Enable javascript in your browser for better experience. Need to know to enable it? Go here.
As informações desta página não estão completamente disponíveis no seu idioma de escolha. Esperamos disponibiliza-las integralmente em outros idiomas em breve. Para ter acesso às informações no idioma de sua preferência, faça o download do PDF aquí.
Atualizado em : Mar 29, 2017
NÃO ENTROU NA EDIÇÃO ATUAL
Este blip não está na edição atual do Radar. Se esteve em uma das últimas edições, é provável que ainda seja relevante. Se o blip for mais antigo, pode não ser mais relevante e nossa avaliação pode ser diferente hoje. Infelizmente, não conseguimos revisar continuamente todos os blips de edições anteriores do Radar. Saiba mais
Mar 2017
Avalie ?

Nuance Mix is a framework for natural language processing from the company that created the speech-to-text technology behind Dragon Speaking and the first roll-out of Siri. This framework supports the creation of grammars that allow for free-form user interaction via voice. The developer defines a domain-specific grammar that the framework can train itself to understand. The outcomes are responses to user input that identify the user's intents and interaction concepts. At first, it is limited to phrases close to the ones used to train it, but over time it can start to identify meaning from more divergent phrasing. Though it is still in beta, the accuracy from early exploration has been compelling, and the eventual product is one to watch for application forms that could benefit from hands-free user interaction—including mobile, IoT, AR, VR and interactive spaces.

Nov 2016
Avalie ?

Nuance Mix is a framework for natural language processing from the company that created the speech-to-text technology behind Dragon Speaking and the first roll-out of Siri. This framework supports the creation of grammars that allow for free-form user interaction via voice. The developer defines a domain-specific grammar that the framework can train itself to understand. The outcomes are responses to user input that identify the user's intents and interaction concepts. At first, it is limited to phrases close to the ones used to train it, but over time it can start to identify meaning from more divergent phrasing. Though it is still in beta, the accuracy from early exploration has been compelling, and the eventual product is one to watch for application forms that could benefit from hands-free user interaction—including mobile, IoT, AR, VR and interactive spaces.

Publicado : Nov 07, 2016

Baixe o PDF

 

 

 

English | Español | Português | 中文

Inscreva-se para receber o boletim informativo Technology Radar

 

 

Seja assinante

 

 

Visite nosso arquivo para acessar os volumes anteriores