Categories: AI/ML News

Machine listening: Making speech recognition systems more inclusive

One group commonly misunderstood by voice technology are individuals who speak African American English, or AAE. Researchers designed an experiment to test how AAE speakers adapt their speech when imagining talking to a voice assistant, compared to talking to a friend, family member, or stranger. The study tested familiar human, unfamiliar human, and voice assistant-directed speech conditions by comparing speech rate and pitch variation. Analysis of the recordings showed that the speakers exhibited two consistent adjustments when they were talking to voice technology compared to talking to another person: a slower rate of speech with less pitch variation.

IBM’s new Watson Large Speech Model brings generative AI to the phone

Most everyone has heard of large language models, or LLMs, since generative AI has entered our daily lexicon through its amazing text and image generating capabilities, and its promise as a revolution in how enterprises handle core business functions. Now, more than ever, the thought of talking to AI through a chat…

January 4, 2024

In "FAANG"

Is your conversational AI setting the right tone?

Conversational AI is too artificial Nothing is more frustrating than calling a customer support line to be greeted by a monotone, robotic, automated voice. The voice on the other end of the phone is taking painfully long to read you the menu options. You’re two seconds away from either hanging…

September 27, 2022

In "FAANG"

Improving Voice Trigger Detection with Metric Learning

Voice trigger detection is an important task, which enables activating a voice assistant when a target user speaks a keyword phrase. A detector is typically trained on speech data independent of speaker information and used for the voice trigger detection task. However, such a speaker independent voice trigger detector typically…

September 3, 2022

In "FAANG"

AI Generated Robotic Content