Jana Roßbach, Study Author, Carl Von Ossietzky University The researchers calculated how many words per sentence a listener understands using automatic speech recognition (ASR).

Speech recognition has roots that go back to the days of Thomas Edison ’s phonograph. Machine translation, which began to evolve in the 1950s, is newer. The two technologies working effectively ...

Today, powered by the latest technologies like Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning, speech recognition is touching new milestones.

How can organisations go about improving recognition of speech/audio within machine learning? As with many of machine learning’s biggest challenges, it comes down to the data. The use of manually ...

In the final stage of the training pipeline, downstream tasks such as automatic voice recognition or automatic speech translation are fine-tuned using minimal supervised data.

Dr. Wayne Ward is a Research Professor at CU Boulder whose research involves applying supervised machine learning to the tasks of automatic speech recognition, dialog modeling and extracting semantic ...

Discover how FPGA-accelerated automatic speech recognition (ASR) models are reshaping the landscape of speech-to-text applications by enabling faster inference, significantly reduced latency, and ...

The global speech and voice recognition market is projected to grow from USD 9.66 billion in 2025 to USD 23.11 billion by ...