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Tkinter Module. Network Programming with Python. Learn Web Scraping. More in Python Python Compiler. Java Core Java Tutorial. Java Type Conversion Examples. Java Wrapper Class. Java 8. Technically speaking, this cycle represents the recognition of a single Result. The result state system and result events are described in detail in Section 6. At this point the result is usually empty: it does not contain any recognized words.
As recognition proceeds words are added to the result along with other useful information. Applications will often make grammar changes during the result finalization because the result causes a change in application state or context. This buffering allows a user to continue speaking without speech data being lost. The commit applies all grammar changes made at any point up to the end of result finalization, such as changes made in the result finalization events. For applications that deal only with spoken input the state cycle described above handles most normal speech interactions.
For applications that handle other asynchronous input, additional state transitions are possible. Other types of asynchronous input include graphical user interface events e.
When a non-speech event occurs which changes the application state or application data it may be necessary to update the recognizer's grammars.
The suspend and commitChanges methods of a Recognizer are used to handle non- speech asynchronous events. The typical cycle for updating grammars in response to a non-speech asynchronous events is as follows. As soon as the event is received, the application calls suspend to indicate that it is about to change grammars.
The grammar changes affected by this event cycle and the pending commit are described in Section 6. Once all grammar changes are completed the application calls the commitChanges method. Finally, the Recognizer resumes recognition of the buffered audio and then live audio with the new grammars. The suspend and commit process is designed to provide a number of features to application developers which help give users the perception of a responsive recognition system.
The user has the perception of real-time processing. This minimizes the amount of data in the audio buffer and hence the amount of time it takes for the recognizer to "catch up". It also minimizes the possibility of a buffer overrun. Technically speaking, an application is not required to call suspend prior to calling commitChanges. If the suspend call is committed the Recognizer behaves as if suspend had been called immediately prior to calling commitChanges. However, an application that does not call suspend risks a commit occurring unexpectedly while it updates grammars with the effect of leaving grammars in an inconsistent state.
The three sub-state systems of an allocated recognizer shown in Figure normally operate independently. There are, however, some indirect interactions. When a recognizer is paused, audio input is stopped. However, recognizers have a buffer between audio input and the internal process that matches audio against grammars, so recognition can continue temporarily after a recognizer is paused. Eventually the audio buffer will empty. When the recognizer is resumed, it will have the focus and its grammars will be activated for recognition.
The focus state of a recognizer is very loosely coupled with the recognition state. A grammar defines what a recognizer should listen for in incoming speech.
Any grammar defines the set of tokens a user can say a token is typically a single word and the patterns in which those words are spoken. These grammars differ in how patterns of words are defined. They also differ in their programmatic use: a rule grammar is defined by an application, whereas a dictation grammar is defined by a recognizer and is built into the recognizer. A rule grammar is provided by an application to a recognizer to define a set of rules that indicates what a user may say.
Rules are defined by tokens, by references to other rules and by logical combinations of tokens and rule references. Rule grammars can be defined to capture a wide range of spoken input from users by the progressive combination of simple grammars and rules. A dictation grammar is built into a recognizer. It defines a set of words possibly tens of thousands of words which may be spoken in a relatively unrestricted way. Dictation grammars are closest to the goal of unrestricted natural speech input to computers.
Although dictation grammars are more flexible than rule grammars, recognition of rule grammars is typically faster and more accurate. As Section 4. A recognizer may have many rule grammars loaded at any time. However, the current Recognizer interface restricts a recognizer to a single dictation grammar. The technical reasons for this restriction are outside the scope of this guide. The Grammar interface is the root interface that is extended by all grammars.
The grammar functionality that is shared by all grammars is presented through this interface. The RuleGrammar interface is an extension of the Grammar interface to support rule grammars. The DictationGrammar interface is an extension of the Grammar interface to support dictation grammars. The Java Speech API supports dynamic grammars ; that is, it supports the ability for an application to modify grammars at runtime.
In the case of rule grammars any aspect of any grammar can be changed at any time. After making any change to a grammar through the Grammar , RuleGrammar or DictationGrammar interfaces an application must commit the changes.
This applies to changes in definitions of rules in a RuleGrammar , to changing context for a DictationGrammar , to changing the enabled state, or to changing the activation mode.
It does not apply to adding or removing a GrammarListener or ResultListener. Changes are committed by calling the commitChanges method of the Recognizer. The commit is required for changes to affect the recognition process: that is, the processing of incoming audio.
There is one instance in which changes are committed without an explicit call to the commitChanges method. Once processing of that event is completed changes are normally committed. This supports the common situation in which changes are often made to grammars in response to something a user says. The event-driven commit is closely linked to the underlying state system of a Recognizer. The state system for recognizers is described in detail in Section 6.
A grammar is active when the recognizer is matching incoming audio against that grammar to determine whether the user is saying anything that matches that grammar. When a grammar is inactive it is not being used in the recognition process. Applications to do not directly activate and deactivate grammars. Instead they provided methods for 1 enabling and disabling a grammar, 2 setting the activation mode for each grammar, and 3 requesting and releasing the speech focus of a recognizer as described in Section 6.
The enabled state of a grammar is set with the setEnabled method and tested with the isEnabled method. For programmers familiar with AWT or Swing, enabling a speech grammar is similar to enabling a graphical component.
Once enabled, certain conditions must be met for a grammar to be activated. The activation mode indicates when an application wants the grammar to be active. For each mode a certain set of activation conditions must be met for the grammar to be activated for recognition. The activation mode is managed with the setActivationMode and getActivationMode methods. The enabled flag and the activation mode are both parameters of a grammar that need to be committed to take effect.
As Section 6. Recognizer focus is a major determining factor in grammar activation and is relevant in computing environments in which more than one application is using an underlying recognition e. Recognizer focus is used to turn on and off activation of grammars. The roll of focus depends upon the activation mode. The three activation modes are described here in order from highest priority to lowest. An application should always use the lowest priority mode that is appropriate to its user interface functionality.
The current activation state of a grammar can be tested with the isActive method. An application may have zero, one or many grammars enabled at any time. Thus, an application may have zero, one or many grammars active at any time. As the conventions below indicate, well-behaved applications always minimize the number of active grammars.
However, when a Recognizer is paused, audio input to the Recognizer is turned off, so speech won't be detected. This is useful, however, because when the recognizer is resumed, recognition against the active grammars immediately and automatically resumes.
Activating too many grammars and, in particular, activating multiple complex grammars has an adverse impact upon a recognizer's performance. In general terms, increasing the number of active grammars and increasing the complexity of those grammars can both lead to slower recognition response time, greater CPU load and reduced recognition accuracy i.
Well-behaved applications adhere to the following conventions to maximize recognition performance and minimize their impact upon other applications:. A rule grammar is defined by a set of rules. These rules are defined by logical combinations of tokens to be spoken and references to other rules.
The references may refer to other rules defined in the same rule grammar or to rules imported from other grammars. Since the RuleGrammar interface extends the Grammar interface, a RuleGrammar inherits the basic grammar functionality described in the previous sections naming, enabling, activation etc. If multiple grammars must be loaded where a grammar references one or more imported grammars , importing by URL is most convenient.
The application must specify the base URL and the name of the root grammar to be loaded. If the demo grammar imports sub-grammars, they will be loaded automatically using the same location mechanism. This method creates an empty grammar with a specified grammar name.
Once a RuleGrammar has been loaded, or has been created with the newRuleGrammar method, the following methods of a RuleGrammar are used to create, modify and manage the rules of the grammar. The rule definitions of a RuleGrammar can be considered as a collection of named Rule objects. Each Rule object is referenced by its rulename a String. The different types of Rule object are described in Section 6. Unlike most collections in Java, the RuleGrammar is a collection that does not share objects with the application.
This is because recognizers often need to perform special processing of the rule objects and store additional information internally. The implication for applications is that a call to setRule is required to change any rule. The following code shows an example where changing a rule object does not affect the grammar. To ensure that the changed "green" token is loaded into the grammar, the application must call setRule again after changing the word to "green".
Furthermore, for either change to take effect in the recognition process, the changes need to be committed see Section 6. Complex systems of rules are most easily built by dividing the rules into multiple grammars. For example, a grammar could be developed for recognizing numbers. That grammar could then be imported into two separate grammars that defines dates and currency amounts.
Those two grammars could then be imported into a travel booking application and so on. This type of hierarchical grammar construction is similar in many respects to object oriented and shares the advantage of easy reusage of grammars.
An import declaration in JSGF and an import in a RuleGrammar are most similar to the import statement of the Java programming language. Unlike a " include" in the C programming language, the imported grammar is not copied, it is simply referencable. A full specification of import semantics is provided in the Java Speech Grammar Format specification. The RuleGrammar interface defines three methods for handling imports as shown in Table The resolve method of the RuleGrammar interface is useful in managing imports.
Given any rulename, the resolve method returns an object that represents the fully-qualified rulename for the rule that it references. A RuleGrammar is primarily a collection of defined rules. The programmatic rule structure used to control Recognizers follows exactly the definition of rules in the Java Speech Grammar Format. Any rule is defined by a Rule object. It may be any one of the Rule classes described Table The exceptions are the RuleParse class, which is returned by the parse method of RuleGrammar , and the Rule class which is an abstract class and the parent of all other Rule objects.
RuleName Rule that references another defined rule. JSGF example: green red yellow RuleCount Rule containing a sub-rule that may be spoken optionally, zero or more times, or one or more times. The following is an example of a grammar in Java Speech Grammar Format.
The "Hello World! Below we consider how to create the same grammar programmatically. The following code shows the simplest way to create this grammar. In advanced programs there is often a need to define rules using the set of Rule objects described above. To create a rule by code, the detailed structure of the rule needs to be understood.
The two alternatives are each sequences containing two items. In the first alternative, the brackets around the token "a" indicate it is optional. The code to construct this Grammar follows this code example is not compact - it is written for clarity of details. Grammars may be modified and updated. The changes allow an application to account for shifts in the application's context, changes in the data available to it, and so on.
This flexibility allows application developers considerable freedom in creating dynamic and natural speech interfaces.
For example, in an email application the list of known users may change during the normal operation of the program. This code snippet shows the update and commit of a change in users.
Committing grammar changes can, in certain cases, be a slow process. It might take a few tenths of seconds or up to several seconds. The time to commit changes depends on a number of factors. First, recognizers have different mechanisms for committing changes making some recognizers faster than others.
Second, the time to commit changes may depend on the extent of the changes - more changes may require more time to commit. Thirdly, the time to commit may depend upon the type of changes.
For example, some recognizers optimize for changes to lists of tokens e. Finally, faster computers make changes more quickly. The other factor which influences dynamic changes is the timing of the commit.
Parsing is the process of matching text to a grammar. Applications use parsing to break down spoken input into a form that is more easily handled in software. Parsing is most useful when the structure of the grammars clearly separates the parts of spoken text that an application needs to process.
Examples are given below of this type of structuring. The text may be in the form of a String or array of String objects one String per token , or in the form of a FinalRuleResult object that represents what a recognizer heard a user say. The RuleGrammar interface defines three forms of the parse method - one for each form of text.
The parse method returns a RuleParse object a descendent of Rule that represents how the text matches the RuleGrammar. The structure of the RuleParse object mirrors the structure of rules defined in the RuleGrammar.
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Here, we are going to discuss about the conversion of text to word file. The real problem is that how do i convert the text files into gzip file. Maven dependency for com. Learn to use robobo-speech version 0. Raidri your link is about how to convert a text to speech , right? Add a comment. Active Oldest Votes. Improve this answer. Sudantha Sudantha Sai Sunder Sai Sunder 1 1 gold badge 9 9 silver badges 16 16 bronze badges.
Check out this question. Community Bot 1 1 1 silver badge. Jimmy Collins Jimmy Collins 3, 5 5 gold badges 37 37 silver badges 57 57 bronze badges. Wasn't the question was "speech to text"? The user accepted it so I guess it must have helped - surely you have something better to do on a Sunday. Trying to find ways to convert mp3 to text : — Vineet Bhatia.
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