Can You Understand Me Now? Soon Records and Information Managers Will Be Required to Address the Output of Voice Recognition Systems as an Integral Part of Their Electronic Records Retention Decisions

By Andolsen, Alan A. | Information Management, January-February 2004 | Go to article overview

Can You Understand Me Now? Soon Records and Information Managers Will Be Required to Address the Output of Voice Recognition Systems as an Integral Part of Their Electronic Records Retention Decisions


Andolsen, Alan A., Information Management


At the Core

This article

* defines voice recognition technology

* explains how the technology is used

* discusses how voice recognition will impact records management

"I would like to speak to a human being."

"I am sorry. I do not understand what you have asked. Please repeat your request."

"I would like to speak to a human being."

"I am sorry. I do not understand what you have asked ..."

So went a recent conversation with the voice recognition computer at a health provider's 800 number. The caller needed to explain a rather complex situation to reorder a prescription. He was fully aware that the voice recognition system he was addressing could not answer his question, one that required several sentences to explain. For some reason, the system could not interpret the phrase "speak to a human being" well enough to transfer the caller to a live operator. It was not until he spoke the magic phrase "customer service representative" that the system responded, "I will connect you with a customer service representative."

This interchange highlights the advantages and drawbacks of voice recognition technology. On the positive side, individuals can communicate in their own words and no longer have to worry about pushing a variety of buttons and listening to a decision tree. On the other hand, if the voice recognition software is unable to recognize and properly interpret the words spoken, users can become increasingly frustrated and concerned that they cannot accomplish their task.

What Is Voice Recognition Technology?

Voice recognition technology describes the ability of a computer to understand human speech. More completely, according to MSN.com, it is "a system of computer input and control in which the computer can recognize spoken words and transform them into digitized commands or text. With such a system, a computer can be activated and controlled by voice commands or take dictation [that] is input to a word processor or desktop publishing system."

The broadest type of voice recognition technology is automatic speech recognition (ASR). Within ASK the most common divisions are text-to-speech and speech-to-text. In addition, voice recognition can be discrete (i.e., each word must be pronounced distinctly and separately from the next) or continuous (i.e., words flow naturally as in normal speech without breaks between them).

The Technology

Voice recognition technology is based on processing spoken words in increasingly complex phases.

* The first phase is to take sounds and convert them from the analog form of airwaves into an electrical signal. This is not different from what Alexander Graham Bell did more than 100 years ago. (See "The History of Voice Recognition Technology.")

* Next, an analog-to-digital converter changes the electrical signal into a string of numbers that reflect a range of analog values.

* A set of compression techniques reduces the amount of information and highlights specific features of the captured sound that enable speech recognition.

* The compressed digital representation of the captured sound is then compared to a reference set of sounds that have been previously stored in compressed digital format as part of the system. In the simplest version, a comparison is made between the recorded speech and, in the case of English, the 40 or so phonemes (or distinct speech sounds) that are the building blocks of speech. (In fact, voice recognition systems may actually compare the digitized and compressed speech to as many as 1,024 possible classifications.)

* The systems are now ready to recognize words. Some systems approach this task through statistical models or neural nets. Others match the recorded speech to words whose patterns of phonemes or classifications have been compiled as a reference standard for the system. …

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