Automatic speech recognition process involves multiple and extremely complex steps. The process starts with sound waves being converted from analog to digital signals that computers understand. To initiate this step, the system has to digitize the sound by measuring the length and frequency with which the waves are passed on to the system; the digitized sounds are then filtered to remove unwanted sound elements. We know that not everyone speaks in the same frequency even if they are speaking the same sentences. The system has to adjust the frequency of sounds it receives to match the sound template that has been already fed into the system memory.
The sound signals are then further broken down into minute segments that can be as short as few thousandths of a second. The smallest elements of a language called phonemes are combined together to make meaningful expressions of a specific language. So, the minute segments are broken out from the signals and are matched with the known phonemes. Then the speech recognition program studies phonemes and examines them with other phonemes around them. It then uses a complex statistics or pattern to compare them with a large library of words and sentences that is already present in the system memory. Now, the program determines what the speaker was trying to convey and gives the output either as a text or a computer-decipherable command.
Automatic speech recognition is used in various ways. It is widely in automated voice recording answers in phones.
Advanced and refined forms of speech recognition software are nowadays used to develop automated speech-to-text conversion applications in transcription industries; in fact, the speech recognition software is the backbone of any speech-to-text application. Automated transcription applications are used to convert speech to text by various transcription companies, which help them to deliver highly accurate transcripts at quicker turnarounds. Modern-day transcription companies’ delivery involves very minimal human intervention, thanks to the speech-to-text conversion applications.
Transcribe Now uses a highly advanced version of the speech to text conversion application with which they are able to deliver near-live transcripts with accuracy as good as 96%. The automated transcripts are further proofread and edited by experienced transcriptionist for even better accuracy.