Artificial intelligence primed for voice recordings

Artificial Intelligence has the ability to process natural language and generate one. This is one of the most profound applications among various others of Artificial Intelligence. This can be done for any language; currently in English.

Algorithms, which are built for these functionalities, sifts through data that deals in words, meaning implied, in various scenarios, to give as much authenticity and context to the outputs. To advance in this feature, neural networks are dedicated that can listen to a certain on-going voice recording, be it live or pre-recorded, to parse them accordingly, and correlate the parsed data with previously fed and processed data, to find a match and provide output.

To readers who are new to the concept of how artificial intelligence works, certain algorithms are trained using various mathematical theories, applied to more than one layer of interconnected layers of algorithms, whose soul work is to sift, filter and analyse data to recognize and match patterns, to learn and put it in its memory. When they are fed with fresh information, to get an output from it, these algorithms process the information and utilise their previous learnings to return desired outputs.

Taking this basic flow into consideration, certain algorithms like ‘Eva’ listens to spoken voices, process the natural language, recognise and match with its costumed experiences, and transcribe it back in words using natural language generation technique. This is not a small feat.

In some cases, like ‘Lyrebird’, algorithms listen to voice recordings, evaluate it using NLP (Natural Language Processing), matched the phenomes, tonal quality, voice bass, and other acoustical properties and audio features, to duplicate it and talk back something meaningful in that same voice. It’s like an artificial mimic artist. Like photo shopped pictures, there are faked voices available too.

Hence listening to voice and processing it to produce meaningful insights out of it, is enabling people to make informed decision or look into a scenario that might have been missed by people. Using NLP and NLG, businesses and consumers can ease many of their redundant work. Voice assistant who can simultaneously transcribe can be used by business executives automatically compose mails, doctors quickly prescribe treatment, researchers simultaneously taking note of the experiment without stopping to write their observations, teachers creating assignments and course works for students, and minutes of the meeting prepared during on-going meeting events.

Artificial Intelligence is gearing up to do more with voice.

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