In the past few years, automatic speech recognition (ASR) has become common practice, with billions of voice-enabled products and services. A wide variety of ASR technologies exists, each suited for different use cases. Undeniably though, the holy grail of ASR is natural language processing (NLP), which lets users speak freely, as if they were talking to another person. A simple example is that you can say “Set a reminder for 9AM the day after tomorrow” to any of the leading virtual assistants like Alexa, Google Assistant, Siri or Cortana, and they would understand the intent. There is no specific order or magic word that you have to say. You could also say “remind me on Wednesday at 9 in the morning” or “set a reminder on May 16th at 9 AM” and get the same result. The bottom line in NLP is extracting the meaning, regardless of the phrasing.
Read the full article on Embedded Computing Design.
You might also like
More from Audio / Voice
LE Audio and Auracast Aim to Personalize the Audio Experience
We live in a noisy world. At an airport trying to hear flight update announcements through the background clamor, in …
Evaluating Spatial Audio – Part 1 – Criteria & Challenges
We here at Ceva, have spoken at length about spatial audio before, including this blog post talking about what it …
AI Audio for Voice Enhancement: Deep into the Deep – Part 3
It is Tomer again with more about ENC! Throughout this journey, we've laid the foundation with an introduction and explored …