What are Voice Assistants, and how do they Recognize Languages? Voice assistants are now on everyone’s lips. They are among the biggest innovative home trends and are now inspiring more and more newcomers to technology, thanks to their ease of use. When used correctly, voice-controlled systems and components can make everyday life much more accessible and provide entertainment. Amazon’s Alexa, Google‘s Assistant, Apple’s Siri, Microsoft’s Cortana, and Samsung’s Bixby compete in favor of intelligent home fans. We show which two voice assistants are ahead and explain what makes them so popular. We also provide an overview of the most important strengths and weaknesses.
What is a voice assistant?
A specific type of software serves as a personal assistant that analyzes spoken words, puts them into the correct context, and reacts to them. Voice assistants, sometimes also referred to as mobile assistants, are usually integrated into smartphones or smart speakers. If you talk to these end devices, the device answers verbal questions via voice software or controls, e.g., B. Smart home devices connected to it. The most popular voice assistant is currently Alexa from Amazon.
How will the weather be tomorrow? Digital voice assistants that can answer such questions can be found in more and more smartphones, loudspeakers, and laptops. They are calling Siri, Alexa, Cortana, or Google Assistant. If IT companies have their way, they will find more and more devices and situations in the future.
Instead of being operated with a keyboard or touchscreen, they listen to something typically human and highly complex: language. Attempts to teach machines to hear and speak are not new. So far, however, they have only been used in a few precisely controlled situations, such as in telephone waiting loops. The users had to adapt to the machine’s minimal horizon rather than the other way around.
How do assistants recognize the language?
In recent years, the technology has been further developed so that digital assistants can identify many everyday expressions, even when the washing machine is running in the background. There are several developments behind this. So that a digital assistant can answer questions about the weather. For example, techniques that are part of Artificial Intelligence (AI) are using at various points. The computing power required for this is provided via the Internet or is in the processor of a smartphone.
However, If the assistant is asking: How is the weather going? The first thing to do is recognize such a sentence in the acoustic signal. This speech recognition often takes place on the provider’s servers. Where the assistants usually send all the data that they are entrusted with. For this purpose, the sound sequence breaks down into its most minor components and searches for characteristic features. Finally, the program stubbornly calculates the probability that it is a particular phrase.
The machine learning approach does not involve programming the assistant with rules in advance – such as how language works. Instead, they are initially given extensive collections of data to train them. Machines learn differently than humans, but they all have one thing in common: Trial and error make you bright. In the mountains of data, you will find complex statistical relationships, the structure of which follows the rules of language, for example. Little by little, they gain a model from the data. This approach is often enough to be able to use them for everyday tasks.
But speech recognition alone is not enough. To provide a suitable answer, the assistant must recognize what intention a user associates with the uttered sentence. Language is also ambiguous: a sentence can often not interpreting without context. IT companies are currently mobilizing all their resources to teach assistants such skills.
An example: If someone in Hamburg asks the assistant first about a train to Munich, then about the weather, it may be about the weather in Munich. The Wizards to understand the general knowledge link to large fact databases, such as Google’s “Knowledge Graph” or Microsoft’s “Satori Knowledge.” The users are also constantly providing the providers with data that the assistants can use to learn.
Intelligence remains limited
Despite all the technical developments, the assistants’ skills remain limited to a few precisely defined areas and aspects of life. So this applies to the development of AI as a whole. Literature and cinema have long devised general AI that can take on any human task. Again and again, it seems to some researchers that computer science was on the verge of a breakthrough. To such a superintelligence. But time and again, it turning out that the prognosis was based on wrong assumptions and was too optimistic.
However, the more the digital assistants know about their owners, the sooner they can become active on their own. They then warn of traffic jams on the way to work, for example, even before you have set off. Using a search engine may soon seem old-fashioned.
It is, therefore, possible that digital assistants are only harbingers of a development in which artificial intelligence is not opposing to human intelligence but instead expands people’s skills and senses, as tools and media have always done. The price is that learning systems assist us better the more they are permanent data collectors. hopefully, you have understood the Article What are Voice Assistants and how do they Recognize Languages?