Technologies

Technologies Driving Highly Interactive Applications

How can you have an answer before you understand the question? Many vendors want you to adopt their technologies before understanding the true nature of your challenges.

Chant's Getting the World Taking with Technology® experts understand the complexity involved in adopting new processes, technologies, and organizational structures and have been working with advanced interactive technologies, SDKs, and cloud services for over twenty-five years. The following are some of technologies, vendor SDKs, products, and services used in formulating turnkey solutions and supported with Chant developer tools. Speak with an expert about technologies that are best for you.

Artificial Intelligence

The field of Artificial Intelligence (AI) has roots back to the 1950s where its research and concepts and are found in many disciplines, frameworks, and technologies throughout the evolution of computing science. Each wave of technology has introduced more of its applied theories and practices.

Examples can be found in machine hardware and software: instruction optimizations, memory management, database management, data query and analytics, audio processing, graphics rendering, speech technology, motion and special mapping, and virtual reality.

AI also spans the field of machine learning, deep learning, robotics, and more. It has received wide attention for various conversational and generative capabilities lately that conjure the notion of a “thinking” capability and what consequences may unfold.

Be assured AI concepts have already been enabling technologies without nefarious intentions or consequences.

Some of these technologies are used in Chant Turnkey Solutions and in the Chant developer tools highlighted below.

Application Development

Technology vendors offer Interactive Development Environments (IDEs) for rapidly developing and testing apps on a variety of devices and platforms.

Android Studio – IDE for developing and testing apps to run on Google Android devices (e.g. mobile, tablets, special purpose).

JBuilder (et. Al.) – IDE for developing and testing apps written in Oracle Java to run on a variety of devices and platforms.

RAD Studio – IDE for developing and testing apps written in Delphi (Object Pascal) and C++Builder to run on Windows, macOS, Linux, iOS, and Android devices and platforms.

Visual Studio – IDE for developing and testing apps written in C++, C#, VB (et. Al.) to run on Windows, macOS, Linux, iOS, and Android devices and platforms.

Xcode – IDE for developing and testing apps written in Objective-C and Swift to run on macOS, and iOS platforms.

Natural User Interface

Application interfaces are more humanized with movement tracking using natural user interface (NUI) technology.

NUI can be used to control data processing and data entry. As a new modality for a natural user interface, it can augment traditional input methods applications use with keyboard, mouse, touch, and voice.

Movement tracking is the process of mapping movement from image and positional data captured by cameras. It can also be done with measuring light and distance with lasers (lidar). Applications may be humanized to respond to gestures and environmental cues as form of modality.

Virtual Reality

Virtual Reality offers simulated 3D environments for a managed visual experience with specialized head-mounted display device. This experience may also integrate audio, speech detection, and haptic technology (i.e., touch sensitivity and movement detection).

It may include Augmented Reality (AR) that blends what the user sees in their real surroundings with generated digital content simulations.

Commercial solutions advancing today are referred to as Mixed Reality (MR) where real world and virtual world images co-exist. This produces a new environment where physical and simulated digital objects interact in real time.

Natural Language Processing

The field of Natural Language Processing (NLP) has its roots back in the 1940s when Alan Turing proposed a test that includes a task that involves the automated interpretation and generation of natural language.

Since then, developments in language processing include bold advancements in language models, language translation, speech recognition (segmentation), and speech synthesis.

Speech Recognition

Speech recognition is the process of converting an acoustic signal (i.e. audio data), captured by a microphone or a telephone, to a set of words. These words can be used for controlling computer functions, data entry, and application processing.

A speech recognition grammar is a collection of rules comprised of words and phrases to be recognized from speech. A speech recognition engine (i.e., recognizer) uses a grammar to enhance its ability to recognize specific combinations of spoken words and phrases.

With continuous or context-based recognition referred to as dictation, a recognizer matches from all the word possibilities in a large dictionary and asserts contextual analysis to ensure it returns the correct word (i.e., spelling) for homonyms (e.g., right or write).

Unlike dictation recognition, grammar recognition is context-free. A recognizer only matches against the rule definitions in the grammar.

Context-free grammar recognition enables your applications to capture data very efficiently. Grammars also enable your applications to assert domain constraints to elevate data capture accuracy automatically.

A lexicon is a collection of word pronunciations that a speech recognition engine (i.e., recognizer) uses to improve recognition accuracy. Lexicons consist of the words that a recognizer understands and returns as recognized speech. Since it's impractical for a recognizer to maintain every possible word and context in its spoken language, you enhance the accuracy of speech recognition by extending its lexicon.

A recognition profile is a collection of information used by a speech recognition engine to increase its recognition accuracy for a specific individual's voice and environment.

A speech recognition engine saves training and background noise information to use in recognizing speech. Some speech recognition engines, such as Microsoft's Desktop Recognizer, capture and save information over time to adapt the profile for optimum speech recognition accuracy.

Speech Synthesis

Speech synthesis is the process of converting words to phonetic and prosodic symbols and generating synthetic speech audio data. Synthesized speech for can be used for answering questions, event notification, and reading documents aloud for example.

Lexicons play an important role in the quality of text-to-speech playback. A text-to-speech engine (i.e., synthesizer) uses lexicons to obtain pronunciation information associated with words to generate the appropriate speech sounds for the word. For example, with a lexicon you may ensure "record" is pronounced correctly when used as a noun and when used as a verb.

Markup Language

Speech Synthesis Markup Language (SSML) is text with imbedded indicators (text-to-speech markup) that control speech synthesis from the text. Speaking qualities such as the speed, pitch, emphasis, and word pronunciation may be tailored in reproducing speech from text.

A TTS grammar is a collection TTS markup. A text-to-speech engine (i.e., synthesizer) uses TTS markup to enhance its ability to synthesize speech from text and generate the audio for playback.

VoiceXML

Voice Extensible Markup Language (VoiceXML) is defined by the W3C as markup language designed for creating audio dialogs that feature synthesized speech, digitized audio, recognition of spoken and DTMF key input, recording of spoken input, telephony, and mixed initiative conversations. Its major goal is to bring the advantages of Web-based development and content delivery to interactive voice response applications.

Vendors

Chant works with industry leaders to develop turnkey solutions and developer tools.