Transcription is the process of converting an audio recording into a printed text. Technology has simplified production processes in many areas of the economic and social sectors: business, medicine, journalism, and education. In each of them, a person was able to free himself from the exhausting need to write large amounts of text manually (lectures, minutes of meetings, interviews). Now robots have taken over this work.
Historical background
Shorthand can be considered the starting point of the technology. Before the advent of automatic devices for recording meetings, people used a system of special signs that allowed them to record conversations several times faster than regular writing. The services of stenographers were most in demand at meetings of congresses and in courts. At the end of the meetings, the recordings were transcribed and typed.
With the advent of sound recorders, human work became simpler, the recording quality became higher, but to transform it into a printed form, you still had to spend time listening to audio recordings and typing on a typewriter.
Voice recognition technology appeared more than half a century ago. However, it became possible to use it to transcribe conversations only in the early noughties with the advent of machine learning. Artificial intelligence has been taught to record speech, recognize it and display it on the monitor screen in text form.
Further development is aimed at training the neural network to recognize complex professional conversations on medical, legal, and engineering topics, where specific terminology and turns of speech are used. In addition, work continues on improving the quality of speech recognition, learning additional editing, formatting, etc.
However, manual transcription has not yet been completely abandoned. It is still considered the most accurate and in high demand. For example, during private negotiations, when all the nuances of the dialogue must remain secret.
Types of transcription
Manual
Professional transcribers are engaged in this type of transformation of audio or video files into text. Its advantage lies primarily in absolute accuracy: a person, unlike a machine, can hear speech, even if the audio quality is low (there are noises, extraneous distracting sounds). If something is not said clearly enough, then the person will understand the meaning from the context of the conversation (dialogue). For neural networks, poor diction, accent, and noise interference are factors that significantly reduce the quality of speech recognition.
To practice transcription professionally, a person must have:
- high literacy;
- high print speed;
- attentiveness (to recognize difficult places);
- concentration and perseverance (parsing notes is a monotonous and tedious job).
Compared to automatic transcription, manual transcription takes much longer, and the service is expensive.
Automatic
In this case, everything happens without human intervention. The latter only needs to upload the recording to the service or connect to a platform that will work in real time, such as FollowUp. The main advantage of automatic speech recognition is its high speed. The neural network outputs the result in a few minutes. At the same time, many programs already write without spelling and punctuation errors, and they know how to format. Nevertheless, you should still check the operation of the machine, since errors may be semantic or logical in nature.
Types of automatic speech recognition
- Streaming. It is used if you need to transcribe speech in real time, for example, during a telephone conversation or to create subtitles in a video clip. While a person is talking, artificial intelligence recognizes it and translates it into text in the form of subtitles or a document.
- Synchronous. It is used for audio transcription in messengers. Unlike streaming transcription, synchronous transcription recognizes audio recordings, but only handles short audio tracks (30-40 seconds). However, this is enough for short messages in messengers.
- Asynchronous. They are used to work offline. It is suitable for converting large-volume audio (recordings of conferences, interviews, lectures, webinars).
How speech recognition technology works
Human speech consists of sentences, which in turn are formed from words written using letters. With rare exceptions (B, B), the letters denote the sounds that are pronounced during oral speech. When played back, each sound leaves a unique pattern on the spectrogram of the audio recording. The essence of machine learning is to teach a neural network to recognize such patterns, match them with sounds, and select the necessary letters from which to add syllables and words.
The training materials for the neural network, datasets, are fragments of a voice recording and the accompanying marked–up text. The machine is offered to solve such datasets, as a result of which a database is formed. The more hours spent on training (and recognizing datasets), the more competent the robot will be in the future.
If it is necessary to transform speech from a foreign language, it is necessary that the machine be trained in that language.
To transform sound into text, AI uses an acoustic model, while adding words into sentences uses a linguistic model. If he doesn’t find any words in the dictionary, he selects the appropriate ones based on their context.
Schematically, the transformation process can be divided into several stages:
- Audio recording.
- An analysis in which the robot splits text into phonemes (very short speech fragments) and recognizes sounds.
- Decoding, which identifies letters, syllables, and words.
- Converting recognized parts into sentences.
- Decoding.
Areas of transcription application
Business
According to statistics, 25% of companies have already implemented speech recognition technologies. Innovation has expanded business opportunities:
- allowed to optimize production processes;
- improved communication within the company, as well as between managers and clients;
- We saved the staff from the routine of keeping protocols, filling out questionnaires, and cards.;
- simplified the recruitment process.
Entrepreneurial activity is associated with a large number of meetings, meetings, negotiations. At the same time, it is important to record not only the general outline of the meetings, but also the details related to the decisions taken, the appointment of responsible persons, and deadlines. Previously, the minutes were kept by a secretary, whose duties included a detailed description of the details, processing, printing out the text and sending it to the meeting participants. Now the neural network does all this.
The ability to transcribe calls and telephone conversations made it possible to monitor the quality of managers’ work, establish script compliance, reduce call loss, and improve communication with customers.
Another advantage of implementing speech recognition technologies is the opportunity to explore the market. In call centers, the neural network has replaced operators, significantly increasing the efficiency of work: AI does not go on vacation, on sick leave, can work 24/7, does not get tired or annoyed because of the rudeness of subscribers.
When applying for a job on a neural network, an initial interview is more often shifted, during which the robot asks a standard set of questions, analyzes the answers to them and weeds out candidates who do not meet the general criteria.
Education
The free speech recognition platforms that have appeared have made it much easier for students to study. Previously, they had to spend hours writing down lectures for the teacher at a fast pace, missing some of the information, and then parsing poorly readable lines at home. Now you can record lectures using programs that allow you to simultaneously make an audio recording and decode what you hear into a text format. At the same time, the information will be more complete, since the machine will not miss anything.
It has also become easier for teachers. They can also compose their lectures, verbally dictate the material into a microphone, and then send it to neural networks for decoding. Such materials can be sent to students if for any reason they are unable to attend a full-time class.
The technology has also found a response in the scientific community. Scientists actively use the innovation to record texts of meetings and conferences, thus collecting material for dissertations.
Journalism
The innovation has made the work much easier for media workers, as well as for students. It has become easier for them to interview (the machine writes everything accurately, does not miss or distort facts and meanings, which is very important). Thanks to technology, journalists were able to reduce the time between collecting information and sending the finished article to print. After all, there are programs that allow you to make adjustments in parallel with recording and transcription, actually creating an article on the go.
Creating video content
Bloggers running YouTube channels use technology to create subtitles in different languages, which expands their audience by attracting subscribers from other countries (most speech recognition software speaks dozens of languages). Subtitles are a salvation for hearing–impaired users.
Medicine
The technology of automatic transcription has found application in the medical industry. First of all, with their help, it became possible to relieve doctors and average medical staff from the routine associated with filling out medical records. Using neural network assistants at the reception, the doctor can also not waste time filling out the card, but dictate information to the machine, paying more attention to the patient.
Online Secretary from FollowUp
AI Secretary is a smart application for organizing, conducting and analyzing meetings and meetings. The model is suitable for both small and large companies, making their meetings more organized and productive.
Al-Secretary:
- He will record an appointment;
- transcribes the conversation;
- He will make a sammari with an indication of the topic, main issues, conclusions, tasks and responsible persons.;
- will send emails to the participants.
The application connects to the work calendar, and it takes no more than half an hour to set up. The transcription accuracy is 98%, and the information security is 100%.
Will fit:
- business owners;
- for managers;
- project teams;
- HR departments.
The first 100 minutes of use are free. A flexible tariff schedule has been developed for small companies and growing businesses. Individual conditions apply to large enterprises.
