Open source TTS models Kokoro, Orpheus, and Piper are tested on symbols, abbreviations, and prosody with CER and MOS results.

Enterprise AI company Cohere on Thursday launched its first voice model: Transcribe is an open source automatic speech recognition model that can be used for tasks like note-taking and speech analysis ...

Abstract: An automatic speech recognition system is important to help Muslims recite the Holy Quran accurately. Most existing research ignores a wide range of potential users (reciters) in their ...

AI cyberattacks are rapidly transforming the cybersecurity landscape, enabling attackers to automate and scale operations with unprecedented speed. Through machine learning hacking, adversaries can ...

The context of inclusive education for blind people lacks suitable learning materials and traditional devices are difficult to expand, creating a need for a personalized technological solution. This ...

LAS VEGAS--(BUSINESS WIRE)--Deepgram, the world’s most realistic and real-time Voice AI platform, today announced integration of its enterprise-grade speech-to-text (STT) and text-to-speech (TTS) ...

Willkommen. Bienvenue. Welcome. C’mon in. Meta has unveiled Omnilingual Automatic Speech Recognition (ASR), an AI system that can transcribe speech in over 1,600 languages — including 500 low-resource ...

How do you build a single speech recognition system that can understand 1,000’s of languages including many that never had working ASR (automatic speech recognition) models before? Meta AI has ...

Meta has just released a new multilingual automatic speech recognition (ASR) system supporting 1,600+ languages — dwarfing OpenAI’s open source Whisper model, which supports just 99. Is architecture ...

Mental disorders have a significant impact on many areas of people’s life, particularly on affective regulation; thus, there is a growing need to find disease-specific biomarkers to improve early ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...