Communication plays an essential role in our lives. Humans started with signs, symbols, and then progressed to a stage where they began to communicate with languages. Later came computing and communication technologies.
Machines began to communicate with humans and in some cases even themselves. Communication created the world of the Internet, or as we technically know it, the Internet of Things (IoT). Here is the development of speech recognition technology which includes machine learning.
Development of speech recognition technology and machine learning
The Internet has given rise to new ways of using data. By using this we can communicate directly or indirectly by training the machines, which is known as machine learning. Before that, we had to use a computer to communicate with the machines.
Research and development is beginning to substantially eliminate some of the use of computers. We know this technology as automatic speech recognition. Based on Natural Language Processing (NLP), it allows us to interact with the machines in which we speak, using our natural language.
Initial research in the area of speech recognition has been successful. Since then, speech scientists and engineers have aimed to optimize speech recognition engines correctly. The ultimate goal is to optimize the interaction of the machine according to the conditions so as to reduce the error rate and increase the efficiency.
Some organizations have already started to fine-tune speech recognition technologies. For more than a decade, Virginia-based Govives Inc. has steadily built expertise in the design and development of speech recognition technologies and solutions.
Automatic Speech Recognition and its Applications
Automatic Speech Recognition (ASR) technology is a combination of two different branches – computer science and linguistics. Computer science to design algorithms and programs and linguistics to build a dictionary of words, sentences and phrases.
generate speech transcription
The first stage of development begins with speech transcription, where audio is converted to text, i.e. speech to text conversion. The system then filters and removes the unwanted signal or noise. We have different voice speeds when speaking a word or sentence, so general models of speech recognition are designed to account for those rate changes.
Signs are further divided to identify vowels later. Phonemes are letters that have the same level of airflow, such as ‘b’ and ‘p’. Next, the program tries to match the exact word by comparing it with words and sentences stored in the linguistics dictionary. Then, the speech recognition algorithm uses statistical and mathematical modeling to determine the exact words.
Presently there are two types of speech recognition system.
One type of system is accomplished with the mode of learning and the other as a human dependent system. With the development of Artificial Intelligence (AI) and Big Data, speech recognition technology has taken the next level.
A specific neural structure called long-term short-term memory has brought about a significant improvement in this area. Globally, organizations are leveraging the power of speech in their premises at different levels for a wide variety of tasks.
Speech to text software can be used to convert audio files to text files.
Speech to text software includes a timestamp and a confidence score for each word. Many countries do not have their language keyboard embedded, and most people do not have the idea of using a specific language keyboard, although they are good at it orally.
In such cases, speech transcription helps them to convert speech into text in any language.
Real-time captioning system — Captions on the go.
Another use of this technology is in real-time. Tech done in real-time is known as computer assisted real-time translation. It is basically a speech to text system which operates on a real time basis. Organizations around the world hold meetings and conferences.
They leverage the power of live captioning systems, for maximum engagement by a global audience. The real-time captioning system converts speech to text and displays it on the output screen. It translates speech in one language into text in other languages and also helps in making notes of a presentation or speech. These systems convert speech into text that can be understood by the hearing impaired.
Voice Biometric System – A smart way to authenticate
In addition to speech-to-text, the technology expands its branch into biometric systems, which created voice biometrics for authenticating users. The voice biometric system analyzes the speaker’s voice, depending on factors such as modulation, pronunciation and other elements.