Automatic Speech Recognition (ASR) systems have long struggled to accurately recognize and process stuttered speech, largely due to their training on fluency-biased datasets. As a result, people who stutter (PWS) frequently encounter challenges when using voice-activated technologies, automated transcription services, and other speech-based AI tools. This lack of inclusivity and […]
By Charan Sridhar (Research & Engineering Intern at AImpower.org) Introduction to Speech to Text Software Automated Speech Recognition (ASR) technologies are something most of us take for granted. These technologies process spoken language and convert it into written text, and most of us use them nearly every day through tools […]
The ACM CHI Conference on Human Factors in Computing Systems is one of the biggest, most renowned research conference on Human Computer Interactions – and, according to the president of ACM during the conference opening speech, “the only ACM conference that includes 'human’ in it’s name”. As we study and […]
By Shaomei Wu I was very excited to speak at American Association for Advancements in Science’s Annual Meeting last week in Denver, with the support and sponsorship from the American Speech-Language-Hearing Association (ASHA). This year’s meeting theme is “Science without Walls”, which aligns so well with AImpower.org’s mission to dismantle […]
By sharing our experience and findings from StammerTalk’s stuttered speech collection project, we advocate for a new AI data paradigm of community data stewardship, especially for data from and about marginalized communities.
I recently attended the “Voice-Activated AI for Stuttered Speech Convergence Symposium” organized by Michigan State University, Friends, and West Michigan University. I was honored to speak at Sociotechnical Challenges in Voice-Activated AI Panel with a fantastic group of panelists and participants from academic, industry, and nonprofits. It was an incredible […]
Lindsay and Shaomei had a discussion about Shaomei's recent experience at the National Stuttering Association annual conference, covering topics across AImpower's goals, Shaomei's personal identity as PWS, her connection to the stuttering community, and the lessons she learned at the conference.
Speech recognition technology has progressed a lot in recent years, especially when using modern deep learning techniques. While new models such as Facebook AI Research’s wav2vec has achieved 2.43 WER (Word Error Rate) in research benchmark dataset, their performance usually tanks when processing atypical speech, such as, speech by people who stutter, […]