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VOICE USER INTERFACE

VOICE USER INTERFACE. BY R.SELVI K.PRIYA I-MCA. INTRODUCTION. voice portal can be defined as “speech enabled access to Web based information”. In other words, a voice portal provides telephone users with a natural language interface to access and retrieve Web content. Voice based

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VOICE USER INTERFACE

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  1. VOICE USER INTERFACE BY R.SELVI K.PRIYA I-MCA

  2. INTRODUCTION • voice portal can be defined as “speech • enabled access to Web based information”. In other words, a voice portal provides telephone users with a natural language interface to access and retrieve Web content.

  3. Voice based internet access uses rapidly advancing speech recognition technology to give users any time, anywhere communication and access-the Human Voice- over an office, wireless, or home phone.

  4. Why Voice? • Natural speech also has an advantage as • an input modality, allowing for hands-free and eyes-free use. With • proper design, voice commands can be created that are easy for a user to • remember • Speech can be used to create an interface that is • easy to use and requires a minimum of user attention.

  5. VUI (Voice User Interface) • Automated speech recognition (ASR) is the • engine that drives today's voice user interface (VUI) systems. These let • customers break the 'menu barrier' and perform more complex • transactions over the phone. • The best VUI systems are "speaker independent"-they understand • naturally spoken dialog regardless of the speaker.

  6. ASR systems can be enabled with voice authentication, • eliminating the need for PINs and passwords. • the 'voice Web' is evolving, where • browsers or Wireless Application Protocol (WAP)-enabled devices • display information based on what the user vocally asks for. • Good VUI systems have multiple fallback strategies for speech • recognition failure, such as asking callers to spell names or breaking a • question into parts.

  7. VoiceXML is a markup language • specification that defines the key elements of voice-enabled transactions, • which also allows repurposing of this data across any number of • platforms and systems

  8. Next Generation Network Services • It is the next step in the world • communications traditionally enabled by three separate networks: the • public switched telephone network (PSTN) voice network, the wireless • network and the data network (the Internet). NGNs converge all three of • these networks-voice, wireless and internet- into a common a common • packet infrastructure.

  9. Three types of services drive NGNs: real-time and non real-time • communication services, content services, and transaction services. • The • services-driven NGN gives service provides greater control, security, • and reliability while reducing their operating costs. Service providers • can quickly and costs effectively build new revenue.

  10. Next-generation Network Benefits •  More choices-Open systems promote multiple-vendor • participation in the marketplace. •  Lower cost-Solutions built on open standards cut • development time for solution providers. •  Innovative Services- Working to standards frees developers • to concentrate on adding value. •  Lower Risk- Compatibility with products and technologies • from many suppliers decreases the risk of ownership.

  11. Deploying NGN Services • The NGN begins with media servers, which provide advanced • media-processing capabilities. The value of a media server is its • flexibility for supporting advanced media-processing services like basic • voice announcements, interactive voice response (IVR), conferencing, • messaging, text-to-speech (TTS), and speech recognition.

  12. Voice Recognition and AuthorizationSpeaker Verification • The speaker-specific characteristics of speech are due to • differences in physiological and behavioral aspects of the speech • production system in humans. The main physiological aspect of the • human speech production system is the vocal tract shape.

  13. The vocal tract modifies the spectral content of an acoustic wave • as it passes through it, thereby producing speech. Hence, it is common in • speaker verification systems to make use of features derived only from • the vocal tract.

  14. It is possible to represent the vocal-tract in a parametric form as the • transfer function H(z). In order to estimate the parameters of H(z) from • the observed speech waveform, it is necessary to assume some form for • H(z). • Figure 3 illustrates the differences • in the models for two speakers saying the same vowel. • Figure 3:

  15. Speaker Modeling : • The purpose of voicemodeling is to build a model that captures these variations in the extracted set of features. There are two types of models that have been used extensively in speaker verification and speech recognition systems: • Stochastic models and template models. • The stochastic model treats the speech production process as a parametric random process and assumes that the parameters of the underlying stochastic process can be estimated in a precise, well defined manner. The template model attempts to model • the speech production process in a non-parametric manner by retaining a number of sequences of feature vectors derived from multiple utterances of the same word by the same person.

  16. A verypopular stochastic model for modeling the speech production process is • the Hidden Markov Model (HMM). HMMs are extensions to the conventional Markov models, wherein the observations are a • probabilistic function of the state, i.e., the model is a doubly embedded • stochastic process where the underlying stochastic process is not directly • observable (it is hidden).

  17. For speech signals, another type of HMM, called a left-right model • or a Bakis model, is found to be more useful. A left-right model has the • property that as time increases, the state index increases (or stays the • same)-- that is the system states proceed from left to right.

  18. Pattern Matching: • The pattern matching process involves the comparison of a given • set of input feature vectors against the speaker model for the claimed • identity and computing a matching score.

  19. Speech Recognition Challenges • The basic challenges faced by voice application • developers included the following: • 1. Variability of speech patterns: • in many different ways. • Processing power: • Extracting meaning:

  20. Conclusion. • Speech-enabled Internet portals or voice portals are quickly • becoming the hottest trend in E-commerce – broadening the access to • internet content to everyone with the most universal communications • device of all, a telephone. • The potential for voice portals is as wide as the reach of • telephones, which today number 1.3 billion around the world. • A voice portal provides telephone users with a natural • language interface to access and retrieve web content.

  21. A voice portal can also • provide users access to virtual personal assistance and web-based unified • messaging applications • Voice portals can also cut operating expenses by freeing up agent • time and replacing human operators with an easy-to-use automated • solution.

  22. The voice portal reference system is a packaged, integrated • hardware and • Software reference system for building hardened E-Business and • speech-enabled voice portal solutions.

  23. QUERIES ?????????????

  24. THANK YOU

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