e.g., whether a name in the customer&#39;s record was recognized. If a name is recognized, and speech was received via the Internet, the telephone number corresponding to the recognized name is returned via the Internet to the device which provided the speech. However, if a contact telephone number was received via the Internet with the speech to be processed, the voice dialing routine  614  calls the call setup routine  615  which is responsible for imitating a call to the telephone number corresponding to the recognized name. 
     In such a case, where the customer&#39;s computer  50  will not be used to place the call, the call setup routine  615  signals the telephone switch via interface  606  to initiate a call to the contact telephone number where the subscriber can be reached and to the telephone number corresponding to the recognized name. Once both parties answer, the call setup routine instructs the switch to bridge the calls thereby completing a call between the Internet based voice dialing service user and the party being called. 
     Instead of using VD IP  70 , computer system  50  can use the speech processing facility  18  to support a voice dialing operation. Voice dialing will now be described from the perspective of computer system  50  as it interacts with speech processing facility  18 .  FIG. 8  illustrates an exemplary voice dialing routine  416  which may be executed by the computer system  50 . 
     The voice dialing routine  800  begins in start step  802  when it is executed, e.g., by the processor  305  of computer system  50 . From step  802 , operation proceeds to step  804  wherein the routine monitors for speech input. If in step  806 , it is determined that speech was received in step  804 , operation proceeds to step  808 . Otherwise, operation returns to monitoring step  804 . 
     In step  808  a determination is made as to whether or not local speech feature extraction is supported. If it is not, operation proceeds directly to step  818 . However, if local feature extraction is supported, e.g., feature extractor  324  is present, operation proceeds to step  810  wherein a feature extraction operation is performed on the received speech. Next in step  814  a determination is made as to whether or not local speech recognition capability is available, e.g., a determination is made whether or not the system  50  includes speech recognition circuit  328 . If in step  328  it is determined that local speech recognition is not available, operation proceeds directly to step  818 . However, if local speech recognition capability is available, operation proceeds to step  812  wherein a local voice dialing sub-routine, e.g., the subroutine  900  illustrated in  FIG. 9  is called. 
     Referring now briefly to  FIG. 9 , it can be seen that  FIG. 9  illustrates a local voice dialing subroutine  900  which can be executed by the computer system  50 . The subroutine  900  can be used by the computer system  50  to perform voice dialing calls without having to contact an external voice dialing or speech processing facility. The subroutine  900  begins in start step  902 , e.g., in response to being called by voice dialing routine  800 . In step  902 , the subroutine is provided with the extracted feature information  903  produced, e.g., in step  810 , from the speech which is to be processed for voice dialing purposes. Operation then proceeds to step  904  wherein a speech recognition operation is performed using the received extracted speech feature information and one or more locally stored speech recognition models, e.g., speech recognition models obtained from the SD voice dialing customer record  422  or SI voice dialing customer record  424  stored in memory  302 . 
     In step  906  a determination is made as to whether or not a name was recognized as a result of the voice dialing operation. If a name was not recognized operation proceeds to return step  908  wherein operation returns to step  812  of the voice dialing routine  800  with an indicator that the local voice dialing operation was unsuccessful. 
     However, if a name was recognized by the speech recognition operation of step  904 , operation proceeds from step  906  to step  910 . In step  910 , a determination is made as to whether or not a computer to telephone connection exists. If the computer system  50  is connected to a telephone line, operation will proceed to step  914 . In step  914 , the computer system  50  is made to dial the telephone number associated, e.g., in one of the voice dialing records  422 ,  424 , with the recognized name. Then, in step  916 , the computer system  50  detects completion of the call initiated in step  914  before proceeding to step  918 . 
     If in step  910  it was determined that a computer-telephone connection did not exist, operation proceeds to step  912 . In step  912 , the telephone number to be dialed, i.e., the telephone number associated with the recognized name and the contact telephone number where the user of the system  50  can be reached, is transmitted, e.g., via the Internet, to a call establishment device such as conference calling IP  78 . The conference calling IP will initiate calls to both the number associated the recognized name and the contact number and then bridge the calls. In this manner, voice dialing can be used to place a call even when the computer system  50  is not coupled to a telephone line. 
     From step  912  operation proceeds to return step  918 . In return step  918  operation is returned to step  812  of the voice dialing routine  800  with an indicator, notifying the routine  800  that the local voice dialing operation was successful. The indication may be, e.g., a pre-selected value, message or other signal. 
     Upon a return from the local voice dialing sub-routine  900 , operation proceeds from step  812  to step  813 . In step  813  a determination is made as to whether or not the local voice dialing operation was successful. This is determined by success/failure information returned from the sub-routine  900 . If the local voice dialing operation was successful, operation proceeds to monitoring step  804  in preparation for another voice dialing operation. However, if the local voice dialing operation was not successful, operation proceeds to step  818  in an attempt to use outside resources, such as the speech process facility  18  or VD IP  70 , to determine a telephone number to be dialed. 
     In step  818  a system user ID is transmitted to the remote speech processing facility  18 . Then, in step  820  the received speech and/or extracted feature information is transmitted to the remote speech processing facility  18 . Next, in step  822  a determination is made as to whether a computer to telephone line connection exits. If in step  822 , it is determined that a computer-telephone connection does not exist, indicating that the system  50  cannot make a call, operation proceeds to step  824  wherein a telephone contact number  401  is transmitted to the remote speech processing facility. The telephone contact number  401  is the telephone number of a telephone where the user of the system  50  can be reached. 
     Operation proceeds from step  824  to step  826 . In the event it is determined in step  822  that a computer-telephone connection exists, operation will proceed directly from step  822  to step  826 . 
     As will be discussed below, in response to the transmitted information, the speech processing facility  18  executes a voice dialing routine. Upon detecting the name of a party having an associated telephone number, the executed routine returns, e.g., in an E-mail message, the telephone number associated with the recognized name via the Internet assuming a contact telephone number was not provided to the facility  18 . The telephone number can than be used by the computer system  50  to place a call to the party whose name was spoken. In the case where the computer system provides a contact telephone number to the speech processing system  18 , the system  18  realizes that the computer  50  cannot place the call. In such a case, the remote speech processing facility  18  returns a signal indicating that the named party is being called assuming a name was recognized or that the system was unable to identify a party to be called in the event a name was not recognized. 
     In step  826 , the computer system  50  detects the response sent by the speech processing facility in response to the speech and voice dialing information supplied to the facility. In step  828  a determination is made as to whether or not the received response includes a telephone number to be dialed. If the response does not include a telephone number to be dialed, operation proceeds to step  829  where the system user is provided a message indicating the results of the remote voice dialing operation. That is, the system user is notified if the named party is being called or that the system was unable to identify a party to be called. The message to be provided is indicated by the response received from the speech processing facility  18 . Operation proceeds from notification step  829  via GOTO step  834  to monitoring step  804 . 
     Assuming a telephone number is received from the remote speech processing facility, operation will proceed from step  826  to step  830  wherein the computer system  50  dials the received telephone number. After call completion is detected in step  832 , operation proceeds to step  804  via GOTO step  834 . In this manner, the voice dialing routine returns to a state of monitoring for speech input, e.g., input associated with an attempt to place another telephone call. 
     Voice dialing from the perspective of the speech processing facility will now be described with reference to  FIG. 10 . A remote voice dialing routine  1000  which may be implemented by, e.g., speech processing facility  18 , is illustrated in  FIG. 10 . The routine starts in step  1002  when it is executed by the speech processing facility&#39;s processor. In step  1004 , voice dialing service input is received from a remote device, e.g. computer system  50 , via a communications channel such as the Internet. In the case of a voice dialing operation, the input will normally include a user ID, speech and/or extracted feature information, and optionally, a telephone contact number where the system user can be reached by telephone. This information corresponds to the information normally transmitted by the computer system  50  in steps  818 ,  822  and  824  of voice dialing routine  800 . 
     Next, in step  1006 , voice dialing information is retrieved from memory. The retrieved information may include, e.g., a voice dialing record including speech recognition models and corresponding telephone numbers to be used in providing voice dialing services for the identified user. The voice dialing record may be a customer specific record, e.g., part of a personal voice dialing record corresponding to the received user ID, or a common voice dialing record such as a corporate voice dialing directory shared by many individuals including the user identified by the received user ID. 
     After the dialing directory information has been retrieved, operation proceeds to step  1008  wherein a determination is made as to whether or not extracted feature information was received. If extracted feature information was received operation proceeds directly to step  1012 . If extracted feature information was not received operation proceeds to step  1010  wherein a feature extraction operation is performed on the received speech. Operation proceeds from step  1010  to step  1012 . 
     In step  1012  a speech recognition operation is performed using the retrieved voice dialing information, e.g., speech recognition models, and received or extracted feature information. The results of the speech recognition operation are supplied to step  1014  wherein a determination is made as to whether a name in the voice dialing directory being used was identified. If a name was identified operation proceeds to step  1016 . 
     In step  1016  a determination is made as to whether or not a telephone contact number was received, e.g., in step  1004 . If a telephone contact number was received, indicating that the user can&#39;t, or does not want to, initiate a call from his/her computer, operation proceeds to step  1018 . 
     In step  1018  the telephone number to be dialed, i.e., the telephone number associated in the retrieved voice dialing information and the contact telephone number is transmitted to a call initiation device. The user&#39;s ID information may also be transmitted to the call initiation device. The call initiation device may be, e.g., conference calling IP  78  or circuitry interval to the speech processing system  18 . 
     When the call initiation device is an external device such as conference calling IP  78 , the telephone number to be dialed, the contact telephone number, and the user ID information is transmitted to the call initiation device over any one of a plurality of communication channels including the Internet, a LAN, and conventional telephone lines. In response to receiving the transmitted information the call initiation device executes a call establishment routine, e.g., the routine  1100  illustrated in  FIG. 11 , will initiate a call to both the telephone number to be dialed and the contact telephone number and then bridge the calls when they are answered. From step  1018  of  FIG. 10 , operation proceeds to step  1028 . 
     In step  1016 , of  FIG. 10 , if it is determined that a telephone contact number was not received, e.g., because the device which transmitted the voice dialing information is capable of initiating a call, operation proceeds to step  1020  wherein the telephone number to be dialed is transmitted (returned) to the remote computer system  50  in response to the received voice dialing information, e.g., received speech and user ID information. Then operation proceeds to step  1028 . 
     Referring once again to step  1014  if it is determined in this step that a name was not recognized by the speech recognition operation then processing proceeds to step  1022  instead of step  1016 . In step  1022  a determination is made as to whether there is an additional remote speech processing system associated with the identified user, e.g., another system such as VD IP  70  which can be used support a voice dialing operation. This determination may be made by checking information about the user stored in memory. 
     If the answer to the inquiry made in step  1022  is no, operation proceeds to notification step  1023  prior to proceeding to STOP step  1028 . In step  1023  a message is sent back to the system  50  indicating to the system that the voice dialing attempt failed due to a failure to recognize a name. 
     If in step  1022  it is determined that there is an additional remote speech processing system associated with the identified user, operation will proceed from step  1022  to step  1024 . In step  1024  the user ID information is transmitted to the additional remote speech processing facility associated with the identified user. Then, in step  1026 , the previously received speech information and/or feature information is transmitted to the additional remote speech processing facility. Thus, the additional remote speech processing facility is provided an opportunity to provide a voice dialing service when the current facility is unable to ascertain a telephone number to be dialed. The additional speech processing facility, e.g., VD IP  70 , will notify the user&#39;s system  50  of the ultimate outcome of the voice dialing operation. 
     Operation proceeds from step  1026  to STOP step  1028  wherein the remote voice dialing routine  1028  is stopped pending its execution to service additional voice dialing service requests. 
       FIG. 11  illustrates a call establishment routine  1100  that is executed by a call initiation device, such as the conference calling IP  78  or telephone call initiation circuit  1308 , in response to call initiation information received as part of a voice dialing operation. 
     As illustrated in  FIG. 11 , the call establishment routine starts in step  1102  when it is executed, e.g., by a processor in the conference IP  78 . Then, in step  1104  a user ID, a telephone number to be dialed and a contact telephone number is received, e.g., from the speech processing facility  18  via an Internet or telephone communications channel. Such a set of information is recognized as a request for a call initiation and bridging operation. When such information is received operation proceeds to steps  1106  and  1108 . In step  1106  the conference calling IP initiates a call using the telephone number to be dialed while in step  1108  the contact telephone number is used to initiate a call. The initiation of the calls in steps  1106 ,  1108  may occur in parallel or serially. Once the two calls are answered, in step  1110 , the calls are bridged. Then in step  1112  the bridged call is allowed to terminate normally, e.g., by either of the called parties hanging up their telephone. With the termination of the bridged call, the call establishment routine STOPS in step  1114  pending its re-execution to service additional dialing requests from, e.g., the speech processing facility  18 . 
     In addition to supporting voice dialing operations, the speech processing  18  is capable of receiving speech signals, e.g., in compressed or uncompressed digital form, generating speech recognition models from the received speech, and then distributing the generated models to one or more devices, e.g., voice dialing IPs, business sites which perform speech recognition, and individual computer systems  50 . In accordance with one feature of the present invention speech to be used in speech recognition model training operations, and the models generated there from, are transmitted over the Internet. Alternatively, other communications channels such as conventional telephone lines may be used for this purpose. 
     Speech recognition model training will now be discussed in detail.  FIG. 7  illustrates a model training routine  700  which may be executed under control of a user of the computer system  50  when the user desires to train a new speech recognition model or to update an existing model, e.g., because of unsatisfactory recognition results. 
     The model training routine  700  begins in step  702  wherein it is initially executed by the processor  304 . Operation proceeds to step  704  wherein the processor  304  receives text corresponding to the word or name to be trained or retrained. The text may be entered by a user of the computer system  50  via keyboard  316 . 
     In response to receiving the text version of the word or name to be trained, e.g., modeled, in step  706  the user is prompted to state the word or name to be trained. Then, in step  708  speech received from the user is recorded by the digital recording circuit  326 . Next, in step  710  a determination is made as to whether or not local feature extraction is supported. Assuming a feature extractor  324  is included in the computer system  50 , operation proceeds from step  710  to step  712 . In step  712 , a feature extraction operation is performed on the recorded speech resulting in the generation of a set of feature vectors corresponding to the speech to be modeled. 
     Since the set of feature vectors includes speech characteristic information, e.g., timing, duration, amplitude and/or power information and/or changes in these values over time, and not the actual digitized speech, the set of feature vectors generated in step  712  is often considerably smaller than the digital recording from which the set of feature vectors is generated. 
     Operation proceeds from step  712  to step  714 . In cases where local feature extraction is not supported, operation proceeds directly from step  710  to step  714 . 
     In step  714  information required from the computer system  50  to train or retrain a speech recognition model and to return the resulting model, is transmitted to a speech processing facility, e.g., via the Internet. In step  714  a user identifier is transmitted to the speech processing facility. In addition a text version of the speech to be modeled, the extracted set of feature information corresponding to the speech to be modeled, the digital recording of the speech to be modeled and/or an already existing speech recognition model corresponding to the speech to be modeled is transmitted to the speech processing facility. 
     As will be discussed below, the speech processing facility  18  processes the transmitted speech or feature information by using it in a speech recognition model training process. The speech recognition model generated by the speech processing facility  18  is then returned to the computer system  50  for storage and/or use in speech recognition operations. 
     From step  714  operation of the computer system  50  proceeds to step  716  wherein the system  50  receives, e.g., via the Internet, one or more speech recognition models from the speech processing facility  18 . The received speech recognition models will include the model or models generated from the speech extracted feature information and/or other information transmitted to the speech processing facility in step  714 . 
     The received speech recognition models are stored in the computer system&#39;s memory  302  in step  718 . In the case of updated or retrained models, the received model will replace the previous model or models corresponding to the same words, names or sounds. 
     As a result of storage in the memory  302 , the speech recognition models will be available to applications which perform speech recognition such as the voice dialing and word processor applications. After storage of the received models, the new model training routine  700  then stops in step  720  until being executed again to train an additional model. 
     In addition to providing voice dialing service, the speech processing facility  18  can be used to provide speech recognition model training services.  FIG. 12  illustrates a model generation routine  1200 , which can be implemented by the speech processing facility  18 . As illustrated, the routine starts in step  1202  when it is executed by the speech processing facility&#39;s processor. Operation then proceeds to steps  1202  and  1204  which represent parallel processing paths. While the processing associated with these paths can be performed in parallel, they can also be performed on a time shared basis as is commonly done in single processor systems. 
     In step  1204  the system monitors for a model generation and/or model updating service request, e.g., a signal from a device such as the computer system  50  or computerized business system  58  indicating that a speech recognition model needs to be generated or updated. The request may take the form of an E-mail message with an attachment including information, speech and/or other speech data. When a request for such a service is received, e.g. via the Internet  30 , operation proceeds to step  1206  wherein the information and data used to provide the requested service is received by the processor  1304 , e.g., by extracting the attachment from the E-mail request message. The received information depends on the service to be performed. 
     Block  1206   a  illustrates exemplary data that is received with a request to generate a new speech recognition model. The data  1206   a  includes a User ID, speech or feature information, text information providing a text representation of the word or phrase to be modeled, and optional speech recognition model type information. The User Id may be a telephone number, Email address or some other type of unique identifier. Assuming model type information is not provided a default model type will be used. 
     Block  1206   b  illustrates exemplary data that is received with a request to update an existing speech recognition model. The data  1206   b  includes a User ID, an existing speech recognition model to be updated, existing model type information, speech or feature information, text information providing a text representation of the word or phrase to be modeled, and optional updated speech recognition model type information. If the optional updated speech recognition model type information is not provided, it is assumed that the updated model is to be of the same type as the received existing model. 
     Operation proceeds from step  1206  to step  1208 . In step  1208 , the training database  1209  maintained in the speech processing facility  18  is augmented with the speech received in step  1206 . Thus, over time, the size and robustness of the speech training database  1211  will improve from the input received from various sources which use the speech processing facility to provide speech recognition model generation and updating services. Since users will tend to retrain models which have been providing poor recognition results the quality of the training data used for numerous subscribers is improved as each subscriber provides new and/or additional speech samples to be used in model training. 
     From step  1208  operation proceeds to step  1210  wherein a speech recognition model is generated from the received speech, feature information and/or other received information. Various known model training techniques may be used to implement step  1210  with the training technique being used at any given time being determined by the training data available and the type of speech recognition model to be generated. 
     In the case where speech was received, the speech normally undergoes a feature extraction operation as part of the training process. In the case where speech feature information was received, in addition or in place of speech, the provided feature information, e.g., feature vectors, may be used in model training thereby avoiding the need to perform a feature extraction operation on received speech. 
     The generated speech recognition model will be of the type specified by the received information. In the case of a speaker dependent speech recognition model type, the generated model will be a speaker dependent speech recognition model. In the case of speaker independent speech recognition model the generated model will be a speaker independent model. Speaker independent models are normally trained using the received speech and speech included in the training database  1209  as training data. Speaker dependent models are normally generated using the received speech as the training data. In addition to indicating whether a generated model is to be speaker independent or speaker dependent the received model type information can indicate particular features or information which are to be used in the model, e.g., energy and delta energy coefficient information. In the case of models which are being updated, the updated model type information can specify a different model type than the existing model type information. 
     In one particular application, a dynamic time warping (DTW) template is received and processed along with speech to generate a speaker dependent Hidden Markov model as an updated model. In such an embodiment the received existing model type information would be e.g., “DTW template” and the updated model type information would be “SD HMM” indicating a speaker dependent HMM. In this particular application, the template to HMM model conversion and training techniques discussed in U.S. Pat. No. 6,014,624 which is hereby expressly incorporated by reference may be used in the model generation step  1210 . 
     With the new or updated model generated, operation proceeds from step  1210  to step  1212 . In step  1212 , the generated model is stored in the speech processing facility&#39;s model store  1213 . The model store includes separate sets of models for individual users, and a common model store for speaker independent models. The speaker independent models are stored in the corresponding user&#39;s model set which generated speaker independent models are stored in the speaker independent model set. The models may be stored according to their intended application as well as type if desired. That is, models intended for voice dialing applications may be stored separately in the model store  1213  from models stored for word processing operations. 
     From step  1212 , operation proceeds to step  1214  wherein the generated speech recognition model is transmitted to the device from which the model generation or updating request was received. Operation then proceeds to step  1204  wherein the processor monitors for additional input, e.g., requests to generate or update additional speech recognition models. 
     The processing path which begins with step  1224  executes in parallel with the processing path which beings with step  1204 . In step  1224  a system clock is maintained. Operation proceeds from step  1224  to step  1226  wherein a determination is made as to whether or not a preselected time corresponding to a selected time interval which is to occur between the transmission of model updates has passed. If the preselected time has not expired operation returns to step  1224 . However, if the preselected period of time has expired operation proceeds to step  1228  wherein updated models stored in the model store  1213  are transmitted, e.g., via the Internet  30 , to systems which use the speech recognition models, e.g., systems indicated in the update list  1215  stored in the speech processing systems memory. To avoid the needless transmission of models that have not been updated only those speech recognition models which have been updated, as indicated by creation time and date information stored in the model store along with the models, are transmitted to the various systems to be updated. After the updated models are transmitted, operation returns to step  1224 . 
     As an alternative to broadcasting updated speech recognition models on a periodic basis, systems which use speech recognition models can periodically request, from the speech processing facility  18 , speech recognition model updates via the Internet. 
     As discussed above, the speech processing facility  18  can be used to provide speech recognition services in addition to voice dialing and speech recognition model training services. Speech recognition service can be provided to devices, e.g., computer system  50  and business computer system  58 , which have speech capture capabilities but may lack speech recognition capabilities or have relatively limited speech recognition capabilities. Systems can transmit to the speech processing facility  18  speech and/or extracted speech feature information, e.g., feature vectors, and receive in response the results of a speech recognition operation performed using the received speech or feature vectors. The speech or feature vectors may be transmitted as a file attachment to an E-mail message sent by the system  50  or  58  over the Internet to the facility  18  requesting a speech recognition operation. The results of the speech recognition operation can be returned by E-mail to the device requesting the speech recognition operation. The results may be in the form of a list of words recognized in the received speech or from the received feature vectors. The words may be included in a text portion of the responsive E-mail message or in a text file attachment. 
       FIG. 14  illustrates a speech recognition routine that is implemented by the speech processing facility  18  to service speech processing requests received from various devices coupled to the Internet  30 . As illustrated, the routine  1400  begins in step  1402 , wherein the routine  1400  is retrieved from memory  1302  and executed by the speech processing facility&#39;s processor  1304 . 
     Next, in step  1404 , the speech processing system  18  receives a speech recognition service request from a remote device, e.g., system  50  or  58 . As mentioned above, the request may take the form of an E-mail message. The received request includes speech, e.g., compressed or uncompressed digitized speech, and/or extracted speech feature information. This data may be included in the form of an attached file. In addition, the message includes a system identifier, e.g., return E-mail address, which can be used to identify the source system to which the speech recognition results are to be returned. 
     From step  1404  operation proceeds to step  1406  wherein the speech processing facility performs a speech recognition operation using the received speech or received feature information in an attempt to recognize words in the received speech or speech from which the received feature information was extracted. Then, in step  1408  a message is generated including the speech recognition results, e.g., recognized words, in text form. The generated message may be an E-mail message with the source of the speech or feature information being identified as the recipient and the recognized information incorporated into the body of the message or an attached text file. 
     In step  1410  the generated message including the recognition results is transmitted, e.g., via the Internet  30 , to the system which supplied the speech or feature information used to perform the recognition operation. Then operation proceeds to step  1404  to await another request for a speech recognition operation. 
     Thus, in the above described manner, through the use of the Internet and simple E-mail messages, speech processing facility  18  provides speech recognition services to physically remote devices which are also coupled to the Internet  30 . 
     Numerous variations on the above described methods and apparatus are possible without departing from the scope of the invention.