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 ...

A European agency report on artificial intelligence includes this image in a section that says "the opportunities created by AI can also contribute to better understanding and consequently mitigation ...

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 ...

Objectives: This study aimed to analyze the relationship between tinnitus and speech audiometry results. Materials and methods: In this investigation, 314 patients with primary subjective tinnitus and ...

Astral's uv utility simplifies and speeds up working with Python virtual environments. But it has some other superpowers, too: it lets you run Python packages and programs without having to formally ...

Mistral AI has released Voxtral, a family of open-weight models—Voxtral-Small-24B and Voxtral-Mini-3B—designed to handle both audio and text inputs. Built on top of Mistral’s language modeling ...

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 ...