![]() Nevertheless, ASR accuracy has continued to improve, reaching human parity on more datasets and in more use cases. have pointed out, such optimistic results do not hold up on data reflecting natural human speech spoken by a diverse population. In 2016, 6 years ago already, Microsoft Research published an article announcing they had reached human performance (as measured using Word Error Rate, WER) on a 25-year old data set called Switchboard. Source: Hannun, Awni, “ Speech Recognition is not Solved ”. Finally, speech recognition will engender the principles of responsible AI, and operate without bias." Humans and machines will collaborate seamlessly, allowing machines to learn new words and speech styles organically. "By 2030, speech recognition will feature truly multilingual models, rich standardized output objects, and be available to all and at scale. These new use-cases and customers are pushing the requirements for ASR, which is accelerating research. We are seeing more companies offering automated captions to live videos, making live content accessible to more people. Keeping a record of important interactions, and perhaps identifying interactions before they become dangerous, could save lives. For example, as ASR gets better with very noisy environments, it can be used effectively in police body cams, to automatically record and transcribe interactions. These developments are not only improving existing uses of the technology, such as Siri’s and Alexa’s accuracies, but they are also expanding the market ASR technology serves. ![]() We truly are at the onset of big changes in the ASR field and of massive adoption of the technology. ![]() ![]() This confluence of forces has produced an amazing momentum shift in commercial ASR. The accelerated success of ASR deployments is due to many factors, including the growing ecosystem of freely available toolkits, more open source datasets, and a growing interest on the part of engineers and researchers in the ASR problem. The last two years have been some of the most exciting and highly anticipated in Automatic Speech Recognition’s (ASR’s) long and rich history, as we saw multiple enterprise-level fully neural network-based ASR models go to market (e.g. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |