What is automatic speech recognition?
Automatic speech recognition or ASR is a field of computer science that enables people to communicate with computer interfaces using their voices in a manner that, in its most advanced forms, closely resembles natural human conversation.
One of the most recent versions of ASR is described as Natural Language Processing. Natural language processing (NLP) is a field of artificial intelligence and computer science that deals with the interaction between computers and human (natural) languages. The goal of NLP is to develop algorithms and models that enable computers to understand, interpret, and generate human language. NLP tasks include text classification, sentiment analysis, language translation, transcript, named entity recognition, and text generation, among others.
The most popular automatic speech recognition services are voice assistants such as Google Home, Amazon Echo, Siri, and Cortana. In recent times ChatGPT also gained popularity as it can perform a wide range of NLP tasks, such as answering questions, generating text, and conversing in a natural way.
How speech-to-text services can help your company?
Speech-to-text services can have a significant impact on a company’s operations and productivity by enabling faster and more accurate transcription of audio and video content into text format. The advantages of voice technology can dramatically reduce the amount of time we need to spend on certain of our regular tasks. Companies that use audio transcription can profit in the following ways:
- Improved documentation: Companies can use STT services to transcribe audio recordings of meetings, interviews, or presentations into text format, allowing them to be easily documented and stored for later reference.
- Increased productivity: Transcribing audio content manually is time-consuming and error-prone. Speech recognition software can automate this process, freeing up employees to focus on other tasks.
- Better accessibility: By transcribing audio content into text format, companies can make their content more accessible to a wider audience, including individuals who are hard of hearing or have disabilities that prevent them from listening to audio content.
- Better searchability: Transcribing audio content into text format makes it searchable, allowing employees to quickly find and retrieve specific information within large volumes of audio content.
- Improved customer service: Companies can use a speech recognition engine to transcribe customer calls and chats, making it easier to track customer interactions and improve response times.
Speech-to-text services evaluation
Evaluating speech-to-text (STT) services can be a complex process, as there are several factors to consider, including accuracy, speed, cost, compatibility with different languages and accents, and integration with other systems. Here are some key considerations when evaluating STT services:
One of the most important factors in evaluating STT services is the accuracy of the transcription. You should evaluate the STT service’s ability to transcribe speech accurately and with minimal errors, particularly with regard to different accents and languages. Accuracy can depend on multiple factors such as the quality of the audio input, the language, and the accent of the speaker, or the provider of the service. However, it is important to keep in mind that there is still room for improvement and that errors can occur, especially in complex or noisy environments. It is always a good idea to review the transcription to ensure accuracy and make any necessary corrections.
The speed at which STT services transcribe speech is another important factor. You should consider the turnaround time for transcriptions and how well the STT service can handle large volumes of audio content. The speed of the evaluation depends on several factors including the quality of the audio input, the length of the speech, the complexity of the language and vocabulary used, and the processing power of the speech engine. Modern cloud-based STT services can transcribe short audio clips in real-time with high accuracy, while longer audio files may take longer to process. Offline STT systems, which do not require an internet connection, tend to be slower due to limited processing power but may still provide high accuracy for speech recognition tasks.
The cost of STT services can vary widely, so you should consider your budget and the value the service provides for the cost. Some STT services charge based on usage or the length of audio transcribed, while others offer a monthly or annual subscription. For example, Amazon Web Services (AWS) offers a speech-to-text service called Amazon Transcribe, which is priced based on the duration of audio processing. Prices start at $0.0004 per second of audio processed. Another one – IBM Watson – offers a speech-to-text service that is priced based on the duration of the audio processing. Prices start at $0.02 per minute of audio processed.
Language and accent support
If your company operates in multiple countries or has a diverse workforce with different accents, it is important to choose an STT service that can accurately transcribe speech in different languages and accents. Due to accents, inflections, and many languages, it is difficult to obtain highly accurate speaker-independent voice recognition. 90% to 95% of speech recognition attempts are accurate. This also reduces the word error rate which can effect the accuracy of automatic speech recognition.
Integration with other systems
You should also consider how well the speech-to-text engines integrate with other systems and tools that you already use, such as customer relationship management (CRM) systems, transcription software, and video conferencing platforms. Also, STT recognition engine should cover voice-based search, document management, large-scale voice data processing, etc. Additionally, the program must host and process speech data in a compliant data center that respects user privacy and doesn’t compromise confidential company data.
By evaluating STT services based on these factors, you can choose the service that best fits your company’s needs and budget, and ensure that you are able to take full advantage of the benefits of speech-to-text technology. Machine learning has improved over the years and has gained popularity in different areas. Because of that, automatic speech recognition results can definitely effect your daily work life in a positive way.
isLucid as a speech-to-text service and much more
isLucid bridges verbal information with task management software, allowing team members to focus on the discussion and have organized written information. This helps to make a better decision-making process and keep teams aligned. Information from conversations are being organized in seconds and stored to any chosen task management platform, CRM or ATS. All the meetings become searchable, sharable, and actionable. By using integrated GPT3 notes and tasks are paraphrased and ready to go.
Communication between team members can become clear because of actionable items such as tasks, bookmarks, or meeting minutes. This helps to save time on keeping in touch with all decisions made during the meeting. With isLucid, organize and access all of your meetings at any time – they are stored for an unlimited amount of time. You can go back to a meeting that happened a long time ago and organize it the they you like or share it with your colleagues.
If you are interested in isLucid digital meeting assistant, get it for MS Teams.
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