Technology has made everything more convenient for everyone. However, it also made it impossible for the world to be able to live without it. It has become an essential part of human life on a daily basis from simple household chores to transportation. To keep up with the activity demands of human life, technology kept on evolving. Day by day, technological advancements are studied and new operational machines are invented. As long as there’s something that can be made more convenient, technology will continue to persist.
Aside from making life easier for everyone, the technology that we have today is getting more intelligent. Whether it’s in the US, Europe or even in Asia, newly-discovered and invented technologies became more accessible for everyone to use. These advancements of science make it uncomplicated for humans to live in this fast-paced world where 24 hours seems to be not enough to be called a day.
Technology is slowly mimicking human intelligence. Technologies such as Artificial Intelligence (AI) and machine learning became tools to create newer breakthroughs and branches of technology. Several businesses in the international market are slowly transitioning to use AI in their future projects. AI opened up new opportunities for companies to grow and contribute to how society is keeping up with technology. Now, let us understand why we need data collection for AI.
Data Collection for AI
Artificial Intelligence (AI) is continuously advancing over time. AI is becoming more and more human as it feeds on chunks of data. At present, AI can already make human-like decisions and answer questions in complete sentences. For AI to become more intelligent, it needs to feed on more recent data.
Data for AI
Data fed to AI can either be mined or made. Mined data comes from online databases and various online sources. There are several companies that actually sell this type of data. Made data is from customized and specified data collection. Data collection is essential to AI. It can help AI to have specialized and specific functions depending on where it’s needed. Let’s take speech recognition as an example. In speech recognition, audio and speech data collection is used to gather the data to be fed to its AI. Just like AI, language is evolving as well. So, up-to-date audio and speech data is needed to also update what’s being fed to the AI.
Speech recognition became relevant in terms of communication. Speech recognition made it more convenient to search information on the web, to give out commands, to have voice control on smart devices remotely, and to communicate with friends, family, and loved ones. The application of speech recognition also became rampant. Several apps and in the market are making a case to incorporate speech recognition in their services. With this, various data collection services and processes have been in demand to make AI in apps, software, and even hardware, smarter.
Audio and Speech Data Collection for AI
One may wonder “Why would there be a need to collect audio and speech data?”. The answer is simple. The AI in speech recognition needs to be up to date. Therefore, the data that it feeds on also needs to be updated. Audio and speech data collection for AI projects is not new and it’s mostly done for speech, voice, and audio recognition. The data collected in the process are audio and speech samples paired with their transcriptions. These samples can either be scripted, scenario-based or conversational depending on what the client needs and what needs to be fed to the AI. At CCCI, part of our audio and speech data collection services is making sure that we understand what your business and your AI needs.
How Audio and Speech Data are Processed for Machine Learning
Audio and speech data are used in training the machine learning algorithms of your AI projects. The audio and speech recordings as well as their transcriptions are fed to the said algorithm and act as training data. The algorithm of the training data is coded by engineers and developers in such a way that the machine comprehends and understands them. The system will then be taught to identify the speech, voice, and language patterns within the sample data.
To add more, the meaning of words conversed within the samples is also taught to the AI. Natural language will also be analyzed in this process. The AI will also be taught to identify different dialects and language sets so it can communicate and respond appropriately.
Collecting audio and speech data for AI projects may sound simple but it’s actually a bit more complicated than that. Different business industries such as finance and banking, health, transportation, gaming, and many more are already using AI in their services. AI in speech recognition paved the way to further develop the technology to be more accessible for everyone. Applying AI, let alone speech recognition, helped businesses identify problems and give out quick solutions to those.