More than a million people around the world rely on cochlear implants (CIs) to hear. CI effectiveness is generally evaluated through speech recognition tests, and despite how widespread they are, CI ...

Abstract: This brief presents an edge-AIoT speech recognition system, which is based on a new spiking feature extraction (SFE) method and a PoolFormer (PF) neural network optimized for implementation ...

Optimizing only for Automatic Speech Recognition (ASR) and Word Error Rate (WER) is insufficient for modern, interactive voice agents. Robust evaluation must measure ...

British authorities have ramped up the use of facial recognition, artificial intelligence and internet regulation to address crime and other issues, stoking concerns of surveillance overreach. British ...

Automatic Speech Recognition (ASR) System Analysis This repository contains Speech Recognition Robustness in Noisy Environments, where we analyze audio features, evaluate ASR models (Vosk & Whisper) ...

In today’s voice-first world, it’s not enough for systems to simply hear what users say. They need to understand it with precision. In high-stakes environments like healthcare, finance, or enterprise ...

The Allen Institute for AI (AI2) has released OLMoASR, a suite of open automatic speech recognition (ASR) models that rival closed-source systems such as OpenAI’s Whisper. Beyond just releasing model ...

Here's a closer look at the programming behind my animatronic mouth. Using Arduino, Python, and a few open-source libraries, I take a typed sentence and convert it into an animation sequence.

Every time you say something to Alexa or Siri, or use voice to text to send a text message, you’re using artificial intelligence. While those programs can be pretty accurate, there’s plenty of times ...