AS Roma
PulseAugur coverage of AS Roma — every cluster mentioning AS Roma across labs, papers, and developer communities, ranked by signal.
No coverage in the last 90 days.
-
Voice AI paradox: Advanced chat, basic failures
Voice AI assistants like Yandex's Alisa exhibit a paradox of advanced conversational abilities alongside basic functional failures, stemming from their complex architecture. This hybrid system combines speech recognitio…
-
Sakana AI's KAME architecture injects LLM knowledge into speech AI without latency
Sakana AI has developed KAME, a novel tandem architecture for speech-to-speech AI that aims to combine the speed of direct systems with the knowledge depth of LLM-based approaches. KAME operates with two asynchronous co…
-
Tamazight single-speaker speech dataset released on Hugging Face
A new single-speaker speech dataset for the Tamazight language has been released on Hugging Face and the Mozilla Data Collective. This dataset is intended for use in AI applications such as automatic speech recognition …
-
Researchers enhance elderly ASR with LLM paraphrasing and speech synthesis
Researchers have developed a novel data augmentation technique to improve automatic speech recognition (ASR) for elderly individuals. This method utilizes large language models to paraphrase existing transcripts, genera…
-
New LLMs unify audio and language processing for full-duplex and medical applications
Researchers have developed UAF, a novel unified audio front-end LLM designed for full-duplex speech interaction. This model integrates diverse audio front-end tasks like voice activity detection and turn-taking into a s…
-
MedSpeak framework improves medical QA by correcting ASR errors with knowledge graphs
Researchers have developed MedSpeak, a new framework designed to improve the accuracy of spoken question-answering systems in the medical domain. This system utilizes a medical knowledge graph to aid automatic speech re…
-
New framework identifies demographic unfairness in speech recognition models
A new research paper identifies two types of errors—random variance and systematic bias—that contribute to demographic unfairness in speech recognition models. The study found that while both error types are present, ra…
-
"This Wasn't Made for Me": ASR Bias Hurts Users Emotionally and Cognitively
A new research paper highlights the emotional and psychological toll of bias in Automatic Speech Recognition (ASR) systems. The study, which involved user experience research in four U.S. locations, found that participa…