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

Anima – Sharing Some Prompts and Results

Been experimenting with Anima lately and ended up spending way too much time refining prompts.…

16 hours ago

Keychron K2 HE Concrete Edition Review: Rock-Solid Typing

Keychron's K2 HE Concrete Edition sounds like a cute gimmick, but as I discovered, there's…

17 hours ago

AI generates full battery electrolyte recipes, matching top lithium metal battery performance

Battery electrolytes aren't just one chemical, but a complex mixture of salts, solvents, and additives…

17 hours ago

Nava – A 6.3B audio-video model .

Page: https://ernie-research.github.io/NAVA/ Model: https://huggingface.co/ernie-research/NAVA Github: https://github.com/ernie-research/NAVA NAVA is a 6.3 B-parameter joint audio-video generator that…

2 days ago

Enterprise Business Software and the Mixed-Up Chameleon Problem

Editor’s Note: This blog post was written by Greg Little, Senior Counselor at Palantir, with…

2 days ago

High-Throughput Graph Abstraction at Netflix: Part I

By Oleksii Tkachuk, Kartik Sathyanarayanan, Rajiv ShringiIntroductionNetflix has a diverse range of graph use cases, each…

2 days ago