How Voice Recognition Software Actually Works

Technology can do amazing things. One technological achievement that is certainly impressive is voice recognition software.

This software has the ability to enter data into a computer through speech commands. It can, in fact, be used to replace a keyboard all together. This technology has been widely implemented in call centers, and it is also available for personal computers. It can be especially useful to the disabled. Still, despite its now wide availability to the public, many people don’t know how voice recognition technology works.

Converting spoken word into data requires multiple complex steps. The sound of speech actually exists as vibrations that are sent through the air. When these waves meet a microphone used with speech recognition software, they are interpreted by something known as an analog to digital sound converter. This program is what takes those sound waves in the air and translates them into a digital representation of those waves that the computer can understand.

This conversion is achieved through a process known as sampling. The digital representation of the sound wave is not an exact copy. Instead, the sample that is produced is a measurement of the wave at different intervals that are very close together. This program may also do other things like remove background noise or split the sound wave up into different frequencies to represent changes in pitch in the human voice.

The next step occurs when the software separates these recorded sound waves into tiny individual segments. These are often only a couple hundredths of a second in length. They are sometimes even shorter. This is done so the program can interpret changes in sounds that are part of spoken words. These are translated into what are known in linguistics as phonemes. Phonemes can be thought of as the building blocks of words that are used in all languages. For example, there is believed to be 40 different phonemes used in English.

After the sound waves have been digitized and split up into phonemes, the software must work to process what those phonemes mean. It does this by looking for patterns and context. Phonemes surrounded by other phonemes generally produce certain spoken words in different languages. The program compares the pattern of phonemes it has recorded against a library of patterns phonemes that compose different words, sentences and phrases in different languages. By comparing the patterns, it can with some accuracy detect what language, words and phrases are being spoken.

Once this has occurred, the command for the appropriate output is sent out. If this is an automated phone program, it will interpret the command to go to correct help line. If it’s a spoken keyboard program, the output will be sent to the operating system as text.

Speech recognition software implements statistical models to convert perceived phonemes to words and sentences. This is done because such a program can only make a best “guess” at what is being said. Such software can produce correct results most of the time, but there are too many variations in speech to definite it exactly. For example, accents and dialects can vary widely within countries. How a person pronounces words in Minnesota is very different from how someone from Louisiana does. Using statistical models helps provide the flexibility needed to account for such minute differences within in a given language.

To work properly, most speech recognition software programs require significant computer power. It’s easy to understand why. Within a language, there tends to be trillions of different possible word combinations. While the statistical models employed cut down on the need to sift through trillions of pieces of information, speech recognition software still requires a good amount of RAM and processing power.