[attachment=1403]Submitted by:
Speech Recognition
Aditi.P
Swathi.Ch
Abstract:
Language is man's most important means of communication and speech its primary medium. Speech provides an international forum for communication among researchers in the disciplines that contribute to our understanding of the production, perception, processing, learning and use. Spoken interaction both between human interlocutors and between humans and machines is inescapably embedded in the laws and conditions of Communication, which comprise the encoding and decoding of meaning as well as the mere transmission of messages over an acoustical channel. Here we deal with this interaction between the man and machine through synthesis and recognition applications. The paper dwells on the speech technology and conversion of speech into analog and digital waveforms which is understood by the machines Speech recognition, or speech-to-text, involves capturing and digitizing the sound waves, converting them to basic language units or phonemes, constructing words from phonemes, and contextually analyzing the words to ensure correct spelling for words that sound alike. Speech Recognition is the ability of a computer to recognize general, naturally flowing utterances from a wide variety of users. It recognizes the caller's answers to move along the flow of the call. We have emphasized on the modeling of speech units and grammar on the basis of Hidden Markov Model. Speech Recognition allows you to provide input to an application with your voice. The applications and limitations on this subject has enlightened us upon the impact of speech processing in our modern technical field. While there is still much room for improvement, current speech recognition systems have remarkable performance. We are only humans, but as we develop this technology and build remarkable changes we attain certain achievements. Rather than asking what is still deficient, we ask instead what should be done to make it efficient¦.
INTRODUCTION
One of the most important inventions of the nineteenth century was the telephone. Then at the midpoint of twentieth century, the invention of the digital computer amplified the power of our minds, enabled us to think and work more efficiently and made us more imaginative then we could ever have imagined .now several new technologies have empowered us to teach computers to talk to us in our native languages and to listen to us when we speak(recognition); haltingly computers have begun to understand what we say. Having given our computers both oral and aural abilities, we have been able to produce innumerable computer applications that further enhance our productivity. Such capabilities enable us to route phone calls automatically and to obtain and update computer based information by telephone, using a group of activities collectively referred to as Voice Processing.
SPEECH TECHNOLOGY
Three primary speech technologies are used in voice processing applications: stored speech, text-to “ speech and speech recognition . Stored speech involves the production of computer speech from an actual human voice that is stored in a computer™s memory and used in any of several ways. Speech can also be synthesized from plain text in a process known as text-to “ speech which also enables voice processing applications to read from textual database.

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Speech Recognition


Introduction

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Speech Recognition

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Sub mitted by
Speech Recognition
Aditi.P
Swathi.Ch

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Introduction

What is Speech Recognition?
- Voice Recognition?
Where can it be used?
- Dictation
- System control/navigation
- Commercial/Industrial applications
- Hand held digital recorders

Abstract:
Language is man's most important means of communication and speech its
primary medium. Speech provides an international forum for
communication among researchers in the disciplines that contribute to
our understanding of the production, perception, processing, learning
and use. Spoken interaction both between human interlocutors and
between humans and machines is inescapably embedded in the laws and
conditions of Communication, which comprise the encoding and decoding
of meaning as well as the mere transmission of messages over an
acoustical channel. Here we deal with this interaction between the
man and machine through synthesis and recognition applications.
The paper dwells on the speech technology and conversion of speech into
analog and digital waveforms which is understood by the machines
Speech recognition, or speech-to-text, involves capturing
and digitizing the sound waves, converting them to basic language units
or phonemes, constructing words from phonemes, and contextually
analyzing the words to ensure correct spelling for words that sound
alike. Speech Recognition is the ability of a computer to recognize
general, naturally flowing utterances from a wide variety of users. It
recognizes the caller's answers to move along the flow of the call.
We have emphasized on the modeling of speech units
and grammar on the basis of Hidden Markov Model. Speech Recognition
allows you to provide input to an application with your voice. The
applications and limitations on this subject has enlightened us upon
the impact of speech processing in our modern technical field.
While there is still much room for improvement, current speech
recognition systems have remarkable performance. We are only humans,
but as we develop this technology and build remarkable changes we
attain certain achievements. Rather than asking what is still
deficient, we ask instead what should be done to make it efficient¦.

Vicki Wassenhove
Quad-Cities Computer Society
June 10th, 2009

Using Speech Recognition

Why use Speech Recognition?


-Today’s improved technology
-Three times faster than typing
-Hands-free computer use
-No more spelling mistakes!

-And… It’s just fun!

For more information about this article,please follow the link:
http://googleurl?sa=t&source=web&cd=8&ve...g%2FSR.pps&ei=RrmpTMiRNYPovQOkhI3nDA&usg=AFQjCNFsmOVLnBBgvGi6b3BU40-4ZKQDvg

[attachment=5034]
Speech Recognition
Abstract:
Language is man's most important means of communication and speech its primary medium. Speech provides an international forum for communication among researchers in the disciplines that contribute to our understanding of the production, perception, processing, learning and use. Spoken interaction both between human interlocutors and between humans and machines is inescapably embedded in the laws and conditions of Communication, which comprise the encoding and decoding of meaning as well as the mere transmission of messages over an acoustical channel. Here we deal with this interaction between the man and machine through synthesis and recognition applications. The paper dwells on the speech technology and conversion of speech into analog and digital waveforms which is understood by the machines Speech recognition, or speech-to-text, involves capturing and digitizing the sound waves, converting them to basic language units or phonemes, constructing words from phonemes, and contextually analyzing the words to ensure correct spelling for words that sound alike. Speech Recognition is the ability of a computer to recognize general, naturally flowing utterances from a wide variety of users. It recognizes the caller's answers to move along the flow of the call. We have emphasized on the modeling of speech units and grammar on the basis of Hidden Markov Model. Speech Recognition allows you to provide input to an application with your voice. The applications and limitations on this subject has enlightened us upon the impact of speech processing in our modern technical field. While there is still much room for improvement, current speech recognition systems have remarkable performance. We are only humans, but as we develop this technology and build remarkable changes we attain certain achievements. Rather than asking what is still deficient, we ask instead what should be done to make it efficient¦.
INTRODUCTION
One of the most important inventions of the nineteenth century was the telephone. Then at the midpoint of twentieth century, the invention of the digital computer amplified the power of our minds, enabled us to think and work more efficiently and made us more imaginative then we could ever have imagined .now several new technologies have empowered us to teach computers to talk to us in our native languages and to listen to us when we speak(recognition); haltingly computers have begun to understand what we say. Having given our computers both [censored] and aural abilities, we have been able to produce innumerable computer applications that further enhance our productivity. Such capabilities enable us to route phone calls automatically and to obtain and update computer based information by telephone, using a group of activities collectively referred to as Voice Processing.
SPEECH TECHNOLOGY
Three primary speech technologies are used in voice processing applications: stored speech, text-to “ speech and speech recognition . Stored speech involves the production of computer speech from an actual human voice that is stored in a computer™s memory and used in any of several ways. Speech can also be synthesized from plain text in a process known as text-to “ speech which also enables voice processing applications to read from textual database.

Reference: http://studentbank.in/report-speech-reco...z11SsgoFzR

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THE TECHNOLOGY OF COMPUTER SPEECH RECOGNITION


ARTIFICIAL INTELLIGENCE

Type equation here.
INTRODUCTION
Artificial Intelligence (AI), the study and engineering of intelligent machines capable of performing the same kinds of functions that characterize human thought. The concept of AI dates from ancient times, but the advent of digital computers in the 20th century brought AI into the realm of possibility. AI was conceived as a field of computer science in the mid-1950s. The term AI has been applied to computer programs and systems capable of performing tasks more complex than straightforward programming, although still far from the realm of actual thought. While the nature of intelligence remains elusive, AI capabilities currently have far-reaching applications in such areas as information processing, computer gaming, national security, electronic commerce, and diagnostic systems

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SPEECH-RECOGNITION AND SPEECH SYNTHESIS
1. ABSTRACT
Astronauts exploring Moon will probably want to use computers in the field for many purposes including communication such as e- mail, information retrieval, and command and control of both their spacesuit and off- suit equipment. Traditional computer systems present many difficulties in the field including the difficulty of operating a keyboard wearing a spacesuit and the effect of pervasive dust and extreme conditions on equipment. Speech-recognition and speech synthesis have been proposed as partial solutions for these problems.
Methods for creating a controlled acoustic environment in a spacesuit so that current large vocabulary, speaker-dependent speech-recognition can be used reliably are discussed. Display options such as in-helmet displays, external projectors, and external flat screens are discussed. The advantages and challenges of in-helmet displays are detailed. Pointing devices such as trackballs and motion sensors that can be integrated into a spacesuit are discussed for operating graphical applications and traditional graphical user interfaces. User interface and operating system design with no keyboard, no mouse, and no traditional graphical user interface is discussed.
Partitioning applications between fast, high reliability physical input devices -- switches, buttons, motion and pointing sensors -- and slower, less reliable, more flexible and versatile speech input is discussed. In general, mission-critical and life-support functions will use physical inputs. Lower priority and support functions such as e- mail, database query, and non-essential equipment control will use speech. What can and cannot be done in space exploration applications with current accuracy large vocabulary speech-recognition (about 95% accurate) is discussed. Some strategies to increase accuracy such as incorporating syntactic and semantic rules are discussed.
2. INTRODUCTION
The planet Mars has been proposed as the next major step in the human exploration of space after the Moon. Mars has a diameter of 4219 miles. Mars has a surface area of 144 million square kilometers, about the same as all the continents and islands of earth put together. This is about 28% of total surface area of the Earth -- including the oceans. The surface gravity of Mars is 38% of the surface gravity on Earth. Mars traverses a slightly elliptical orbit around the sun ranging from 128,000,000 miles to 155,000,000 miles from the Sun. Mars has an axial tilt of 25.2°. The Martian day is 24 hours and 37 minutes. The Martian year is 687 days.
The average surface temperature of Mars is -85°F. The Martian atmosphere is about 1% he atmospheric pressure at sea level on Earth. It is comparable in density and pressure to he atmosphere on Earth at an altitude of 100,000 feet. The Martian atmosphere is 95% carbon dioxide, 3% nitrogen, and 2% other gasses. Mars receives about half the sunlight hat the Earth receives. However, lacking the Earth's heavy atmosphere and ozone layer, ars receives more ultraviolet light than the Earth at its surface. Mars lacks the global magnetic field that protects the Earth from cosmic rays.
Current proposals for humans to Mars usually involve a lengthy mission using chemical ockets1. About 180 days will be spent traveling from Earth to Mars. Often, a lengthy tay, such as 550 days, on the planet Mars is envisioned. An additional 180 days will be spent traveling back from Mars to Earth.
3. Goals for the Human Exploration of Mars
Goals for the human exploration of Mars include the search for past or present life on the planet. Astronauts will also seek resources, especially easily exploitable resources. Possible resources include mineral deposits (especially surface mineral deposits), water, and methane. Recent observations have produced evidence of subsurface water or ice on Mars. Trace amounts of methane have recently been reported in the Martian atmosphere. On Earth, most methane is attributed to past or present life. Methane is the principal ingredient of natural gas on Earth. Methane is both a fuel and a precursor to plastics and other materials in industrial processes. Methane can also be used as rocket fuel. As fluids, both water and methane do not require extensive heavy mining equipment to exploit on Mars.
Surface features of interest in the exploration of Mars include OphirChasma, Juventae Chasma, Hebes Chasma, Kasei Vallis, and the Viking 1 landing site, and many other locations on the planet. A thorough exploration of the planet will require that the astronauts visit many locations separated by thousands of kilometers, using a vehicle such as a rover or rocket plane.

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prepared by:
Aditi.P
Swathi.Ch

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[attachment=9846]
Abstract:
Language is man's most important means of communication and speech its primary medium. Speech provides an international forum for communication among researchers in the disciplines that contribute to our understanding of the production, perception, processing, learning and use. Spoken interaction both between human interlocutors and between humans and machines is inescapably embedded in the laws and conditions of Communication, which comprise the encoding and decoding of meaning as well as the mere transmission of messages over an acoustical channel. Here we deal with this interaction between the man and machine through synthesis and recognition applications.
The paper dwells on the speech technology and conversion of speech into analog and digital waveforms which is understood by the machines
Speech recognition, or speech-to-text, involves capturing and digitizing the sound waves, converting them to basic language units or phonemes, constructing words from phonemes, and contextually analyzing the words to ensure correct spelling for words that sound alike. Speech Recognition is the ability of a computer to recognize general, naturally flowing utterances from a wide variety of users. It recognizes the caller's answers to move along the flow of the call.
We have emphasized on the modeling of speech units and grammar on the basis of Hidden Markov Model. Speech Recognition allows you to provide input to an application with your voice. The applications and limitations on this subject has enlightened us upon the impact of speech processing in our modern technical field.
While there is still much room for improvement, current speech recognition systems have remarkable performance. We are only humans, but as we develop this technology and build remarkable changes we attain certain achievements. Rather than asking what is still deficient, we ask instead what should be done to make it efficient….
INTRODUCTION
One of the most important inventions of the nineteenth century was the telephone. Then at the midpoint of twentieth century, the invention of the digital computer amplified the power of our minds, enabled us to think and work more efficiently and made us more imaginative then we could ever have imagined .now several new technologies have empowered us to teach computers to talk to us in our native languages and to listen to us when we speak(recognition); haltingly computers have begun to understand what we say. Having given our computers both oral and aural abilities, we have been able to produce innumerable computer applications that further enhance our productivity. Such capabilities enable us to route phone calls automatically and to obtain and update computer based information by telephone, using a group of activities collectively referred to as Voice Processing.
SPEECH TECHNOLOGY
Three primary speech technologies are used in voice processing applications: stored speech, text-to – speech and speech recognition . Stored speech involves the production of computer speech from an actual human voice that is stored in a computer’s memory and used in any of several ways.
Speech can also be synthesized from plain text in a process known as text-to – speech which also enables voice processing applications to read from textual database.
Speech recognition is the process of deriving either a textual transcription or some form of meaning from a spoken input.
Speech analysis can be thought of as that part of voice processing that converts human speech to digital forms suitable for transmission or storage by computers.
Speech synthesis functions are essentially the inverse of speech analysis – they reconvert speech data from a digital form to one that’s similar to the original recording and suitable for playback.
Speech analysis processes can also be referred to as a digital speech encoding ( or simply coding) and
DIGITIZATION OF ANALOG WAVEFORMS
Two processes are required to digitize an analog signal:
(a) Sampling which discretizes the signal in time
(b) Quantizing, which discretizes the signal in amplitude.
ANALYSIS/SYNTHESIS IN THE TIME AND FREQUENCY DOMAIN
The analog and digital speech waveforms exist in time domain; the waveform represents speech as amplitude versus time. The time –domain sound pressure wave emanating from the lips is easily converted by microphone to a speech waveform, so it’s natural that speech analysis/synthesis systems operate directly upon this waveform. The objective of every speech-coding scheme is to produce code of minimum data rate so that a synthesizer can reconstruct an accurate facsimile of the original speech waveform. Frequency domain coders attempt to reach this objective by exploiting the resonant characteristics of the vocal tract.
VOCODERS – Voice Coders
RELP – Residual–excited linear production
SBC – Subband Coding
CVSD- Continously variable slope deltmodulation
ADM - Adaptive Delta Modulation
ADPCM – Adaptive Quantization
LOG PCM – Logarithmic Quantization
Figure summarizes the relative voice quality of various speech coders. Voice quality is measured in terms of signal-to-noise ratio on the y-axis versus data rate as a logarithmic scale on the x-axis. Both solid and dashed traces appear in the figure and respectively represent objective and estimated results- all of which are approximations.
SPEECH RECOGNITION
Speech recognition is the process of deriving either a textual transcription or some form of meaning from a spoken input. Speech recognition is the inverse process of synthesis, conversion of speech to text. The Speech recognition task is complex. This involves the computer taking the user's speech and interpreting what has been said. This allows the user to control the computer (or certain aspects of it) by voice, rather than having to use the mouse and keyboard, or alternatively just dictating the contents of a document. It would be complicated enough if every speaker pronounced every word in an identical manner each time, but this doesn’t happen

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-: SPEECH RECOGNITION :-
Introduction
One don’t have to be a scientist to know that the computer of the future will talk, listen and understand. One of them is the Apple Macintosh of today. Apple’s Speech Recognition and Speech Synthesis Technologies now give speech-savvy applications the power to carry out your voice commands and even speak back to you in plain English.
Apple Speech Recognition lets the system (Macintosh) understand what you say, giving you a new dimension for interacting with and controlling your computer by voice. You don’t even have to train it to understand your voice, because it already understands you, from your very first word. You can speak naturally, without pausing or stopping. Apple’s leadership in speech recognition technology makes it possible by bringing a whole new dimension to the user interface: speech. Combined with Voice-Over, speech synthesis will help turn the graphical user interface into a vocal user interface.
Speech recognition (in many contexts also known as 'automatic speech recognition', computer speech recognition or erroneously as Voice Recognition) is the process of converting a speech signal to a sequence of words, by means of an algorithm implemented as a computer program. Speech recognition applications that have emerged over the last years include voice dialing (e.g., Call home), call routing (e.g., I would like to make a collect call), simple data entry (e.g., entering a credit card number), and preparation of structured documents (e.g., a radiology report).
Voice Verification or speaker recognition is a related process that attempts to identify the person speaking, as opposed to what is being said.
Speech Technology Development at IBM:
The overall view, with emphasis on Via-Scribe and Accessibility
 Speech technologies – development, deployments
 Speech Analytics: Automated Quality Assurance Application
• Monitor 100% of calls
• Download recorded calls daily from across North America
• Answer questions and assign default ratings
• Provide a ranked list to human monitors to focus on bad calls
Speech recognition is the process of converting an acoustic signal, captured by a microphone or a telephone, to a set of words. The recognized words can be the final results, as for applications such as commands & control, data entry, and document preparation. They can also serve as the input to further linguistic processing in order to achieve speech understanding.
An isolated-word speech recognition system requires that the speaker pause briefly between words, whereas a continuous speech recognition system does not. Spontaneous, or extemporaneously generated, speech contains disfluencies, and is much more difficult to recognize than speech read from script. Some systems require speaker enrollment---a user must provide samples of his or her speech before using them, whereas other systems are said to be speaker-independent, in that no enrollment is necessary. Some of the other parameters depend on the specific task. Recognition is generally more difficult when vocabularies are large or have many similar-sounding words. When speech is produced in a sequence of words, language models or artificial grammars are used to restrict the combination of words.
Speech recognition is a technology that is constantly evolving. It is a technology that is experiencing tremendous growth in the commercial market, apart from its original niche as an assistive technology product. There are presently three major companies with speech recognition products, Dragon Systems, Lernout & Hauspie (L&H), and IBM. Stiff competition between these companies and more demand from consumer and business markets, has led to a tremendous drop in prices over the last few years. Competition has also fueled the development of a plethora of new products. Each company has several products available, ranging in price, features, and the applications that they support. This paper seeks to make sense of the overwhelming array of products so that persons who are shopping for speech recognition will have a better understanding of their choices.
What are the Types of Speech Recognition?
*Discrete
• Slower dictation process - better for persons with difficulty in language processing or in fluid speech
• Word-by-word style, rather than phrases, reflects the way beginning writers form sentences
*Continuous
• Processes speech by phrase
• Takes context into account
• Is less accurate if phrases are interrupted
• Advantages: Speed and accuracy (for most users)
Who Can Benefit from Speech Recognition?
• Persons with mobility impairments or injuries that prevent keyboard access
• Persons who have or who are seeking to prevent repetitive stress injuries
• Persons with writing difficulties
• Any person who want hands-free access to the computer
• Any persons who wants to increase their typing speed
(reportedly up to 160 wpm)
What is Required to Use Speech Recognition?
• A Powerful Computer
• Consistent Speech (not necessarily intelligible)
• Fluid speech (i.e., not pausing between words) desirable for use of continuous speech products
• Patience
• Basic knowledge of computers
• Fairly high cognitive ability
Applications of speech recognition
• Command recognition - Voice user interface with the computer
• Dictation
• Interactive Voice Response
• Automotive speech recognition
• Medical Transcription
• Pronunciation Teaching in computer-aided language learning applications
• Automatic Translation
• Hands-free computing

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Presented by:
Mr. Sibananda Panda

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The Computer of the Future will TALK, LISTEN and UNDERSTAND.
One of them is the Apple Macintosh of today. Apple’s Speech Recognition and Speech Synthesis Technologies now give speech-savvy applications the power to carry out your voice commands and even speak back to you in plain English.
You don’t even have to train it to understand your voice, because it already understands you, from your very first word.. You can speak naturally
DEFINATION
Speech recognition is the process of converting a speech signal to a sequence of words, by means of an algorithm implemented as a computer program.
Voice Verification or speaker recognition is a related process that attempts to identify the person speaking, as opposed to what is being said.
IBM SPEECH RECOGNITION SYSTEM
Speech recognition is the process of converting an acoustic signal, captured by a microphone or a telephone, to a set of words.
• The recognized words can be the final results, as for applications such as commands & control, data entry, and document preparation.
• They can also serve as the input to further linguistic processing in order to achieve speech understanding.
• Persons with mobility impairments or injuries that prevent keyboard access
• Persons who have or who are seeking to prevent repetitive stress injuries
• Persons with writing difficulties
• Any person who want hands-free access to the computer
• Any persons who wants to increase their typing speed
(reportedly up to 160 wpm)
• A Powerful Computer
• Consistent Speech (not necessarily intelligible)
• Fluid speech (i.e., not pausing between words) desirable for use of continuous speech products
• Patience
• Basic knowledge of computers
• Fairly high cognitive ability
Applications of Speech Recognition
• Command recognition - Voice user interface with the computer
• Dictation
• Interactive Voice Response
• Automotive speech recognition
• Medical Transcription
• Pronunciation Teaching in computer-aided language learning applications
• Automatic Translation
• Hands-free computing
What are the Types of Speech Recognition?
u Discrete
• Slower dictation process - better for persons with difficulty in language processing or in fluid speech
• Word-by-word style, rather than phrases, reflects the way beginning writers form sentences
v Continuous
• Processes speech by phrase
• Takes context into account
• Is less accurate if phrases are interrupted
• Advantages: Speed and accuracy (for most users)
SPEECH ANALYSIS
Environmental noise, room acoustics and a speaker’s physical and psychological conditions play an important role in determination.
Ex. let’s assume extremely bad individual words recognition with a probability of 0.95. This means that 5% of the words are incorrectly recognized. If we have a sentence with 3 words, the probability of recognizing the sentence correctly is 0.95 × 0.95 × 0.95 = 0.857.
Speech Recognition System
Components of speech recognition & understanding.
Speech Recognition Research
• Room acoustic with existent environmental noise. Overlapping of the primary sound wave.
• Word boundary must be determined.
• During comparison time normalization is necessary. The same word can be spoken quickly or slowly
Speaker –independent & Speaker-dependent
Recognition System.
• A speaker-independent system can recognize with the same reliability essentially fewer words than a speaker- dependent system because the latter is TRAINED IN ADVANCE. Training in advance means that there exists a training phase for the speech recognition system, which takes a half an hour.
• Speaker-dependent recognition system can recognize around 25,000 words, Speaker-independent recognition system can recognize around 500 words but with a worse recognition rate .
The major players in the speech recognition market are Dragon Systems, Lernout & Hauspie (L&H), and IBM.
• Dragon’s original product, Dragon Dictate, is currently the only product that uses the discrete speech model
• The current L&H product line, called VoiceXpress, includes a Standard, Advanced, and Professional edition.
• IBM has been a major player in speech recognition for many years. Its discrete speech product, IBM Voice Type, IBM has discontinued this product and is now focusing all its efforts on developing continuous speech products. Its current product line, IBM Via Voice Millenium, includes a Standard, Web and Professional edition. The web edition features natural language commands for Internet Explorer, Netscape Communicator and America Online.

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Speech Recognition
Introduction
• What is Speech Recognition?
- Voice Recognition?
• Where can it be used?
- Dictation
- System control/navigation
- Commercial/Industrial applications
- Hand held digital recorders
Continuous or Discrete?
• Continuous speech
- dictation
• Discrete speech
- system controls
How does SR work?
• Recognition
• Training
• Correction
• Command/Control
Recognition (1)
Recognition (2)
Acoustic Modeling
• Spoken words: “I think there are…..”
• Phonemes: ‘ ay th-in-nk-kd dh-eh-r aa-r’
• H.M.M.’s: 5 state representation
• Speech Engine
Recognition (3)
Language Modeling
• Word context
• Word frequency
• Transition possibilities
Voice Training (1)
Can be done by:
• Predetermined text segments
• Individual words
Compare new acoustic with old and combines
• More training = better recognition
Voice Training (2)
User specific Voice file
• Voice qualities
• Pronunciation
• Patterns of word use
• Preferred vocabulary
Making Corrections
• Move cursor by voice command
• Memorize edit commands
• List of possible alternatives
• Make correction manually
Command/Control
• Desktop grid
• Program or Link name/number
• URL name
• Memorized commands
Recent Improvements in SR
• Faster training ~10 min.
• Better recognition ~95%
• More compatible software
• Better system control/command
Current Software Options for PC
• Dragon Systems – Naturally Speaking
• Philips – FreeSpeech
• IBM – ViaVoice
• Lernout & Hauspie – Voice Xpress
How well do the work?
Future of SR
• SUI – Speech-based User Interface
• Improvements needed:
- Greater accuracy
- Greater system control/command
- More compatible software
Conclusion
• SR Uses
• How does it work?
• Current Software
• Problems of SR
• More SR coming soon….

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Speech Recognition and its clinical applications
Speech recognition ?
Speech Recognition are technologies of particular interest, for their support of direct communication between humans and computers, through a communications mode, humans commonly use among themselves and at which they are highly skilled.
Rudnicky, Hauptman, and Lee
Timeline of Speech recognition
1936 - AT & T’s Bell labs started study of speech recognition (funded by DARPA)
1974 - optical character recognition
1975 – text to speech synthesis ( Kurzweil reading machine)
1978 – speak and spell toy released by Texas Instruments
1980 – Xerox started producing reading machine Text bridge
1997 – Dragon Systems produces first continuous speech recognition product
Types of speech recognition
Isolated words
Connected words
Continuous speech
Spontaneous speech (automatic speech recognition)
Voice verification and identification
Speech recognition – uses and applications
Dictation
Command and control
Telephony
Medical/disabilities
Challenges of speech recognition
Ease of use
Robust performance
Automatic learning of new words and sounds
Grammar for spoken language
Control of synthesized voice quality
Integrated learning for speech recognition and synthesis
SpeechActs
Why develop SpeechActs?
Integrated conversational applications
No specialized language expertise
Technology independence
Information flow in SpeechActs
SpeechActs - Framework
Audio server presents raw digitized audio to speech recognizer
Swiftus parses the word list to produce a set of feature-value pairs
Discourse manager maintains a stack of information about the current conversation
Discourse manager and application respond to the user by sending a text string to ‘text to speech manager’
SpeechActs: A Spoken Language Framework
Continuous-speech recognizers require grammars that specify every possible utterance a user could say to the application
The recognizer grammar should closely synchronize with the Swiftus semantic grammar
Solved by inventing Unified Grammar
Unified grammar
Collection of rules
Made of a pattern such as Backus-Naur Form followed by augmentations which are statement written in the Pascal-like form
Compiler that produces a grammar specific to speech recognizer and corresponding Swiftus grammar
Swiftus – the natural language processor
Semantic representation generated in real time to facilitate conversation
Accurate understanding
Tolerance of misrecognized words
Wide variation among applications
Ease of use
Swiftus performance - Solved
Discourse management
To support more natural speech , we need at least rudimentary discourse management
Should support discourse-segment pushing and popping
Prompt design
Error-correcting mechanism
Discourse manager
discourse represented as a data structure consisting of functions for handling user output
maintains a stack of these structures, and the top one handles the default discourse for the current application or current dialogue
current application or dialogue popped off the stack when the user cancels the activity or the problem is resolved
keeps a simple stack of referenced items to a avoid entering into a subdialogue
To simulate human conversation….
conversational pacing
explicit error corrections
define the functional boundaries of an application
Clinical applications
Medical transcription mainly in radiology and pathology
First use of speech recognition in the field of radiology in 1981
Mean accuracy rate of reading pathology reports, using IBM Via Voice Pro software – 93.6% compared to human transcription at 99.6%
Speech recognition in clinical dentistry?
13% used voice recognition
16% discontinued using voice recognition
21% believed chairside computer use could be improved with better voice recognition
Using an automatic speech recognition will be the way to go!!

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INTRODUCTION
One of the most important inventions of the nineteenth century was the telephone. Then at the midpoint of twentieth century, the invention of the digital computer amplified the power of our minds, enabled us to think and work more efficiently and made us more imaginative then we could ever have imagined.
Now several new technologies have empowered us to teach computers to talk to us in our native languages and to listen to us when we speak (recognition); haltingly computers have begun to understand what we say.
Having given our computers both oral and aural abilities, we have been able to produce innumerable computer applications that further enhance our productivity. Such capabilities enable us to route phone calls automatically and to obtain and update computer based information by telephone, using a group of activities collectively referred to as Voice Processing.
Speech is one of the most natural ways to interact. When it comes to computers it is no different. If an application can be controlled solely by way of voice commands then the opportunity that lies is unlimited. Even though the idea of using speech as an input mechanism for an application is not new there are not a lot of applications that use speech as in input. In other words speech is still a big opportunity that is yet to be explored.
Speech recognition allows you to provide input to an application with your voice. Just like clicking with your mouse, typing on your keyboard, or pressing a key on the phone keypad provides input to an application, speech recognition allows you to provide input by talking. In the desktop world, you need a microphone to be able to do this.
Broadly, speech analysis can be divided in to two paradigms : - Text to speech and Speech to Text conversion.
Speech recognition can be of two types based on the grammar that the recognition is based on. (Grammar is in other words the list of possible recognition outputs that can be generated). An application can limit the possible combination of the words spoken by choosing proper grammar.
In a command and control scenario a developer provides a limited set of possible word combinations, and the speech recognition engine matches the words spoken by the user to the limited list. In command and control the accuracy of recognition is very high. It is always better for applications to implement command and control as the higher accuracy of recognition makes the application respond better.
In Dictation mode the recognition engine compares the input speech to the whole list of the dictionary words. For the dictation mode to have a high accuracy of recognition is it important that the user has prior trained the recognition engine by speaking in to it. The training or creating of a profile can be done by using the speech properties in the control panel.
Speaker Dependence vs. Speaker Independence
Speaker dependence describes the degree to which a speech recognition system requires knowledge of a speaker’s individual voice characteristics to successfully process speech. The speech recognition engine can “learn” how you speak words and phrases; it can be trained to your voice.
Speech recognition systems that require a user to train the system to his/her voice are known as speaker-dependent systems. If you are familiar with desktop dictation systems, most are speaker dependent. Because they operate on very large vocabularies, dictation systems perform much better when the speaker has spent the time to train the system to his/her voice.
Speech recognition systems that do not require a user to train the system are known as speaker-independent systems. Speech recognition in the Voice XML world must be speaker-independent. Think of how many users (hundreds, maybe thousands) may be calling into your web site. You cannot require that each caller train the system to his or her voice. The speech recognition system in a voice-enabled web application MUST successfully process the speech of many different callers without having to understand the individual voice characteristics of each caller.

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Abstract:
Language is man's most important means of communication and speech its primary medium. Speech provides an international forum for communication among researchers in the disciplines that contribute to our understanding of the production, perception, processing, learning and use. Spoken interaction both between human interlocutors and between humans and machines is inescapably embedded in the laws and conditions of Communication, which comprise the encoding and decoding of meaning as well as the mere transmission of messages over an acoustical channel. Here we deal with this interaction between the man and machine through synthesis and recognition applications.
The paper dwells on the speech technology and conversion of speech into analog and digital waveforms which is understood by the machines
Speech recognition, or speech-to-text, involves capturing and digitizing the sound waves, converting them to basic language units or phonemes, constructing words from phonemes, and contextually analyzing the words to ensure correct spelling for words that sound alike. Speech Recognition is the ability of a computer to recognize general, naturally flowing utterances from a wide variety of users. It recognizes the caller's answers to move along the flow of the call.
We have emphasized on the modeling of speech units and grammar on the basis of Hidden Markov Model. Speech Recognition allows you to provide input to an application with your voice. The applications and limitations on this subject has enlightened us upon the impact of speech processing in our modern technical field.
While there is still much room for improvement, current speech recognition systems have remarkable performance. We are only humans, but as we develop this technology and build remarkable changes we attain certain achievements. Rather than asking what is still deficient, we ask instead what should be done to make it efficient….
INTRODUCTION
One of the most important inventions of the nineteenth century was the telephone. Then at the midpoint of twentieth century, the invention of the digital computer amplified the power of our minds, enabled us to think and work more efficiently and made us more imaginative then we could ever have imagined .now several new technologies have empowered us to teach computers to talk to us in our native languages and to listen to us when we speak(recognition); haltingly computers have begun to understand what we say. Having given our computers both oral and aural abilities, we have been able to produce innumerable computer applications that further enhance our productivity. Such capabilities enable us to route phone calls automatically and to obtain and update computer based information by telephone, using a group of activities collectively referred to as Voice Processing.
SPEECH TECHNOLOGY
Three primary speech technologies are used in voice processing applications: stored speech, text-to – speech and speech recognition . Stored speech involves the production of computer speech from an actual human voice that is stored in a computer’s memory and used in any of several ways.
Speech can also be synthesized from plain text in a process known as text-to – speech which also enables voice processing applications to read from textual database.
Speech recognition is the process of deriving either a textual transcription or some form of meaning from a spoken input.
Speech analysis can be thought of as that part of voice processing that converts human speech to digital forms suitable for transmission or storage by computers.
Speech synthesis functions are essentially the inverse of speech analysis – they reconvert speech data from a digital form to one that’s similar to the original recording and suitable for playback.
Speech analysis processes can also be referred to as a digital speech encoding ( or simply coding) and
DIGITIZATION OF ANALOG WAVEFORMS
Two processes are required to digitize an analog signal:
(a) Sampling which discretizes the signal in time
(b) Quantizing, which discretizes the signal in amplitude.

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