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.
AI Generated Robotic Content

Share
Published by
AI Generated Robotic Content

Recent Posts

A Complete Guide to Matrices for Machine Learning with Python

Matrices are a key concept not only in linear algebra but also with regard to…

8 hours ago

An Efficient and Streaming Audio Visual Active Speaker Detection System

This paper delves into the challenging task of Active Speaker Detection (ASD), where the system…

8 hours ago

Benchmarking Amazon Nova and GPT-4o models with FloTorch

Based on original post by Dr. Hemant Joshi, CTO, FloTorch.ai A recent evaluation conducted by…

8 hours ago

How Google Cloud measures its climate impact through Life Cycle Assessment (LCA)

As AI creates opportunities for business growth and societal benefits, we’re working to reduce their…

8 hours ago

Sony testing AI to drive PlayStation characters

PlayStation characters may one day engage you in theoretically endless conversations, if a new internal…

9 hours ago

15-inch MacBook Air (M4, 2025) Review: Bluer and Better

The latest 15-inch MacBook Air is bluer and better than ever before—and it dropped in…

9 hours ago