Abstract:
A system, method, computer program product, and application program interface for indexing data relating to results of speech recognition in a database management system provides the capability to perform simple and efficient searches on audio speech data with reduced development effort. An application program interface for indexing data relating to results of speech recognition in a database management system comprises an indextype operable to support text queries on speech recognition results, an interface operable to provide interaction with an index of the indextype, and a format adapter interface a format adapter that the index creation activity will invoke to extract relevant information from a proprietary speech recognition format.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
   The benefit under 35 U.S.C. § 119(e) of provisional application Ser. No. 60/419,520, filed October 21, 2002, is hereby claimed. 

   FIELD OF THE INVENTION 
   The present invention relates to a system, method, computer program product, and application program interface for indexing data relating to results of speech recognition in a database management system. 
   BACKGROUND OF THE INVENTION 
   Speech recognition technology provides the capability to design computer systems that can recognize spoken words. Speech recognition systems accept audio speech data, which are digitized audio speech signals, and output textual information. A number of speech recognition systems are available on the market. The most powerful can recognize thousands of words. However, they generally require an extended training session during which the computer system becomes accustomed to a particular voice and accent. Such systems are said to be speaker dependent. More recently speech recognition systems have been developed that can recognize speech without being trained using a particular voice and accent. Such systems may recognize the speech of most or any speakers, and are said to be speaker independent. 
   Audio speech data may be treated like any other data and stored and organized in a database. In the case of textual or numeric data, searches may be readily performed on the data by a database management system for the database. However, unlike textual or numeric data, there is no simple and efficient way to search audio speech data. Prior systems required developers who wished to search audio speech data had to develop complex software procedures in order to perform the searching. For example, to perform a typical search, a user will want to know which audio or video assets satisfy given text query search criteria, the time offsets within each matched media asset where matches occurred, and the user may want to know the speech recognition confidence of each match. Conventionally, this required development of software to perform several iterations of extracting the relevant text, time offset, and confidence data from the speech recognition results, build appropriate B-tree indices on this extracted data, and associate time offsets and confidence values. with their corresponding text data. In addition, procedures would have to be developed that would use the index and search through the text data for matched rows, and then search through the matched rows for time offsets into the media asset where matches occurred. 
   What is needed is a technique by which simple and efficient searches may be performed on audio speech data and which provides reduced development effort. 
   SUMMARY OF THE INVENTION 
   The present invention provides the capability to perform simple and efficient searches on audio speech data with reduced development effort. According to one embodiment of the present invention, an application program interface for indexing data relating to results of speech recognition in a database management system comprises an indextype operable to support text queries on speech recognition results, an interface operable to provide interaction with an index of the indextype, and a format adapter interface operable to invoke a format adapter for converting speech recognition results having a first format to a second format. 
   The format adapter may be operable to parse the speech recognition results in the first format, extract from the speech recognition results text data representing the recognized speech, information relating to a confidence in each speech recognition result, and timestamp information indicating a location of each portion of a speech recognition result, and generate speech recognition results in the second format using the extracted text data representing the recognized speech, information relating to a confidence in each speech recognition result, and timestamp information indicating a location of each portion of a speech recognition result. 
   The indextype may comprise the text data representing the recognized speech, the information relating to a confidence in each speech recognition result, and the timestamp information indicating a location of each portion of a speech recognition result. The interface may be operable to provide interaction comprising performing a query of the text data representing the recognized speech. The query of the text data representing the recognized speech relates to the confidence information and/or the timestamp information. The results of the query may indicate time offsets within each matched media asset where matches occurred and speech recognition confidence of each match occurrence within a matched media asset. 

   
     BRIEF DESCRIPTION OF THE DRAWINGS 
     The details of the present invention, both as to its structure and operation, can best be understood by referring to the accompanying drawings, in which like reference numbers and designations refer to like elements. 
       FIG. 1  is an exemplary dataflow diagram of speech indexing processing performed in the present invention. 
       FIG. 2  is a block diagram of an exemplary implementation of a database management system, in which the present invention may be implemented. 
       FIG. 3  is an exemplary flow diagram of a process of operation of the present invention. 
       FIG. 4  is an exemplary format of data table that may be used in the present invention. 
       FIG. 5  is an exemplary code sample of how an application would invoke speech recognition on a particular row and populate the result column. 
       FIG. 6  is an example of an SQL command to build an index on the result column. 
       FIG. 7  is an example of an SQL command to create and pass preferences as arguments to index creation. 
       FIG. 8  is an example of a simple query on the data table, which makes use of the index. 
       FIG. 9  is an example of a query that retrieves confidence and timestamps for each occurrence within a matched audio asset row. 
       FIG. 10  is an example of an interface to a format adapter shown in  FIG. 1 , which is a proprietary format understanding procedure that extracts the information required for creating an index of the required indextype from a proprietary audio processing result format of a speech recognition engine. 
       FIG. 11  is an algorithmic description of an exemplary implementation of the proprietary format understanding procedure. 
   

   DETAILED DESCRIPTION OF THE INVENTION 
   An exemplary dataflow diagram of speech indexing processing performed in the present invention is shown in FIG.  1 . Included in  FIG. 1  are database management system (DBMS)  102 , speech recognition engine  104 , and speech query requestor  106 . Speech query requester  106  may be any database client, tool, or application that wants to issue text queries on audio speech data. 
   Database management system (DBMS)  102  provides the capability to store, organize, modify, and extract information from one or more databases included in DBMS  102 . From a technical standpoint, DBMSs can differ widely. The terms relational, network, flat, and hierarchical all refer to the way a DBMS organizes information internally. The internal organization can affect how quickly and flexibly you can extract information. 
   Each database included in DBMS  102  includes a collection of information organized in such a way that computer software can select and retrieve desired pieces of data. Traditional databases are organized by fields, records, and files. A field is a single piece of information; a record is one complete set of fields; and a file is a collection of records. An alternative concept in database design is known as Hypertext. In a Hypertext database, any object, whether it be a piece of text, a picture, or a film, can be linked to any other object. Hypertext databases are particularly useful for organizing large amounts of disparate information, but they are not designed for numerical analysis. 
   Typically, a database includes not only data, but also low-level database management functions, which perform accesses to the database and store or retrieve data from the database. Such functions are often termed queries and are performed by using a database query language, such as Structured Query Language (SQL). SQL is a standardized query language for requesting information from a database. Historically, SQL has been a popular query language for database management systems running on minicomputers and mainframes. Increasingly, however, SQL is being supported by personal computer database systems because it supports distributed databases (databases that are spread out over several computer systems). This enables several users on a local-area network to access the same database simultaneously. 
   Most full-scale database systems are relational database systems. Small database systems, however, use other designs that provide less flexibility in posing queries. Relational databases are powerful because they require few assumptions about how data is related or how it will be extracted from the database. As a result, the same database can be viewed in many different ways. An important feature of relational systems is that a single database can be spread across several tables. This differs from flat-file databases, in which each database is self-contained in a single table. 
   DBMS  102  may also include one or more database applications, which are software that implements a particular set of functions that utilize one or more databases. Examples of database applications include:
         computerized library systems   automated teller machines   flight reservation systems   computerized parts inventory systems       

   Typically, a database application, includes data entry functions and data reporting functions. Data entry functions provide the capability to enter data into a database. Data entry may be performed manually, by data entry personnel, automatically, by data entry processing software that receives data from connected sources of data, or by a combination of manual and automated data entry techniques. Data reporting functions provide the capability to select and retrieve data from a database and to process and format that data for other uses. Typically, retrieved data is used to display information to a user, but retrieved data may also be used for other functions, such as account settlement, automated ordering, numerical machine control, etc. 
   DBMS  102  includes speech enhancements  108 , format adapter  110 , data table  112  and speech indexing processing  114 . Speech enhancements  108  are extensions to the standard query language of DBMS  102 . For example, where DBMS  102  uses SQL, speech enhancements include extensions to the command set of SQL, an indextype, and its associated operators and types to empower applications with sophisticated text querying capabilities on audio data. 
   Speech recognition engine  104  provides speech recognition processing functionality to DBMS  102 . Speech recognition engine  104  is typically configured as a server communicatively connected to DBMS  102 . Preferably, speech recognition engine  104  provides large vocabulary continuous speech recognition (LVCSR) services to DBMS  102 . Essentially, speech recognition engine  104  receives data that represents digitized speech, processes the data to recognize the speech, and outputs text data that represents the speech, which is the speech recognition result. The speech recognition results are placed in the CLOB (Character Large Object) result column in the data table  112  the procedure that invoked the speech recognition processing. This procedure places the result in a CLOB column in data table  112  next to the audio data. When a Create Index command is issued on this CLOB column, Speech Indexing processing  114  is invoked, which in turn invokes format adapter  110 . Typically, the speech recognition result is arranged in a proprietary format. Format adapter  110  adapts the format of the speech recognition result generated by speech recognition engine  104  to the format used for speech indexing. Format adapter  110  parses the speech recognition result and extracts the required information. In particular, format adapter  110  extracts text, confidence, and timestamp tuples from each speech recognition result. 
   Speech indexing processing  114  receives the text, confidence, and timestamp tuples extracted from the proprietary format of each speech recognition result by format adapter  110 , stores the extracted information in its own internal data structures and creates an index of the required indextype based on the extracted data. When an index of the required indextype is created or updated, speech indexing processing  114  is invoked for each new or updated row in data table  112 . The row data, which are extracted from the speech recognition results, along with a table name and key to the original row in the indexed table, are provided as parameters. The routine must process the speech recognition result to extract &lt;text, timestamp, confidence&gt; and insert this data, along with some additional computed data (character offset and sequence number), and the key supplied as a parameter to the procedure into a that is part of an index internal data structure. Speech indexing processing  114  then inserts the extracted tuples of information into index data structures that are stored independently from the table upon which the index is built. 
   An example of an interface  1100  to format adapter  110  and speech indexing processing  114  is shown in  FIG. 10  An example of an implementation of format adapter  110  is shown in FIG.  11 . 
   A block diagram of an exemplary implementation of a DBMS  102 , in which the present invention may be implemented, is shown in FIG.  2 . DBMS  102  is typically a programmed general-purpose computer system, such as a personal computer, workstation, server system, and minicomputer or mainframe computer. DBMS  102  includes one or more processors (CPUs)  202 A- 202 N, input/output circuitry  204 , network adapter  206 , and memory  208 . CPUs  202 A- 202 N execute program instructions in order to carry out the functions of the present invention. Typically, CPUs  202 A- 202 N are one or more microprocessors, such as an INTEL PENTIUM® processor.  FIG. 2  illustrates an embodiment in which DBMS  102  is implemented as a single multi-processor computer system, in which multiple processors  202 A- 202 N share system resources, such as memory  208 , input/output circuitry  204 , and network adapter  206 . However, the present invention also contemplates embodiments in which DBMS  102  is implemented as a plurality of networked computer systems, which may be single-processor computer systems, multi-processor computer systems, or a mix thereof. 
   Input/output circuitry  204  provides the capability to input data to, or output data from, DBMS  102 . For example, input/output circuitry may include input devices, such as keyboards, mice, touchpads, trackballs, scanners, etc., output devices, such as video adapters, monitors, printers, etc., and input/output devices, such as, modems, etc. Network adapter  206  interfaces DBMS  102  with network  210 . Network  210  may include one or more standard local area networks (LAN) or wide area networks (WAN), such as Ethernet, Token Ring, the Internet, or a private or proprietary LAN/WAN. 
   Memory  208  stores program instructions that are executed by, and data that are used and processed by, CPU  202  to perform the functions of DBMS  102 . Memory  208  may include electronic memory devices, such as random-access memory (RAM), read-only memory (ROM), programmable read-only memory (PROM), electrically erasable programmable read-only memory (EEPROM), flash memory, etc., and electromechanical memory, such as magnetic disk drives, tape drives, optical disk drives, etc., which may use an integrated drive electronics (IDE) interface, or a variation or enhancement thereof, such as enhanced IDE (EIDE) or ultra direct memory access (UDMA), or a small computer system interface (SCSI) based interface, or a variation or enhancement thereof, such as fast-SCSI, wide-SCSI, fast and wide-SCSI, etc, or a fiber channel-arbitrated loop (FC-AL) interface. 
   In the example shown in  FIG. 2 , memory  208  includes database management routines  212 , database  214 , and operating system  216 . Database management routines  212  include software routines that provide the database management functionality of DBMS  102 . Database management routines  212  include SQL interface with speech enhancements  108 , format adapter  110 , and speech indexing processing  114 . SQL interface  108  accepts database queries using the SQL database query language, converts the queries to a series of database access commands, calls database processing routines to perform the series of database access commands, and returns the results of the query to the source of the query. For example, in an embodiment in which DBMS  102  is a proprietary DBMS, such as the ORACLE® DBMS, SQL interface  108  may support one or more particular versions of SQL or extensions to SQL, such as the ORACLE® PL/SQL extension to SQL. Speech enhancements are extension to the standard query language of DBMS  102 . For example, where DBMS  102  uses SQL, speech enhancements include extensions to the command set of SQL, an indextype, and its associated operators and types to empower applications with sophisticated text querying capabilities on audio data. 
   Format adapter  110  processes the speech recognition result from speech recognition engine  104 . Typically, the speech recognition result is arranged in a proprietary format. Format adapter  110  adapts the format of the speech recognition result generated by speech recognition engine  104  to the format used for speech indexing. Format adapter  110  parses the speech recognition result and extracts the required information. In particular, format adapter  110  extracts text, confidence, and timestamp tuples from each speech recognition result. 
   Speech indexing processing  114  receives. the text, confidence, and timestamp tuples extracted from the proprietary format of each speech recognition result by format adapter  110 , stores the extracted information in its own internal data structures and creates an index of the required indextype based on the extracted data. When an index of the required indextype is created or updated, speech indexing processing  114  is invoked for each new or updated row in data table  112 . The row data, which are extracted from the speech recognition results, along with a table name and key to the original row in the indexed table, are provided as parameters. The routine must process the speech recognition result to extract &lt;text, timestamp, confidence&gt; and insert this data, along with some additional computed data (character offset and sequence number), and the key supplied as a parameter to the procedure into a that is part of an index internal data structure. Speech indexing processing  114  then inserts the extracted tuples of information into index data structures that are stored independently from the table upon which the index is built. Database  214  includes a collection of information organized in such a way that computer software can select, store, and retrieve desired pieces of data. Typically, database  214  includes a plurality of data tables, such as data table  112 . Data table  112  is arranged to store audio speech data that has been or is to be processed by speech recognition engine  104 , shown in  FIG. 1 , speech recognition processing results output by speech recognition engine  104 . Preferably, indexing information is kept in internal data structures, not in the same data table that stores the media data and speech recognition results. Typically, a user of the system would store media assets in data table  112 . 
   In addition, as shown in  FIG. 2 , the present invention contemplates implementation on a system or systems that provide multi-processor, multi-tasking, multi-process, and/or multi-thread computing, as well as implementation on systems that provide only single processor, single thread computing. Multi-processor computing involves performing computing using more than one processor. Multi-tasking computing involves performing computing using more than one operating system task. A task is an operating system concept that refers to the combination of a program being executed and bookkeeping information used by the operating system. Whenever a program is executed, the operating system creates a new task for it. The task is like an envelope for the program in that it identifies the program with a task number and attaches other bookkeeping information to it. Many operating systems, including UNIX®, OS/2®, and WINDOWS®, are capable of running many tasks at the same time and are called multitasking operating systems. Multi-tasking is the ability of an operating system to execute more than one executable at the same time. Each executable is running in its own address space, meaning that the executables have no way to share any of their memory. This has advantages, because it is impossible for any program to damage the execution of any of the other programs running on the system. However, the programs have no way to exchange any information except through the operating system (or by reading files stored on the file system). Multi-process computing is similar to multi-tasking computing, as the terms task and process are often used interchangeably, although some operating systems make a distinction between the two. 
   An exemplary flow diagram of a typical process  300  of operation of a database management system incorporating the present invention is shown in FIG.  3 . It is best viewed in conjunction with FIG.  1 . Process  300  begins with step  302 , in which media content is uploaded into a database table in DBMS  102 , such as data table. In particular, media content includes audio speech data, which are digitized audio speech signals. In step  304 , a speech recognition processing requestor  106 , such as an application, that wants to process audio data with speech recognition engine  104  invokes the appropriate speech recognition. This causes the speech recognition engine  104 , which is waiting for speech processing requests to receive a request for speech recognition. The received requests are processed by interface  116  of speech recognition engine  104 . Speech recognition engine  104  processes the speech data in this request in order to recognize the speech and generate text data representing the recognized speech. 
   In step  308 , format adapter  110  adapts the format of the speech recognition result generated by speech recognition engine  104  to the format used for speech indexing. Format adapter  110  parses the speech recognition result and extracts the required information. In particular, format adapter  110  extracts text, confidence, and timestamp tuples from each speech recognition result. Then, speech indexing processing  114  receives the text, confidence, and timestamp tuples extracted from the proprietary format of each speech recognition result by format adapter  110 , inserts the extracted data in to data table  112  and creates an index of the required indextype based on the inserted data. In one embodiment shown in  FIG. 1 , the extracted text, confidence, and timestamp tuples from format adapter  110  are passed directly to speech indexing processing  114  for index creation. In other embodiments, the extracted text, confidence, and timestamp tuples from format adapter  110  may be stored before being passed o speech indexing processing  114  for index creation. When an index of the required indextype is created or updated, speech indexing processing  114  is invoked for each new or updated row in data table  112 . The row data, which are extracted from the speech recognition results, along with a table name and are provided as parameters. This routine must process the data to extract &lt;text, timestamp, confidence&gt; tuples and insert them into data table  112 . Speech indexing processing  114  then inserts the extracted tuples of information into index data structures associated. 
   In step  308 , speech query requestor  206  generates a query on the text data included in data table  112  and transmits the query to DBMS  102 . The generated query utilizes speech enhancements  108  to the query language used by DBMS  102 . In step  310 , DBMS  102  performs the query by accessing data table  112  and, using the index, retrieves the specified information, and returning the results of the query to speech query requester  106 . 
   Following is an exemplary description of a sample usage scenario that will demonstrate the power and ease of use of the speech indexing functionality provided by the present invention. 
   Imagine a scenario in which a customer wants to do the following:
         1. Upload media content including audio into DBMS  102 .   2. Process the audio by sending data to a previously started speech recognition engine  104  and store the results in DBMS  102 .   3. Create an index on the speech recognition results that will allow for sophisticated text querying capabilities.   4. Query the data to retrieve matched rows along with time offset and speech recognition confidence pairs for each occurrence within a matched row.       

   The customer stores media content including audio in data table  112  in DBMS  102 . An exemplary format of data table  112  is shown in FIG.  4 . Data table  112  includes id column  402 , audio data column  404 , and result column  406 . For each row of data in data table  112 , id column  402  includes a unique identifier if the data in the row, audio data column  404  includes the actual audio data, and result column  406  includes the speech recognition results. An example  500  of how an application would invoke speech recognition on a particular row and populate the result column  406  is shown in FIG.  5 . 
   After the application has processed each audio asset in data table  112  and populated the result column  406 , it is now ready to build an index on the result column, for example, using an SQL command  600 , such as that shown in FIG.  6 . For enhanced text queries that need to take into account customized preferences, such as lexer and wordlist preferences, the application can create preferences using the and pass those preferences as arguments to index creation, for example, using an SQL command  700 , such as that shown in FIG.  7 . 
   An example  800  of a simple query on the data table  112  is shown in FIG.  8 . An example  900  of a more sophisticated query that that retrieves confidence and timestamps for each occurrence within a matched audio asset row is shown in FIG.  9 . In this example, the SpeechContains operator matches those rows that satisfy the input query while the ancillary operator SpeechConfidenceTimestamp returns the corresponding collection of confidence/timestamp pairs for each returned row. 
   Format adapter  110  must be provided to adapt the format of the speech recognition result generated by speech recognition engine  104  to the format used for speech indexing. The formatting procedure must extract the information required for creating an index of the required indextype from the proprietary audio processing result format of speech recognition engine  104 . In one embodiment, when an index of the required indextype is created or updated, format adapter  110  is invoked for each new or updated row in the indexed table. The row data, which are processing results of SpcechMining, along with a table name and key to the original row in the indexed table, are provided as parameters. This routine must process the data to extract &lt;text, timestamp, confidence&gt; tuples. An example of the interface  100  to format adapter  110  is shown in FIG.  10 . An example of the processing  1100  performed by format adapter  110  is shown in FIG.  11 . 
   
     
       
             
           
             
           
             
             
           
             
             
           
             
           
             
           
             
           
             
           
             
           
             
             
           
             
           
             
           
             
           
             
           
             
           
             
             
           
             
           
             
           
             
             
           
         
             
               APPENDIX A 
             
             
                 
             
           
           
             
               OPERATOR: SpeechContains 
             
           
        
         
             
               Signature 
             
             
               SpeechContains(indexed_column CLOB, 
             
           
        
         
             
                 
               query_string VARCHAR2, 
             
             
                 
               [reference_label NUMBER]) 
             
           
        
         
             
                 
               RETURN NUMBER; 
             
           
        
         
             
               Description 
             
             
               Use the SpeechContains operator in the WHERE clause of a SELECT 
             
             
               statement to specify the query expression for a SpeechIndexing query. 
             
             
               SpeechContains returns a relevance score for every row selected. You 
             
             
               obtain this score with the SpeechScore operator. Additionally, 
             
             
               SpeechConfidenceTimestamp returns tuples of speech recognition 
             
             
               confidences and time offsets for the matches in the selected row. 
             
             
               Parameters 
             
             
               indexed_column: Specify the CLOB column to be searched on. This 
             
             
               column must have an ordsys.ORDSpeechIndex index associated with it. 
             
             
               query_string: Specify the query that defines your search in 
             
             
               indexed_column. Oracle Text query operators can be used in 
             
             
               this query string. 
             
             
               reference_label: Optionally specify the label that associates the 
             
             
               SpeechScore and SpeechConfidenceTimestamp generated by the 
             
             
               SpeechContains operator. 
             
             
               Returns 
             
             
               For each row selected, SpeechContains returns a number between 0 and 
             
             
               100 that indicates how relevant the document row is to the query. 
             
             
               The number 0 means that Oracle found no matches in the row. 
             
             
               Example 
             
             
               The following example searches for all documents in the 
             
             
               SpeechMining_result column that contain the word ‘oracle’. The score for 
             
             
               each row is selected with the SpeechScore operator using a label of 1: 
             
             
               SELECT ordsys.SpeechScore(1), title 
             
             
               FROM audionews 
             
             
               WHERE ordsys.SpeechContains(SpeechMining_result, 
             
             
               ‘oracle’, 1) &gt; 0; 
             
           
        
         
             
               OPERATOR: SpeechScore 
             
           
        
         
             
               Signature 
             
             
               SpeechScore(reference_label IN NUMBER) RETURN NUMBER; 
             
             
               Description 
             
             
               Use the SpeechScore operator in a SELECT statement to return the score 
             
             
               values produced by SpeechContains in an SpeechIndexing query. 
             
             
               Parameters 
             
             
               reference_label: An integer that refers to the corresponding invocation 
             
             
               of SpeechContains. If there are multiple invocations of SpeechContains in 
             
             
               the same query, this parameter is used to maintain the reference. 
             
             
               Notes 
             
             
               The SpeechScore operator can be used in a SELECT, ORDER BY, or 
             
             
               GROUP BY clause. 
             
             
               Returns 
             
             
               This operator returns a NUMBER. 
             
             
               Example 
             
             
               See the example for SpeechContains 
             
           
        
         
             
               OPERATOR: SpeechConfidenceTimestamp 
             
           
        
         
             
               Signature 
             
             
               SpeechConfidenceTimestamp(reference_label IN NUMBER) 
             
           
        
         
             
                 
               RETURN ordsys.ORDConfidenceTimestampTable; 
             
           
        
         
             
               Description 
             
             
               Use the SpeechCoinfidenceTimestamp operator in a SELECT 
             
             
               statement to return a collection of confidence and timestamp 
             
             
               pairs produced by SpeechContains in an SpeechIndexing query. 
             
             
               Parameters 
             
             
               reference_label: An integer that refers to the corresponding invocation 
             
             
               of SpeechContains. If there are multiple invocations of SpeechContains in 
             
             
               the same query, this parameter is used to maintain the reference. 
             
             
               Notes 
             
             
               The SpeechConfidenceTimestamp operator can be used in a SELECT 
             
             
               clause. 
             
             
               Returns 
             
             
               This operator returns a table of type 
             
             
               ordsys.ORDConfidenceTimestampTable (defined below). 
             
           
        
         
             
               INDEXTYPE: ORDSpeechIndex 
             
           
        
         
             
               Description 
             
             
               This indextype allows a user to create an audio index 
             
             
               on a CLOB column that contains the results of SpeechMining. 
             
             
               Parameters 
             
             
               parameter_string: Can be used to pass in Oracle Text preferences to the 
             
             
               underlying Oracle Text index. Note that datastore preferences 
             
             
               are disallowed. 
             
             
               The types below are used to retrieve speech recognition confidence and 
             
             
               timestamp values from the query into PL/SQL variables. 
             
           
        
         
             
               OBJECT ORDConfidenceTimestampTuple 
             
           
        
         
             
               CREATE TYPE ORDConfidenceTimestampTuple 
             
           
        
         
             
                 
               AS OBJECT (confidence NUMBER, timestamp NUMBER); 
             
           
        
         
             
               OBJECT ORDConfidenceTimestampTable 
             
           
        
         
             
               CREATE TYPE ORDConfidenceTimestampTable 
             
           
        
         
             
                 
               AS TABLE OF ORDConfidenceTimestampTuple;