Title of Invention: SPEECH RECOGNITION METHOD AND APPARATUS BASED ON SPEAKER RECOGNITION Abstract: A speech recognition method and an apparatus which recognize speech, based on speaker recognition, and output a result of the speech recognition are provided. The speech recognition method includes activating a session for receiving an input of an audio signal, performing speech recognition on a speech signal detected from the input audio signal while the session is maintained, determining whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal, determining whether to maintain the session based on a result of the determination, and outputting a result of performing the speech recognition. Detailed Description: CROSS-REFERENCE TO RELATED APPLICATION(S) This application claims the benefit under 35 U.S.C. §119(a) of a Korean patent application filed on Aug. 31, 2016 in the Korean Intellectual Property Office and assigned Serial number 10-2016-0111690, the entire disclosure of which is hereby incorporated by reference. TECHNICAL FIELD The present disclosure relates to a speech recognition method and apparatus. More particularly, the present disclosure relates to a method and apparatus for recognizing speech based on speaker recognition, and outputting a result of the speech recognition when the speech is recognized in a speech recognition system. BACKGROUND Recently, since electronic devices such as smartphones that perform various functions have been developed, electronic devices having a speech recognition function embedded therein to improve manipulability have been released. The speech recognition function is advantageous in recognizing speech of a user without separate manipulation of a button or contact via a touch module, thereby allowing the user to easily control a device. Due to the speech recognition function, the user may execute a call function or write a text message without inputting separate buttons of a portable terminal such as a smartphone, and may easily set various functions such as navigation, internet search, alarm setting, or the like. The above information is presented as background information only, and to assist with an understanding of the present disclosure. No determination has been made, and no assertion is made, as to whether any of the above might be applicable as prior art with regard to the present disclosure. SUMMARY Aspects of the present disclosure are provided to address at least the above-mentioned problems and/or disadvantages, and to provide at least the advantages described below. Accordingly, an aspect of the present disclosure is to provide a speech recognition method and apparatus that determine whether to maintain a session, based on speaker recognition, thereby allowing sequential speech recognitions without an operation of separately activating the session upon utterance of a registered speaker. Another aspect of the present disclosure is to provide a speech recognition method and apparatus that output a result of performing speech recognition only on utterance of a registered speaker, based on speaker recognition, thereby providing a personalized speech recognition service to a user of the speech recognition apparatus. In accordance with another aspect of the present disclosure, a method of speech recognition is provided. The method includes activating a session for receiving an input of an audio signal, performing speech recognition on a speech signal detected from the input audio signal while the session is maintained, determining whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal, determining whether to maintain the session based on a result of the determination of whether the speaker of the speech signal is a registered speaker, and outputting a result of the speech recognition. In accordance with another aspect of the present disclosure, an apparatus for speech recognition is provided. The apparatus includes a receiver configured to receive an input audio signal while a session for receiving an input of one or more audio signals is maintained, a processor configured to detect a speech signal from the input audio signal, perform speech recognition on the speech signal, determine whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal, and determine whether to maintain the session based on a result of the determination of whether the speaker of the speech signal is a registered speaker, and an output unit configured to output a result of the speech recognition. In accordance with another aspect of the present disclosure, a server for speech recognition is provided. The server includes a receiver configured to receive an input audio signal from a speech recognition apparatus, the input audio signal being received by the receiver while a session for receiving an input of one or more audio signals is maintained, a processor configured to detect a speech signal from the input audio signal, perform speech recognition on the speech signal, determine whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal, and determine whether to maintain the session of the speech recognition apparatus based on a result of the determination of whether the speaker of the speech signal is a registered speaker, and an output unit configured to transmit, to the speech recognition apparatus, a session management signal for determining whether to maintain the session and a result of the speech recognition. In accordance with another aspect of the present disclosure, a non-transitory, computer-readable recording medium is provided having recorded thereon at least one program including instructions that, when executed by at least one processor, configure the at least one processor to execute a speech recognition method. The speech recognition method includes activating a session for receiving an input of an audio signal, performing speech recognition on a speech signal detected from the input audio signal while the session is maintained, determining whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal, determining whether to maintain the session based on a result of the determination of whether the speaker of the speech signal is a registered speaker, and outputting a result of the speech recognition. In accordance with another aspect of the present disclosure, a system for speech recognition is provided. The system includes a plurality of speech recognition apparatuses and a speech recognition server for controlling the plurality of speech recognition apparatuses, wherein a first speech recognition apparatus from among the plurality of speech recognition apparatuses is configured to receive an input audio signal while a session for receiving an input of one or more audio signals is maintained, and transmit the input audio signal to the speech recognition server, and wherein the speech recognition server is configured to detect a speech signal from the input audio signal, perform speech recognition on the speech signal, and determine whether a speaker of the speech signal is a registered speaker, based on speaker information generated from the speech signal, and control, when the speaker of the speech signal is the registered speaker, the plurality of speech recognition apparatuses to maintain sessions of the plurality of speech recognition apparatuses during a preset period. In accordance with another aspect of the present disclosure, a method of speech recognition is provided. The method includes activating a session for receiving an input of an audio signal, performing speech recognition on a plurality of speech signals detected from the input audio signal while the session is maintained, determining whether at least one speaker of the plurality of speech signals is a registered speaker based on speaker information generated from the plurality of speech signals, determining whether to maintain the session based on a result of the determination of whether the at least one speaker is a registered speaker, and outputting a result of the speech recognition. In accordance with another aspect of the present disclosure, an apparatus for speech recognition is provided. The apparatus includes a receiver to receive an input audio signal while a session for receiving an input of one or more audio signals is maintained, a processor to perform speech recognition on a plurality of speech signals detected from the input audio signal while the session is maintained, determine whether at least one speaker of the plurality of speech signals is a registered speaker based on speaker information generated from the plurality of speech signals, and determine whether to maintain the session based on a result of the determination of whether the at least one speaker is a registered speaker, and an output unit configured to output a result of the speech recognition. Other aspects, advantages, and salient features of the disclosure will become apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the annexed drawings, discloses various embodiments of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS The above and other aspects, features, and advantages of certain embodiments of the present disclosure will be more apparent from the following description taken in conjunction with the accompanying drawings, in which: FIG. 1 is a flowchart of a general speech recognition method according to an embodiment of the present disclosure; FIGS. 2A, 2B, 2C, and 2D illustrate a speech recognition system according to various embodiments of the present disclosure; FIGS. 3A and 3B are block diagrams of a speech recognition apparatus according to various embodiments of the present disclosure; FIG. 4 is a flowchart of a speech recognition method according to an embodiment of the present disclosure; FIG. 5 is a flowchart of a speech recognition method according to another embodiment of the present disclosure; FIG. 6 is a block diagram of a processor according to an embodiment of the present disclosure; FIG. 7 is a flowchart of a speech recognition method according to another embodiment of the present disclosure; FIG. 8 is a diagram for describing a method of performing speech recognition and generating speaker information performed by a speech recognition apparatus according to an embodiment of the present disclosure; FIG. 9 is a diagram for describing a method of performing normalization by using information of an adjacent frame for speaker recognition in real-time performed by a speech recognition apparatus according to an embodiment of the present disclosure; FIG. 10 is a diagram for describing a method of managing maintenance of a session and updating registered speaker information based on a result of speaker recognition performed by a speech recognition apparatus according to an embodiment of the present disclosure; FIGS. 11A, 11B, and 11C illustrate an example in which a speech recognition apparatus outputs a result of speech recognition according to various embodiments of the present disclosure; FIGS. 12A and 12B illustrate another example in which a speech recognition apparatus outputs a result of speech recognition according to various embodiments of the present disclosure; FIGS. 13A, 13B, and 13C illustrate another example in which a speech recognition apparatus outputs a result of speech recognition according to various embodiments of the present disclosure; FIGS. 14A, 14B, and 14C illustrate another example in which a speech recognition apparatus outputs a result of speech recognition according to various embodiments of the present disclosure; FIG. 15 is a flowchart of operations in a speech recognition system according to an embodiment of the present disclosure; FIG. 16 is a flowchart of operations in a speech recognition system according to an embodiment of the present disclosure; and FIGS. 17A and 17B illustrate examples in which a speech recognition system outputs a result of speech recognition according to various embodiments of the present disclosure. Throughout the drawings, like reference numerals will be understood to refer to like parts, components, and structures. DETAILED DESCRIPTION The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of various embodiments of the present disclosure as defined by the claims and their equivalents. It includes various specific details to assist in that understanding, but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the various embodiments described herein can be made without departing from the scope and spirit of the present disclosure. In addition, descriptions of well-known functions and constructions may be omitted for clarity and conciseness. The terms and words used in the following description and claims are not limited to the bibliographical meanings, but are merely used to enable a clear and consistent understanding of the present disclosure. Accordingly, it should be apparent to those skilled in the art that the following description of various embodiments of the present disclosure is provided for illustration purpose only, and not for the purpose of limiting the present disclosure as defined by the appended claims and their equivalents. It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a component surface” includes reference to one or more of such surfaces. Throughout the specification, it will also be understood that when an element is referred to as being “connected to” or “coupled with” another element, it can be directly connected to or coupled with the other element, or it can be electrically connected to or coupled with the other element by having an intervening element interposed therebetween. Also, when a part “includes” or “comprises” an element, unless there is a particular description contrary thereto, the part can further include other elements, not excluding the other elements. Throughout the specification, expressions such as “in some embodiments”, “in an embodiment”, or the like, do not necessarily indicate a same embodiment. Some embodiments may be described in terms of functional block components and various processing operations. Some or all of the functional blocks may be realized by any number of hardware and/or software components configured to perform the specified functions. For example, functional blocks of the present disclosure may be realized by one or more microprocessors, or circuit components for a predetermined function. In addition, for example, the functional blocks of the present disclosure may be implemented using any programming or scripting language. The functional blocks may also be implemented using algorithms that execute on one or more processors. Furthermore, the present disclosure could employ any number of techniques for electronics configuration, signal processing and/or control, data processing and the like, according to the related art. The terms such as “module” and “configuration” may be used broadly and are not limited to mechanical and/or physical embodiments. Furthermore, connecting lines or connectors between elements shown in drawings are intended to represent functional relationships and/or physical or logical couplings between the elements. It should be noted that many alternative or additional functional relationships, physical connections or logical connections may be present in a practical device. As used herein, the term “and/or” includes any and all combinations of one or more of the associated listed items. Expressions such as “at least one of,” when preceding a list of elements, modify the entire list of elements and do not modify the individual elements of the list. Hereinafter, the present disclosure will now be described more fully with reference to the accompanying drawings. FIG. 1 is a flowchart of a general speech recognition method according to an embodiment of the present disclosure. Referring to FIG. 1, in operation S110, a general speech recognition system may activate a session for receiving an input of an audio signal. The speech recognition system may activate the session based on a user input (e.g., an input of pressing, by a user, a physical start button, or an input of uttering a preset activation keyword). In operation S120, the general speech recognition system may detect a speech signal from the input audio signal while the session is activated. In operation S130, the general speech recognition system may perform speech recognition on the detected speech signal. When the session is activated and then the speech signal is detected from the input audio signal, the general speech recognition system may output a result of the speech recognition in operation S140, regardless of a speaker who uttered the speech, and may end the session in operation S150. The general speech recognition system ends the session by extracting, by using a speech detection algorithm, a point of time when the speech ends so that the general speech recognition system may end a session after each utterance. A reason why the general speech recognition system ends a session after each utterance is to perform speech recognition only on utterance for the speech recognition. If the general speech recognition system does not end the session even after the utterance is ended, the speech recognition may be performed on utterance not for the speech recognition or on noise. A user of the general speech recognition system has to perform an operation of activating a session so as to allow speech recognition to be performed on another utterance after the speech recognition is performed on the utterance. The user has to utter speech after the session is activated. When the session is activated again, the general speech recognition system may repeatedly perform operations S120 through S150 of FIG. 1. Thus, in order for the general speech recognition system to perform the speech recognition only on utterance that is a speech recognition target, the general speech recognition system has to activate a session before the utterance that is the speech recognition target is started, and end the session when the utterance that is the speech recognition target is ended. Therefore, in order to allow the general speech recognition system to sequentially perform the speech recognition, the user has the inconvenience of performing an operation of activating a session before every utterance. In addition, because the general speech recognition system outputs a speech recognition result regardless of a speaker, the general speech recognition system cannot perform personalized speech recognition. Thus, the general speech recognition system has a problem in that, when a particular speaker utters or after the particular speaker utters, a result of speech recognition that is also performed on content of utterance of another speaker is output. As described above, a general speech recognition system cannot sequentially perform speech recognition if the user does not perform an operation of activating a session for every utterance. Thus, the user has the inconvenience of performing the operation of activating a session for every utterance. In addition, a general speech recognition system may result in an error in a process of recognizing a session activation operation performed by the user. In the case where a general speech recognition system activates a session when a preset activation keyword is uttered, a decision of whether to drive the speech recognition system is affected according to a function of the general speech recognition system in recognizing the activation keyword. In order to solve these problems, it is possible to use a speech recognition system that does not instantly end a session after speech recognition is performed, but maintains the session. However, when the speech recognition system maintains the session, it is difficult for the speech recognition system to distinguish an input audio signal as utterance for a speech recognition target from noise that is not the speech recognition target, so that a speech recognition performance deteriorates. For example, when a plurality of speakers talk, the speech recognition system may perform speech recognition even on utterance of a speaker that is not the speech recognition target, so that the speech recognition performance deteriorates. In addition, when noise constantly occurs, the speech recognition system may determine utterance is continued without an end and may then constantly perform the speech recognition on the noise. If the speech recognition system repeatedly performs a speech detection operation and a speech recognition operation, the speech recognition system may also unnecessarily consume power or memory capacity. An embodiment for solving the problem of the speech recognition system that performs the speech recognition method of FIG. 1 may provide a speech recognition system that performs speech recognition based on speaker recognition. The speech recognition system according to an embodiment may initially activate a session, and even after utterance is ended, and the speech recognition system may sequentially perform speech recognition for a next utterance, without an additional operation of activating a session. In addition, the speech recognition system according to an embodiment may simultaneously perform speaker verification of verifying whether a speaker of an input utterance is a registered speaker and speech recognition on the input utterance, so that the speech recognition system may output only a result of the speech recognition with respect to an utterance of the registered speaker. Therefore, the speech recognition system according to an embodiment may allow personalized speech recognition. In addition, by performing the speech recognition based on the speaker recognition, the speech recognition system according to an embodiment may maintain a speech recognition session when the speaker of the input utterance is the registered speaker. Thus, the speech recognition system according to an embodiment may solve a problem of the speech recognition system that performs the speech recognition method of FIG. 1, including the problem being caused by repeatedly activating a session, and may provide a convenient usage environment to the user. FIGS. 2A, 2B, 2C, and 2D illustrate a speech recognition system according to various embodiments of the present disclosure. Referring to FIG. 2A, a speech recognition system according to an embodiment may include a speech recognition apparatus 210. For example, the speech recognition apparatus 210 may include, but is not limited to, a smartphone, a tablet personal computer (tablet PC), a PC, a smart television (smart TV), a mobile phone, a personal digital assistant (PDA), a laptop, a media player, a micro server, a global positioning system (GPS) device, an electronic book terminal, a digital broadcasting terminal, a navigation device, a kiosk, a Moving Picture Experts Group (MPEG-1 or MPEG-2) audio layer-3 (MP3) player, a digital camera, and mobile or non-mobile computing apparatuses. The speech recognition apparatus 210 according to the present embodiment may activate a session, may receive an input of an audio signal including a speech signal uttered by a speaker 10, and may perform speech recognition on the speech signal. The speech recognition apparatus 210 may then output a result of the speech recognition. Referring to FIG. 2B, a speech recognition system according to an embodiment may include a first speech recognition apparatus 221 and a second speech recognition apparatus 222. The first speech recognition apparatus 221 and the second speech recognition apparatus 222 may be connected to each other in a wired or wireless manner. For example, the second speech recognition apparatus 222 may include a mobile computing apparatus such as a smartphone, a tablet PC, a PC, a smart TV, or the like, and the first speech recognition apparatus 221 may include a wearable device, a smartphone, a tablet PC, a PC, or a smart TV which interoperates with the second speech recognition apparatus 222, but the present disclosure is not limited thereto. The second speech recognition apparatus 222 according to an embodiment may control an operation of the first speech recognition apparatus 221 and may share data with the first speech recognition apparatus 221. The second speech recognition apparatus 222 according to an embodiment may also transmit a control signal to the first speech recognition apparatus 221 to activate a session of the first speech recognition apparatus 221 to receive an input of an audio signal. The first speech recognition apparatus 221 may receive the input of the audio signal including the speech signal uttered by the speaker 10, and may transmit the input audio signal to the second speech recognition apparatus 222. Alternatively, the first speech recognition apparatus 221 may receive the input of the audio signal including the speech signal uttered by the speaker 10, and may transmit the speech signal detected from the input audio signal to the second speech recognition apparatus 222. Alternatively, the first speech recognition apparatus 221 may receive the input of the audio signal including the speech signal uttered by the speaker 10, and may transmit a characteristic of the speech signal detected from the input audio signal to the second speech recognition apparatus 222. The second speech recognition apparatus 222 may perform speech recognition based on a signal received from the first speech recognition apparatus 221. For example, the second speech recognition apparatus 222 may perform the speech recognition on the speech signal detected from the audio signal received from the first speech recognition apparatus 221. The second speech recognition apparatus 222 may then output a result of the speech recognition or may control the first speech recognition apparatus 221 to output the result of the speech recognition. Referring to FIG. 2C, a speech recognition system according to an embodiment may include a speech recognition apparatus 231 and a speech recognition server 232. The speech recognition apparatus 231 and the speech recognition server 232 may be connected to each other in a wired or wireless manner. The speech recognition server 232 according to an embodiment may share data with the speech recognition apparatus 231. The speech recognition apparatus 231 may activate a session, and may receive an input of an audio signal including a speech signal uttered by the speaker 10. The speech recognition apparatus 231 may transmit the input audio signal to the speech recognition server 232. Alternatively, the speech recognition apparatus 231 may transmit the speech signal detected from the input audio signal to the speech recognition server 232. Alternatively, the speech recognition apparatus 231 may transmit a characteristic of the speech signal detected from the input audio signal to the speech recognition server 232. The speech recognition server 232 may perform speech recognition based on a signal received from the speech recognition apparatus 231. For example, the speech recognition server 232 may perform the speech recognition on the speech signal detected from the audio signal received from the speech recognition apparatus 231. The speech recognition server 232 may also transmit a result of the speech recognition to the speech recognition apparatus 231. The speech recognition apparatus 231 may then output the result of the speech recognition. Referring to FIG. 2D, a speech recognition system according to an embodiment may include a first speech recognition apparatus 241, a second speech recognition apparatus 242, and a speech recognition server 243. The first speech recognition apparatus 241, the second speech recognition apparatus 242, and the speech recognition server 243 may be connected to each other in a wired or wireless manner. At least one of the first speech recognition apparatus 241 and the second speech recognition apparatus 242 may be a mobile computing device such as a smartphone, or may be an electronic product included in a home network system. The first speech recognition apparatus 241 and the second speech recognition apparatus 242 may be controlled in a remote manner via the speech recognition server 243, or may share data with each other. In more detail, the speech recognition server 243 may determine at least one of an activation, a maintenance, and an end of a session of the first speech recognition apparatus 241 and/or the second speech recognition apparatus 242, and may perform speech recognition on an audio signal received by the first speech recognition apparatus 241 and/or the second speech recognition apparatus 242. For example, the first speech recognition apparatus 241 according to an embodiment may activate a session, and may receive an input of an audio signal including a speech signal uttered by the speaker 10. The first speech recognition apparatus 241 may transmit information about the input audio signal to the speech recognition server 243. The information about the input audio signal may be the input audio signal, the speech signal detected from the input audio signal, and/or a characteristic of the speech signal detected from the input audio signal. The speech recognition server 243 may perform the speech recognition based on the information about the input audio signal received from the first speech recognition apparatus 241. The speech recognition server 243 may transmit a result of the speech recognition to at least one of the first speech recognition apparatus 241 and the second speech recognition apparatus 242. The speech recognition server 243 may control at least one of the first speech recognition apparatus 241 and the second speech recognition apparatus 242 to then output the result of the speech recognition. As illustrated in FIGS. 2A, 2B, 2C, and 2D, the speech recognition system according to embodiments may include at least one speech recognition apparatus and may further include a speech recognition server. Hereinafter, for convenience of description, a speech recognition method performed by the “speech recognition apparatus” will be described. However, hereinafter, some or all of operations of the speech recognition apparatus which are described below may be performed by the speech recognition server, or may be partially performed by a plurality of speech recognition apparatuses. FIGS. 3A and 3B are block diagrams of a speech recognition apparatus according to various embodiments of the present disclosure. Referring to FIG. 3A, a speech recognition apparatus 300 according to an embodiment may include a receiver 310, a processor 320, and an output unit 330. However, the speech recognition apparatus 300 may be embodied with more elements than the elements shown in FIG. 3A. For example, as illustrated in FIG. 3B, a speech recognition apparatus 300 according to an embodiment may further include a memory 340. For example, the speech recognition apparatus 300 according to an embodiment may be embodied to be included in at least one of an electronic product, a mobile computing device, and a server, or may be embodied to be connected to at least one of the electronic product, the mobile computing device, and the server in a wired or wireless manner. The receiver 310 may receive an audio signal. For example, the receiver 310 may directly receive the audio signal by converting external sound to electrical audio data by using a microphone. Alternatively, the receiver 310 may receive an audio signal transmitted by an external device. Referring to FIG. 3, the receiver 310 is included in the speech recognition apparatus 300, but the receiver 310 according to another embodiment may be included in a separate device and may be connected to the speech recognition apparatus 300 in a wired or wireless manner. The receiver 310 may activate a session for receiving an input of the audio signal by the control of the processor 320. The session may indicate a period during which the speech recognition apparatus 300 starts an operation of receiving the input of the audio signal and then ends the operation. The activation of the session may describe that the speech recognition apparatus 300 starts the operation of receiving the input of the audio signal. While the session is maintained, the receiver 310 may transmit the input audio signal to the processor 320. In addition, the receiver 310 may receive a user input of controlling the speech recognition apparatus 300. The receiver 310 may have a user input device including, but not limited to, a touch panel for receiving a user's touch, a button for receiving push manipulation by the user, a wheel for receiving rotation manipulation by the user, a keyboard, and a dome switch. The receiver 310 may not directly receive the user input but may receive a user input that is received by a separate user input device. For example, the receiver 310 may receive a user input of storing a particular speaker as a registered speaker, and a user input of activating a session. The processor 320 may detect a speech signal from the audio signal input through the receiver 310, and may perform speech recognition on the audio signal. In an embodiment, the processor 320 may extract a frequency characteristic of the speech signal from the input audio signal, and may perform the speech recognition by using one or more of an acoustic model and a language model. The frequency characteristic may indicate a distribution of frequency components of a sound input, where the frequency components are extracted by analyzing a frequency spectrum of the sound input. Thus, as illustrated in FIG. 3B, the speech recognition apparatus 300 may further include the memory 340 for storing a sound model and/or a language model. In an embodiment, the processor 320 may generate speaker information from the speech signal. For example, the processor 320 may generate the speaker information from a frequency characteristic of the speech signal by using at least one of states posteriors extracted from the sound model, a universal background model, and total variability conversion information. The processor 320 may determine, based on the speaker information, whether a speaker of the speech signal is a registered speaker. The processor 320 may decide whether to maintain the session based on a result of the determination. In an embodiment, the memory 340 of FIG. 3B may store at least one of the states posteriors, the universal background model, the total variability conversion information, and registered speaker information. The processor 320 may activate the session for receiving an input of the audio signal so as to perform the speech recognition. The processor 320 may also control maintenance or an end of the activated session. For example, the processor 320 may activate the session based on the user input, and may set the session to be maintained during a preset session maintenance period and then ended after the preset session maintenance period. In the case where a speaker of the speech signal detected from the input audio signal received while the session is activated is the registered speaker, the processor 320 may reset the session to be activated during a preset extended period and then ended after the extended period. The output unit 330 may output a result of performing the speech recognition on the speech signal. The output unit 330 may notify the user about the result of the speech recognition, or may transmit the result of the speech recognition to an external device (e.g., a smartphone, a smart TV, a smart watch, a server, and the like). For example, the output unit 330 may include a display capable of outputting an audio signal or a video signal. Alternatively, the output unit 330 may perform an operation that corresponds to the result of performing the speech recognition. For example, the speech recognition apparatus 300 may determine a function of the speech recognition apparatus 300, the function corresponding to the result of performing the speech recognition, and may output, via the output unit 330, an execution screen in which the function is being performed. Alternatively, the speech recognition apparatus 300 may transmit, to an external server, a keyword corresponding to the result of performing the speech recognition, may receive information about the transmitted keyword from the external server, and may output the information to a screen via the output unit 330. The block diagrams illustrated in FIGS. 3A and 3B may also be applied to a speech recognition server. The speech recognition server according to an embodiment may include a receiver that receives an input audio signal from a speech recognition apparatus. The speech recognition server may be connected to the speech recognition apparatus in a wired or wireless manner. The input audio signal received by the receiver of the speech recognition server might have been received by the speech recognition apparatus while a session for receiving an input of the audio signal is activated. The speech recognition server may include a processor and an output unit, and may further include a memory. The processor of the speech recognition server may detect a speech signal from the input audio signal, and may perform speech recognition on the speech signal. The processor of the speech recognition server may determine whether a speaker of the speech signal is a registered speaker based on speaker information generated from the speech signal. The processor of the speech recognition server may determine whether to maintain the session of the speech recognition apparatus based on a result of the determination. The output unit of the speech recognition server may transmit, to the speech recognition apparatus, a session management signal for determining whether to maintain the session and a result of performing the speech recognition. The speech recognition apparatus may output the result of performing the speech recognition, where the result is received from the speech recognition server. Hereinafter, an operating method by the speech recognition apparatus 300 will now be described in detail. Each operation of a method described below may be performed by each of the aforementioned elements of the speech recognition apparatus 300. For convenience of description, it is assumed that the speech recognition apparatus 300 is a subject of the operations, but the descriptions below may also be applied to a case in which a speech recognition server is a subject of the operations. FIG. 4 is a flowchart of a speech recognition method according to an embodiment of the present disclosure. In operation S410, the speech recognition apparatus 300 may activate a session for receiving an input of an audio signal. The session may indicate a period during which the speech recognition apparatus 300 starts an operation of receiving the input of the audio signal and then ends the operation. The activation of the session may describe that the speech recognition apparatus 300 starts the operation of receiving the input of the audio signal. The speech recognition apparatus 300 may set the session to be maintained during a preset session maintenance period and then ended after the preset session maintenance period. While the session is maintained, the speech recognition apparatus 300 may receive the input of the audio signal. In addition, while the session is maintained, the speech recognition apparatus 300 may perform the operation of receiving the input of the audio signal and may also perform an operation of processing the input audio signal. For example, while the session is maintained, the speech recognition apparatus 300 may perform at least one of operations S420 through S450 illustrated in FIG. 4. In operation S420, the speech recognition apparatus 300 may perform speech recognition. The speech recognition apparatus 300 may detect a speech signal from the audio signal that is input while the session is maintained, and may perform the speech recognition on the detected speech signal. In an embodiment, the speech recognition apparatus 300 may segment the audio signal that is input in real-time into frame units each having a preset length, and may process the audio signal that is segmented into the frame units. A speech signal in frame units may then be detected from the audio signal that is segmented into the frame units. In an embodiment, the speech recognition apparatus 300 may extract, from the speech signal, a speech recognition feature vector which is for robust speech recognition, and a speaker recognition feature vector which is for robust speaker recognition. The speech recognition apparatus 300 may convert the speech signal in a time domain to a signal in a frequency domain, and may differently change frequency energy of the converted signal, thereby extracting the speech recognition feature vector and the speaker recognition feature vector. For example, the speech recognition feature vector and the speaker recognition feature vector may be mel-frequency cepstral coefficients (MFCC) or filter bank energy, but embodiments are not limited thereto and thus, a feature vector may be extracted from a speech signal in various manners. In an embodiment, the speech recognition apparatus 300 may perform speech recognition on the speech recognition feature vector, thereby generating a result of performing the speech recognition. The speech recognition apparatus 300 may perform the speech recognition on the speech recognition feature vector based on one or more of an acoustic model and a language model. The speech recognition apparatus 300 may perform the speech recognition, thereby extracting text assumed to have been uttered by a speaker of the speech signal. In an embodiment, the speech recognition apparatus 300 may generate speaker information by using the speech recognition feature vector. For example, the speech recognition apparatus 300 may extract states posteriors, based on one or more of the acoustic model and the speech recognition feature vector, and may generate the speaker information by using the states posteriors and the speech recognition feature vector. In an embodiment, the speech recognition apparatus 300 may calculate a vector matrix including the speaker information by further using one or more of total variability conversion information and a universal background model in addition to the speech recognition feature vector and the states posteriors. In an embodiment, the speech recognition apparatus 300 may simultaneously perform the speech recognition and the generation of the speaker information. In more detail, the speech recognition apparatus 300 may perform the speech recognition on the speech signal extracted by frame units in real-time and may generate the speaker information. The speech recognition apparatus 300 may perform the speech recognition on a first frame of the speech signal, and may extract states posteriors about the first frame while the speech recognition is performed on the first frame. The speech recognition apparatus 300 may then generate speaker information about the first frame by using the states posteriors about the first frame. In an embodiment, the speech recognition apparatus 300 may repeatedly perform an operation of the speech recognition and an operation of generating speaker information on each of the frames of the speech signal which are sequentially detected from the audio signal that is input in real-time. In operation S430, the speech recognition apparatus 300 may determine whether the speaker of the speech signal is a registered speaker. The speech recognition apparatus 300 may determine whether the speaker of the speech signal is the registered speaker based on the speaker information generated from the speech signal. The registered speaker may be a main user of the speech recognition apparatus 300, but embodiments are not limited thereto. For example, when the speech recognition apparatus 300 is a smartphone, an owner of the smartphone may be the registered speaker. The speech recognition apparatus 300 may register a speaker based on a user input, or may store a predetermined speaker that is a default value as the registered speaker. The speech recognition apparatus 300 may store one speaker as the registered speaker or may store a plurality of speakers as registered speakers. In an embodiment, the speech recognition apparatus 300 may store a speech characteristic of a specific speaker as registered speaker information. For example, before a session is activated, the speech recognition apparatus 300 may previously extract and store the registered speaker information from feature vectors extracted from a plurality of speech signals uttered by the specific speaker. In an embodiment, the speech recognition apparatus 300 may calculate a similarity between the pre-stored registered speaker information and newly-generated speaker information. The speech recognition apparatus 300 may determine whether the speaker of the speech signal is the registered speaker based on a result of comparing the calculated similarity with a predetermined threshold value. Referring to FIG. 4, operation S430 is performed after operation S420 is performed, but embodiments are not limited thereto. The operation of performing the speech recognition in operation S420 and the operation of determining whether the speaker of the speech signal is the registered speaker in operation S430 may be sequentially performed or may be simultaneously performed in a parallel manner. In operation S440, the speech recognition apparatus 300 may determine whether to maintain the session based on a result of the determination in operation S430. In an embodiment, the speech recognition apparatus 300 may determine whether to maintain or end the session based on whether the speaker of the speech signal is the registered speaker. The speech recognition apparatus 300 that is set to end the session after the session maintenance period elapses in operation S410 may reset the session to be further maintained when the speech recognition apparatus 300 determines that the speaker of the speech signal is the registered speaker in operation S430. For example, when the speaker of the speech signal is the registered speaker, the speech recognition apparatus 300 may maintain the session. When the speaker of the speech signal is the registered speaker, the speech recognition apparatus 300 may set the session to be maintained during a preset extended period and then ended after the extended period. In an embodiment, when the speaker of the speech signal is not the registered speaker, the speech recognition apparatus 300 may end the session. For example, when the speech recognition apparatus 300 determines that the speaker of the speech signal is not the registered speaker, the speech recognition apparatus 300 may instantly end the session or may set the session to be ended after the session maintenance period that is set in operation S410 elapses. In operation S450, the speech recognition apparatus 300 may output a result of the speech recognition performed in operation S420. When the speaker of the speech signal is the registered speaker, the speech recognition apparatus 300 may output the result of performing the speech recognition. For example, the speech recognition apparatus 300 may output text as the result of the speech recognition, the result being extracted from the speech signal by performing the speech recognition on the speech signal. In an embodiment, in a case where speech signals are non-continuously extracted or are extracted at regular intervals while the session is maintained, the speech recognition apparatus 300 may output the text as the result of the speech recognition in a sentence unit. The result of the speech recognition which is output in a sentence unit may include text extracted from a plurality of speech signals. When a time interval between the speech signals is longer than a threshold time, the speech recognition apparatus 300 may determine that one sentence has been completed. For example, as illustrated in FIG. 12A, a case where a speaker A utters “Can you show me the way”, and then utters, after a brief pause, “to Gangnam station?”, will be described. The speech recognition apparatus 300 may compare a threshold time with the brief pause with respect to the utterance. In a case where a speech signal including “Can you show me the way” and a speech signal including “to Gangnam station?” are detected one after the other and having a pause shorter than the threshold time, the speech recognition apparatus 300 may determine that the speech signals comprise one sentence. The speech recognition apparatus 300 may determine then, as one sentence, text that is extracted from a combination of the speech signals and includes “Can you show me the way to Gangnam station?”, and may output a result of performing the speech recognition on the text. In an embodiment, the speech recognition apparatus 300 may perform natural language processing on the result of performing the speech recognition. The speech recognition apparatus 300 may perform natural language processing on the text assumed to have been uttered by the speaker. The speech recognition apparatus 300 may also recognize intention of the utterance by the speaker by performing natural language processing. The speech recognition apparatus 300 performs natural language processing on the result of performing the speech recognition, thereby determining whether the speech signals were uttered for the purpose of speech recognition by the speaker. In an embodiment, the speech recognition apparatus 300 may also perform natural language processing on a result of performing the speech recognition on a previous speech signal detected while the session is maintained. The speech recognition apparatus 300 performs natural language processing on the result of performing the speech recognition on the previous speech signal (hereinafter, referred to as the previous speech recognition result), and a result of performing the speech recognition on a current speech signal (hereinafter, referred to as the current speech recognition result), thereby determining whether the current speech signal has been uttered for the purpose of speech recognition by the speaker. When a correlation between the previous speech recognition result and the current speech recognition result is high, the speech recognition apparatus 300 may determine that the speaker has uttered the current speech signal so as to perform the speech recognition. In an embodiment, the speech recognition apparatus 300 may analyze, by performing natural language processing, a meaning of a first text extracted from the previous speech signal and a meaning of a second text extracted from the current speech signal. To analyze the meaning of text includes, but is not limited to, recognizing intention associated with a sentence, i.e., whether the speaker asks a question, whether the speaker makes a request, or whether the speaker simply expresses his/her feelings, or may indicate determining a category of the question or the request. Alternatively, to analyze the meaning of text includes extracting at least one keyword from the text. In an embodiment, the speech recognition apparatus 300 may calculate a correlation between the first text and the second text based on the meanings of the first text and the second text. For example, the speech recognition apparatus 300 compares the calculated correlation with a predetermined threshold value, thereby determining whether the speaker has uttered the current speech signal so as to perform the speech recognition. When a correlation between the
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